An integral design strategy combining optical system and image processing to obtain high resolution images

NASA Astrophysics Data System (ADS)

Wang, Jiaoyang; Wang, Lin; Yang, Ying; Gong, Rui; Shao, Xiaopeng; Liang, Chao; Xu, Jun

2016-05-01

In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.

Integrated circuit layer image segmentation

NASA Astrophysics Data System (ADS)

Masalskis, Giedrius; Petrauskas, Romas

2010-09-01

In this paper we present IC layer image segmentation techniques which are specifically created for precise metal layer feature extraction. During our research we used many samples of real-life de-processed IC metal layer images which were obtained using optical light microscope. We have created sequence of various image processing filters which provides segmentation results of good enough precision for our application. Filter sequences were fine tuned to provide best possible results depending on properties of IC manufacturing process and imaging technology. Proposed IC image segmentation filter sequences were experimentally tested and compared with conventional direct segmentation algorithms.

Combining image-processing and image compression schemes

NASA Technical Reports Server (NTRS)

Greenspan, H.; Lee, M.-C.

1995-01-01

An investigation into the combining of image-processing schemes, specifically an image enhancement scheme, with existing compression schemes is discussed. Results are presented on the pyramid coding scheme, the subband coding scheme, and progressive transmission. Encouraging results are demonstrated for the combination of image enhancement and pyramid image coding schemes, especially at low bit rates. Adding the enhancement scheme to progressive image transmission allows enhanced visual perception at low resolutions. In addition, further progressing of the transmitted images, such as edge detection schemes, can gain from the added image resolution via the enhancement.

Comparison of breast percent density estimation from raw versus processed digital mammograms

NASA Astrophysics Data System (ADS)

Li, Diane; Gavenonis, Sara; Conant, Emily; Kontos, Despina

2011-03-01

We compared breast percent density (PD%) measures obtained from raw and post-processed digital mammographic (DM) images. Bilateral raw and post-processed medio-lateral oblique (MLO) images from 81 screening studies were retrospectively analyzed. Image acquisition was performed with a GE Healthcare DS full-field DM system. Image post-processing was performed using the PremiumViewTM algorithm (GE Healthcare). Area-based breast PD% was estimated by a radiologist using a semi-automated image thresholding technique (Cumulus, Univ. Toronto). Comparison of breast PD% between raw and post-processed DM images was performed using the Pearson correlation (r), linear regression, and Student's t-test. Intra-reader variability was assessed with a repeat read on the same data-set. Our results show that breast PD% measurements from raw and post-processed DM images have a high correlation (r=0.98, R2=0.95, p<0.001). Paired t-test comparison of breast PD% between the raw and the post-processed images showed a statistically significant difference equal to 1.2% (p = 0.006). Our results suggest that the relatively small magnitude of the absolute difference in PD% between raw and post-processed DM images is unlikely to be clinically significant in breast cancer risk stratification. Therefore, it may be feasible to use post-processed DM images for breast PD% estimation in clinical settings. Since most breast imaging clinics routinely use and store only the post-processed DM images, breast PD% estimation from post-processed data may accelerate the integration of breast density in breast cancer risk assessment models used in clinical practice.

A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study.

PubMed

Lizarraga, Gabriel; Li, Chunfei; Cabrerizo, Mercedes; Barker, Warren; Loewenstein, David A; Duara, Ranjan; Adjouadi, Malek

2018-04-26

Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. ©Gabriel Lizarraga, Chunfei Li, Mercedes Cabrerizo, Warren Barker, David A Loewenstein, Ranjan Duara, Malek Adjouadi. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.04.2018.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

SU-E-J-42: Motion Adaptive Image Filter for Low Dose X-Ray Fluoroscopy in the Real-Time Tumor-Tracking Radiotherapy System.

PubMed

Miyamoto, N; Ishikawa, M; Sutherland, K; Suzuki, R; Matsuura, T; Takao, S; Toramatsu, C; Nihongi, H; Shimizu, S; Onimaru, R; Umegaki, K; Shirato, H

2012-06-01

In the real-time tumor-tracking radiotherapy system, fiducial markers are detected by X-ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy. © 2012 American Association of Physicists in Medicine.

Image Segmentation Using Minimum Spanning Tree

NASA Astrophysics Data System (ADS)

Dewi, M. P.; Armiati, A.; Alvini, S.

2018-04-01

This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

The Pan-STARRS PS1 Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Magnier, E.

The Pan-STARRS PS1 Image Processing Pipeline (IPP) performs the image processing and data analysis tasks needed to enable the scientific use of the images obtained by the Pan-STARRS PS1 prototype telescope. The primary goals of the IPP are to process the science images from the Pan-STARRS telescopes and make the results available to other systems within Pan-STARRS. It also is responsible for combining all of the science images in a given filter into a single representation of the non-variable component of the night sky defined as the "Static Sky". To achieve these goals, the IPP also performs other analysis functions to generate the calibrations needed in the science image processing, and to occasionally use the derived data to generate improved astrometric and photometric reference catalogs. It also provides the infrastructure needed to store the incoming data and the resulting data products. The IPP inherits lessons learned, and in some cases code and prototype code, from several other astronomy image analysis systems, including Imcat (Kaiser), the Sloan Digital Sky Survey (REF), the Elixir system (Magnier & Cuillandre), and Vista (Tonry). Imcat and Vista have a large number of robust image processing functions. SDSS has demonstrated a working analysis pipeline and large-scale databasesystem for a dedicated project. The Elixir system has demonstrated an automatic image processing system and an object database system for operational usage. This talk will present an overview of the IPP architecture, functional flow, code development structure, and selected analysis algorithms. Also discussed is the HW highly parallel HW configuration necessary to support PS1 operational requirements. Finally, results are presented of the processing of images collected during PS1 early commissioning tasks utilizing the Pan-STARRS Test Camera #3.

A Study of Light Level Effect on the Accuracy of Image Processing-based Tomato Grading

NASA Astrophysics Data System (ADS)

Prijatna, D.; Muhaemin, M.; Wulandari, R. P.; Herwanto, T.; Saukat, M.; Sugandi, W. K.

2018-05-01

Image processing method has been used in non-destructive tests of agricultural products. Compared to manual method, image processing method may produce more objective and consistent results. Image capturing box installed in currently used tomato grading machine (TEP-4) is equipped with four fluorescence lamps to illuminate the processed tomatoes. Since the performance of any lamp will decrease if its service time has exceeded its lifetime, it is predicted that this will affect tomato classification. The objective of this study was to determine the minimum light levels which affect classification accuracy. This study was conducted by varying light level from minimum and maximum on tomatoes in image capturing boxes and then investigates its effects on image characteristics. Research results showed that light intensity affects two variables which are important for classification, for example, area and color of captured image. Image processing program was able to determine correctly the weight and classification of tomatoes when light level was 30 lx to 140 lx.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Steganalysis based on reducing the differences of image statistical characteristics

NASA Astrophysics Data System (ADS)

Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao

2018-04-01

Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.

Visual Communications and Image Processing

NASA Astrophysics Data System (ADS)

Hsing, T. Russell

1987-07-01

This special issue of Optical Engineering is concerned with visual communications and image processing. The increase in communication of visual information over the past several decades has resulted in many new image processing and visual communication systems being put into service. The growth of this field has been rapid in both commercial and military applications. The objective of this special issue is to intermix advent technology in visual communications and image processing with ideas generated from industry, universities, and users through both invited and contributed papers. The 15 papers of this issue are organized into four different categories: image compression and transmission, image enhancement, image analysis and pattern recognition, and image processing in medical applications.

Range and Panoramic Image Fusion Into a Textured Range Image for Culture Heritage Documentation

NASA Astrophysics Data System (ADS)

Bila, Z.; Reznicek, J.; Pavelka, K.

2013-07-01

This paper deals with a fusion of range and panoramic images, where the range image is acquired by a 3D laser scanner and the panoramic image is acquired with a digital still camera mounted on a panoramic head and tripod. The fused resulting dataset, called "textured range image", provides more reliable information about the investigated object for conservators and historians, than using both datasets separately. A simple example of fusion of a range and panoramic images, both obtained in St. Francis Xavier Church in town Opařany, is given here. Firstly, we describe the process of data acquisition, then the processing of both datasets into a proper format for following fusion and the process of fusion. The process of fusion can be divided into a two main parts: transformation and remapping. In the first, transformation, part, both images are related by matching similar features detected on both images with a proper detector, which results in transformation matrix enabling transformation of the range image onto a panoramic image. Then, the range data are remapped from the range image space into a panoramic image space and stored as an additional "range" channel. The process of image fusion is validated by comparing similar features extracted on both datasets.

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

Pre-Processes for Urban Areas Detection in SAR Images

NASA Astrophysics Data System (ADS)

Altay Açar, S.; Bayır, Ş.

2017-11-01

In this study, pre-processes for urban areas detection in synthetic aperture radar (SAR) images are examined. These pre-processes are image smoothing, thresholding and white coloured regions determination. Image smoothing is carried out to remove noises then thresholding is applied to obtain binary image. Finally, candidate urban areas are detected by using white coloured regions determination. All pre-processes are applied by utilizing the developed software. Two different SAR images which are acquired by TerraSAR-X are used in experimental study. Obtained results are shown visually.

Coincident Extraction of Line Objects from Stereo Image Pairs.

DTIC Science & Technology

1983-09-01

4.4.3 Reconstruction of intersections 4.5 Final result processing 5. Presentation of the results 5.1 FIM image processing system 5.2 Extraction results in...image. To achieve this goal, the existing software system had to be modified and extended considerably. The following sections of this report will give...8000 pixels of each image without explicit loading of subimages could not yet be performed due to computer system software problems. m m n m -4- The

Research and Analysis of Image Processing Technologies Based on DotNet Framework

NASA Astrophysics Data System (ADS)

Ya-Lin, Song; Chen-Xi, Bai

Microsoft.Net is a kind of most popular program development tool. This paper gave a detailed analysis concluded about some image processing technologies of the advantages and disadvantages by .Net processed image while the same algorithm is used in Programming experiments. The result shows that the two best efficient methods are unsafe pointer and Direct 3D, and Direct 3D used to 3D simulation development, and the others are useful in some fields while these technologies are poor efficiency and not suited to real-time processing. The experiment results in paper will help some projects about image processing and simulation based DotNet and it has strong practicability.

Digital image comparison by subtracting contextual transformations—percentile rank order differentiation

USGS Publications Warehouse

Wehde, M. E.

1995-01-01

The common method of digital image comparison by subtraction imposes various constraints on the image contents. Precise registration of images is required to assure proper evaluation of surface locations. The attribute being measured and the calibration and scaling of the sensor are also important to the validity and interpretability of the subtraction result. Influences of sensor gains and offsets complicate the subtraction process. The presence of any uniform systematic transformation component in one of two images to be compared distorts the subtraction results and requires analyst intervention to interpret or remove it. A new technique has been developed to overcome these constraints. Images to be compared are first transformed using the cumulative relative frequency as a transfer function. The transformed images represent the contextual relationship of each surface location with respect to all others within the image. The process of differentiating between the transformed images results in a percentile rank ordered difference. This process produces consistent terrain-change information even when the above requirements necessary for subtraction are relaxed. This technique may be valuable to an appropriately designed hierarchical terrain-monitoring methodology because it does not require human participation in the process.

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

Computer-aided light sheet flow visualization using photogrammetry

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1994-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and a visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) results, was chosen to interactively display the reconstructed light sheet images with the numerical surface geometry for the model or aircraft under study. The photogrammetric reconstruction technique and the image processing and computer graphics techniques and equipment are described. Results of the computer-aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images with CFD solutions in the same graphics environment is also demonstrated.

Automatic Feature Extraction System.

DTIC Science & Technology

1982-12-01

exploitation. It was used for * processing of black and white and multispectral reconnaissance photography, side-looking synthetic aperture radar imagery...the image data and different software modules for image queing and formatting, the result of the input process will be images in standard AFES file...timely manner. The FFS configuration provides the environment necessary for integrated testing of image processing functions and design and

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Computer measurement of particle sizes in electron microscope images

NASA Technical Reports Server (NTRS)

Hall, E. L.; Thompson, W. B.; Varsi, G.; Gauldin, R.

1976-01-01

Computer image processing techniques have been applied to particle counting and sizing in electron microscope images. Distributions of particle sizes were computed for several images and compared to manually computed distributions. The results of these experiments indicate that automatic particle counting within a reasonable error and computer processing time is feasible. The significance of the results is that the tedious task of manually counting a large number of particles can be eliminated while still providing the scientist with accurate results.

Designing Image Analysis Pipelines in Light Microscopy: A Rational Approach.

PubMed

Arganda-Carreras, Ignacio; Andrey, Philippe

2017-01-01

With the progress of microscopy techniques and the rapidly growing amounts of acquired imaging data, there is an increased need for automated image processing and analysis solutions in biological studies. Each new application requires the design of a specific image analysis pipeline, by assembling a series of image processing operations. Many commercial or free bioimage analysis software are now available and several textbooks and reviews have presented the mathematical and computational fundamentals of image processing and analysis. Tens, if not hundreds, of algorithms and methods have been developed and integrated into image analysis software, resulting in a combinatorial explosion of possible image processing sequences. This paper presents a general guideline methodology to rationally address the design of image processing and analysis pipelines. The originality of the proposed approach is to follow an iterative, backwards procedure from the target objectives of analysis. The proposed goal-oriented strategy should help biologists to better apprehend image analysis in the context of their research and should allow them to efficiently interact with image processing specialists.

MEMS-based system and image processing strategy for epiretinal prosthesis.

PubMed

Xia, Peng; Hu, Jie; Qi, Jin; Gu, Chaochen; Peng, Yinghong

2015-01-01

Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.

Single image interpolation via adaptive nonlocal sparsity-based modeling.

PubMed

Romano, Yaniv; Protter, Matan; Elad, Michael

2014-07-01

Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

Architecture of the parallel hierarchical network for fast image recognition

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule

2016-09-01

Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.

A new data processing technique for Rayleigh-Taylor instability growth experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, Yongteng; Tu, Shaoyong; Miao, Wenyong

Typical face-on experiments for Rayleigh-Taylor instability study involve the time-resolved radiography of an accelerated foil with line-of-sight of the radiography along the direction of motion. The usual method which derives perturbation amplitudes from the face-on images reverses the actual image transmission procedure, so the obtained results will have a large error in the case of large optical depth. In order to improve the accuracy of data processing, a new data processing technique has been developed to process the face-on images. This technique based on convolution theorem, refined solutions of optical depth can be achieved by solving equations. Furthermore, we discussmore » both techniques for image processing, including the influence of modulation transfer function of imaging system and the backlighter spatial profile. Besides, we use the two methods to the process the experimental results in Shenguang-II laser facility and the comparison shows that the new method effectively improve the accuracy of data processing.« less

Patch-based models and algorithms for image processing: a review of the basic principles and methods, and their application in computed tomography.

PubMed

Karimi, Davood; Ward, Rabab K

2016-10-01

Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselves, have evolved over time. In the past decade, "patch-based" models have emerged as one of the most effective models for natural images. Patch-based methods have outperformed other competing methods in many image processing tasks. These developments have come at a time when greater availability of powerful computational resources and growing concerns over the health risks of the ionizing radiation encourage research on image processing algorithms for computed tomography (CT). The goal of this paper is to explain the principles of patch-based methods and to review some of their recent applications in CT. We first review the central concepts in patch-based image processing and explain some of the state-of-the-art algorithms, with a focus on aspects that are more relevant to CT. Then, we review some of the recent application of patch-based methods in CT. Patch-based methods have already transformed the field of image processing, leading to state-of-the-art results in many applications. More recently, several studies have proposed patch-based algorithms for various image processing tasks in CT, from denoising and restoration to iterative reconstruction. Although these studies have reported good results, the true potential of patch-based methods for CT has not been yet appreciated. Patch-based methods can play a central role in image reconstruction and processing for CT. They have the potential to lead to substantial improvements in the current state of the art.

New method for identifying features of an image on a digital video display

NASA Astrophysics Data System (ADS)

Doyle, Michael D.

1991-04-01

The MetaMap process extends the concept of direct manipulation human-computer interfaces to new limits. Its specific capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. The correlation is accomplished through reprogramming of both the color map and the image so that discrete image elements comprise unique sets of color indices. This process allows the correlation to be accomplished with very efficient data storage and program execution times. Image databases adapted to this process become object-oriented as a result. Very sophisticated interrelationships can be set up between images text and program control mechanisms using this process. An application of this interfacing process to the design of an interactive atlas of medical histology as well as other possible applications are described. The MetaMap process is protected by U. S. patent #4

Quantitative assessment of the impact of biomedical image acquisition on the results obtained from image analysis and processing.

PubMed

Koprowski, Robert

2014-07-04

Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator's (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient's back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects - error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18% for the nose, 10% for the cheeks, and 7% for the forehead. Similarly, when: (7) measuring the anterior eye chamber - there is an error of 20%; (8) measuring the tooth enamel thickness - error of 15%; (9) evaluating the mechanical properties of the cornea during pressure measurement - error of 47%. The paper presents vital, selected issues occurring when assessing the accuracy of designed automatic algorithms for image analysis and processing in bioengineering. The impact of acquisition of images on the problems arising in their analysis has been shown on selected examples. It has also been indicated to which elements of image analysis and processing special attention should be paid in their design.

The vectorization of a ray tracing program for image generation

NASA Technical Reports Server (NTRS)

Plunkett, D. J.; Cychosz, J. M.; Bailey, M. J.

1984-01-01

Ray tracing is a widely used method for producing realistic computer generated images. Ray tracing involves firing an imaginary ray from a view point, through a point on an image plane, into a three dimensional scene. The intersections of the ray with the objects in the scene determines what is visible at the point on the image plane. This process must be repeated many times, once for each point (commonly called a pixel) in the image plane. A typical image contains more than a million pixels making this process computationally expensive. A traditional ray tracing program processes one ray at a time. In such a serial approach, as much as ninety percent of the execution time is spent computing the intersection of a ray with the surface in the scene. With the CYBER 205, many rays can be intersected with all the bodies im the scene with a single series of vector operations. Vectorization of this intersection process results in large decreases in computation time. The CADLAB's interest in ray tracing stems from the need to produce realistic images of mechanical parts. A high quality image of a part during the design process can increase the productivity of the designer by helping him visualize the results of his work. To be useful in the design process, these images must be produced in a reasonable amount of time. This discussion will explain how the ray tracing process was vectorized and gives examples of the images obtained.

Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

NASA Astrophysics Data System (ADS)

Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2016-03-01

Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

Image-plane processing of visual information

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

1984-01-01

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Improved image processing of road pavement defect by infrared thermography

NASA Astrophysics Data System (ADS)

Sim, Jun-Gi

2018-03-01

This paper intends to achieve improved image processing for the clear identification of defects in damaged road pavement structure using infrared thermography non-destructive testing (NDT). To that goal, 4 types of pavement specimen including internal defects were fabricated to exploit the results obtained by heating the specimens by natural light. The results showed that defects located down to a depth of 3 cm could be detected by infrared thermography NDT using the improved image processing method.

Multiscale image processing and antiscatter grids in digital radiography.

PubMed

Lo, Winnie Y; Hornof, William J; Zwingenberger, Allison L; Robertson, Ian D

2009-01-01

Scatter radiation is a source of noise and results in decreased signal-to-noise ratio and thus decreased image quality in digital radiography. We determined subjectively whether a digitally processed image made without a grid would be of similar quality to an image made with a grid but without image processing. Additionally the effects of exposure dose and of a using a grid with digital radiography on overall image quality were studied. Thoracic and abdominal radiographs of five dogs of various sizes were made. Four acquisition techniques were included (1) with a grid, standard exposure dose, digital image processing; (2) without a grid, standard exposure dose, digital image processing; (3) without a grid, half the exposure dose, digital image processing; and (4) with a grid, standard exposure dose, no digital image processing (to mimic a film-screen radiograph). Full-size radiographs as well as magnified images of specific anatomic regions were generated. Nine reviewers rated the overall image quality subjectively using a five-point scale. All digitally processed radiographs had higher overall scores than nondigitally processed radiographs regardless of patient size, exposure dose, or use of a grid. The images made at half the exposure dose had a slightly lower quality than those made at full dose, but this was only statistically significant in magnified images. Using a grid with digital image processing led to a slight but statistically significant increase in overall quality when compared with digitally processed images made without a grid but whether this increase in quality is clinically significant is unknown.

Automation of image data processing. (Polish Title: Automatyzacja proces u przetwarzania danych obrazowych)

NASA Astrophysics Data System (ADS)

Preuss, R.

2014-12-01

This article discusses the current capabilities of automate processing of the image data on the example of using PhotoScan software by Agisoft. At present, image data obtained by various registration systems (metric and non - metric cameras) placed on airplanes, satellites, or more often on UAVs is used to create photogrammetric products. Multiple registrations of object or land area (large groups of photos are captured) are usually performed in order to eliminate obscured area as well as to raise the final accuracy of the photogrammetric product. Because of such a situation t he geometry of the resulting image blocks is far from the typical configuration of images. For fast images georeferencing automatic image matching algorithms are currently applied. They can create a model of a block in the local coordinate system or using initial exterior orientation and measured control points can provide image georeference in an external reference frame. In the case of non - metric image application, it is also possible to carry out self - calibration process at this stage. Image matching algorithm is also used in generation of dense point clouds reconstructing spatial shape of the object (area). In subsequent processing steps it is possible to obtain typical photogrammetric products such as orthomosaic, DSM or DTM and a photorealistic solid model of an object . All aforementioned processing steps are implemented in a single program in contrary to standard commercial software dividing all steps into dedicated modules. Image processing leading to final geo referenced products can be fully automated including sequential implementation of the processing steps at predetermined control parameters. The paper presents the practical results of the application fully automatic generation of othomosaic for both images obtained by a metric Vexell camera and a block of images acquired by a non - metric UAV system

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

Realization of the FPGA-based reconfigurable computing environment by the example of morphological processing of a grayscale image

NASA Astrophysics Data System (ADS)

Shatravin, V.; Shashev, D. V.

2018-05-01

Currently, robots are increasingly being used in every industry. One of the most high-tech areas is creation of completely autonomous robotic devices including vehicles. The results of various global research prove the efficiency of vision systems in autonomous robotic devices. However, the use of these systems is limited because of the computational and energy resources available in the robot device. The paper describes the results of applying the original approach for image processing on reconfigurable computing environments by the example of morphological operations over grayscale images. This approach is prospective for realizing complex image processing algorithms and real-time image analysis in autonomous robotic devices.

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

[Image processing system of visual prostheses based on digital signal processor DM642].

PubMed

Xie, Chengcheng; Lu, Yanyu; Gu, Yun; Wang, Jing; Chai, Xinyu

2011-09-01

This paper employed a DSP platform to create the real-time and portable image processing system, and introduced a series of commonly used algorithms for visual prostheses. The results of performance evaluation revealed that this platform could afford image processing algorithms to be executed in real time.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

A dual-channel fusion system of visual and infrared images based on color transfer

NASA Astrophysics Data System (ADS)

Pei, Chuang; Jiang, Xiao-yu; Zhang, Peng-wei; Liang, Hao-cong

2013-09-01

A dual-channel fusion system of visual and infrared images based on color transfer The increasing availability and deployment of imaging sensors operating in multiple spectrums has led to a large research effort in image fusion, resulting in a plethora of pixel-level image fusion algorithms. However, most of these algorithms have gray or false color fusion results which are not adapt to human vision. Transfer color from a day-time reference image to get natural color fusion result is an effective way to solve this problem, but the computation cost of color transfer is expensive and can't meet the request of real-time image processing. We developed a dual-channel infrared and visual images fusion system based on TMS320DM642 digital signal processing chip. The system is divided into image acquisition and registration unit, image fusion processing unit, system control unit and image fusion result out-put unit. The image registration of dual-channel images is realized by combining hardware and software methods in the system. False color image fusion algorithm in RGB color space is used to get R-G fused image, then the system chooses a reference image to transfer color to the fusion result. A color lookup table based on statistical properties of images is proposed to solve the complexity computation problem in color transfer. The mapping calculation between the standard lookup table and the improved color lookup table is simple and only once for a fixed scene. The real-time fusion and natural colorization of infrared and visual images are realized by this system. The experimental result shows that the color-transferred images have a natural color perception to human eyes, and can highlight the targets effectively with clear background details. Human observers with this system will be able to interpret the image better and faster, thereby improving situational awareness and reducing target detection time.

EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

NASA Technical Reports Server (NTRS)

Jayroe, R. R.

1994-01-01

Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available evaluation criteria basically compare the observed results with the expected results. For the image reconstruction processes of registration and compression, the expected results are usually the original data or some selected characteristics of the original data. For classification processes the expected result is the ground truth of the scene. Thus, the comparison process consists of determining what changes occur in processing, where the changes occur, how much change occurs, and the amplitude of the change. The package includes evaluation routines for performing such comparisons as average uncertainty, average information transfer, chi-square statistics, multidimensional histograms, and computation of contingency matrices. This collection of routines is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 662K of 8 bit bytes. This collection of image processing and evaluation routines was developed in 1979.

Apple Image Processing Educator

NASA Technical Reports Server (NTRS)

Gunther, F. J.

1981-01-01

A software system design is proposed and demonstrated with pilot-project software. The system permits the Apple II microcomputer to be used for personalized computer-assisted instruction in the digital image processing of LANDSAT images. The programs provide data input, menu selection, graphic and hard-copy displays, and both general and detailed instructions. The pilot-project results are considered to be successful indicators of the capabilities and limits of microcomputers for digital image processing education.

The Application of Special Computing Techniques to Speed-Up Image Feature Extraction and Processing Techniques.

DTIC Science & Technology

1981-12-01

ocessors has led to the possibility of implementing a large number of image processing functions in near real time . ~CC~ jnro _ j:% UNLSSFE (b-.YC ASIIAINO...to the possibility of implementing a large number of image processing functions in near " real - time ," a result which is essential to establishing a...for example, and S) rapid image handling for near real - time in- teraction by a user at a display. For example, for a large resolution image, say

Looking back to inform the future: The role of cognition in forest disturbance characterization from remote sensing imagery

NASA Astrophysics Data System (ADS)

Bianchetti, Raechel Anne

Remotely sensed images have become a ubiquitous part of our daily lives. From novice users, aiding in search and rescue missions using tools such as TomNod, to trained analysts, synthesizing disparate data to address complex problems like climate change, imagery has become central to geospatial problem solving. Expert image analysts are continually faced with rapidly developing sensor technologies and software systems. In response to these cognitively demanding environments, expert analysts develop specialized knowledge and analytic skills to address increasingly complex problems. This study identifies the knowledge, skills, and analytic goals of expert image analysts tasked with identification of land cover and land use change. Analysts participating in this research are currently working as part of a national level analysis of land use change, and are well versed with the use of TimeSync, forest science, and image analysis. The results of this study benefit current analysts as it improves their awareness of their mental processes used during the image interpretation process. The study also can be generalized to understand the types of knowledge and visual cues that analysts use when reasoning with imagery for purposes beyond land use change studies. Here a Cognitive Task Analysis framework is used to organize evidence from qualitative knowledge elicitation methods for characterizing the cognitive aspects of the TimeSync image analysis process. Using a combination of content analysis, diagramming, semi-structured interviews, and observation, the study highlights the perceptual and cognitive elements of expert remote sensing interpretation. Results show that image analysts perform several standard cognitive processes, but flexibly employ these processes in response to various contextual cues. Expert image analysts' ability to think flexibly during their analysis process was directly related to their amount of image analysis experience. Additionally, results show that the basic Image Interpretation Elements continue to be important despite technological augmentation of the interpretation process. These results are used to derive a set of design guidelines for developing geovisual analytic tools and training to support image analysis.

Quantitative comparison of clustered microcalcifications in for-presentation and for-processing mammograms in full-field digital mammography.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-07-01

Mammograms acquired with full-field digital mammography (FFDM) systems are provided in both "for-processing'' and "for-presentation'' image formats. For-presentation images are traditionally intended for visual assessment by the radiologists. In this study, we investigate the feasibility of using for-presentation images in computerized analysis and diagnosis of microcalcification (MC) lesions. We make use of a set of 188 matched mammogram image pairs of MC lesions from 95 cases (biopsy proven), in which both for-presentation and for-processing images are provided for each lesion. We then analyze and characterize the MC lesions from for-presentation images and compare them with their counterparts in for-processing images. Specifically, we consider three important aspects in computer-aided diagnosis (CAD) of MC lesions. First, we quantify each MC lesion with a set of 10 image features of clustered MCs and 12 textural features of the lesion area. Second, we assess the detectability of individual MCs in each lesion from the for-presentation images by a commonly used difference-of-Gaussians (DoG) detector. Finally, we study the diagnostic accuracy in discriminating between benign and malignant MC lesions from the for-presentation images by a pretrained support vector machine (SVM) classifier. To accommodate the underlying background suppression and image enhancement in for-presentation images, a normalization procedure is applied. The quantitative image features of MC lesions from for-presentation images are highly consistent with that from for-processing images. The values of Pearson's correlation coefficient between features from the two formats range from 0.824 to 0.961 for the 10 MC image features, and from 0.871 to 0.963 for the 12 textural features. In detection of individual MCs, the FROC curve from for-presentation is similar to that from for-processing. In particular, at sensitivity level of 80%, the average number of false-positives (FPs) per image region is 9.55 for both for-presentation and for-processing images. Finally, for classifying MC lesions as malignant or benign, the area under the ROC curve is 0.769 in for-presentation, compared to 0.761 in for-processing (P = 0.436). The quantitative results demonstrate that MC lesions in for-presentation images are highly consistent with that in for-processing images in terms of image features, detectability of individual MCs, and classification accuracy between malignant and benign lesions. These results indicate that for-presentation images can be compatible with for-processing images for use in CAD algorithms for MC lesions. © 2017 American Association of Physicists in Medicine.

A comparison of ordinary fuzzy and intuitionistic fuzzy approaches in visualizing the image of flat electroencephalography

NASA Astrophysics Data System (ADS)

Zenian, Suzelawati; Ahmad, Tahir; Idris, Amidora

2017-09-01

Medical imaging is a subfield in image processing that deals with medical images. It is very crucial in visualizing the body parts in non-invasive way by using appropriate image processing techniques. Generally, image processing is used to enhance visual appearance of images for further interpretation. However, the pixel values of an image may not be precise as uncertainty arises within the gray values of an image due to several factors. In this paper, the input and output images of Flat Electroencephalography (fEEG) of an epileptic patient at varied time are presented. Furthermore, ordinary fuzzy and intuitionistic fuzzy approaches are implemented to the input images and the results are compared between these two approaches.

Beyond arousal and valence: the importance of the biological versus social relevance of emotional stimuli.

PubMed

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-03-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention, memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that (1) biologically emotional images hold attention more strongly than do socially emotional images, (2) memory for biologically emotional images was enhanced even with limited cognitive resources, but (3) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images' subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in the visual cortex and greater functional connectivity between the amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in the medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between the amygdala and MPFC than did biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity.

Geometric correction of synchronous scanned Operational Modular Imaging Spectrometer II hyperspectral remote sensing images using spatial positioning data of an inertial navigation system

NASA Astrophysics Data System (ADS)

Zhou, Xiaohu; Neubauer, Franz; Zhao, Dong; Xu, Shichao

2015-01-01

The high-precision geometric correction of airborne hyperspectral remote sensing image processing was a hard nut to crack, and conventional methods of remote sensing image processing by selecting ground control points to correct the images are not suitable in the correction process of airborne hyperspectral image. The optical scanning system of an inertial measurement unit combined with differential global positioning system (IMU/DGPS) is introduced to correct the synchronous scanned Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing images. Posture parameters, which were synchronized with the OMIS II, were first obtained from the IMU/DGPS. Second, coordinate conversion and flight attitude parameters' calculations were conducted. Third, according to the imaging principle of OMIS II, mathematical correction was applied and the corrected image pixels were resampled. Then, better image processing results were achieved.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

High resolution image processing on low-cost microcomputers

NASA Technical Reports Server (NTRS)

Miller, R. L.

1993-01-01

Recent advances in microcomputer technology have resulted in systems that rival the speed, storage, and display capabilities of traditionally larger machines. Low-cost microcomputers can provide a powerful environment for image processing. A new software program which offers sophisticated image display and analysis on IBM-based systems is presented. Designed specifically for a microcomputer, this program provides a wide-range of functions normally found only on dedicated graphics systems, and therefore can provide most students, universities and research groups with an affordable computer platform for processing digital images. The processing of AVHRR images within this environment is presented as an example.

Parallel processing considerations for image recognition tasks

NASA Astrophysics Data System (ADS)

Simske, Steven J.

2011-01-01

Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Automated segmentation of three-dimensional MR brain images

NASA Astrophysics Data System (ADS)

Park, Jonggeun; Baek, Byungjun; Ahn, Choong-Il; Ku, Kyo Bum; Jeong, Dong Kyun; Lee, Chulhee

2006-03-01

Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

Bio-inspired approach to multistage image processing

NASA Astrophysics Data System (ADS)

Timchenko, Leonid I.; Pavlov, Sergii V.; Kokryatskaya, Natalia I.; Poplavska, Anna A.; Kobylyanska, Iryna M.; Burdenyuk, Iryna I.; Wójcik, Waldemar; Uvaysova, Svetlana; Orazbekov, Zhassulan; Kashaganova, Gulzhan

2017-08-01

Multistage integration of visual information in the brain allows people to respond quickly to most significant stimuli while preserving the ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing, described in this paper, comprises main types of cortical multistage convergence. One of these types occurs within each visual pathway and the other between the pathways. This approach maps input images into a flexible hierarchy which reflects the complexity of the image data. The procedures of temporal image decomposition and hierarchy formation are described in mathematical terms. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image which encapsulates, in a computer manner, structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a very quick response from the system. The result is represented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Development of image analysis software for quantification of viable cells in microchips.

PubMed

Georg, Maximilian; Fernández-Cabada, Tamara; Bourguignon, Natalia; Karp, Paola; Peñaherrera, Ana B; Helguera, Gustavo; Lerner, Betiana; Pérez, Maximiliano S; Mertelsmann, Roland

2018-01-01

Over the past few years, image analysis has emerged as a powerful tool for analyzing various cell biology parameters in an unprecedented and highly specific manner. The amount of data that is generated requires automated methods for the processing and analysis of all the resulting information. The software available so far are suitable for the processing of fluorescence and phase contrast images, but often do not provide good results from transmission light microscopy images, due to the intrinsic variation of the acquisition of images technique itself (adjustment of brightness / contrast, for instance) and the variability between image acquisition introduced by operators / equipment. In this contribution, it has been presented an image processing software, Python based image analysis for cell growth (PIACG), that is able to calculate the total area of the well occupied by cells with fusiform and rounded morphology in response to different concentrations of fetal bovine serum in microfluidic chips, from microscopy images in transmission light, in a highly efficient way.

Predictive images of postoperative levator resection outcome using image processing software

PubMed Central

Mawatari, Yuki; Fukushima, Mikiko

2016-01-01

Purpose This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Methods Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller’s muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop®). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Results Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Conclusion Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery. PMID:27757008

Application of a digital high-speed camera and image processing system for investigations of short-term hypersonic fluids

NASA Astrophysics Data System (ADS)

Renken, Hartmut; Oelze, Holger W.; Rath, Hans J.

1998-04-01

The design and application of a digital high sped image data capturing system with a following image processing system applied to the Bremer Hochschul Hyperschallkanal BHHK is the content of this presentation. It is also the result of the cooperation between the departments aerodynamic and image processing at the ZARM-institute at the Drop Tower of Brennen. Similar systems are used by the combustion working group at ZARM and other external project partners. The BHHK, camera- and image storage system as well as the personal computer based image processing software are described next. Some examples of images taken at the BHHK are shown to illustrate the application. The new and very user-friendly Windows 32-bit system is capable to capture all camera data with a maximum pixel clock of 43 MHz and to process complete sequences of images in one step by using only one comfortable program.

Resiliency of the Multiscale Retinex Image Enhancement Algorithm

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Jobson, Daniel J.; Woodell, Glenn A.

1998-01-01

The multiscale retinex with color restoration (MSRCR) continues to prove itself in extensive testing to be very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition, However, issues remain with regard to the resiliency of the MSRCR to different image sources and arbitrary image manipulations which may have been applied prior to retinex processing. In this paper we define these areas of concern, provide experimental results, and, examine the effects of commonly occurring image manipulation on retinex performance. In virtually all cases the MSRCR is highly resilient to the effects of both the image source variations and commonly encountered prior image-processing. Significant artifacts are primarily observed for the case of selective color channel clipping in large dark zones in a image. These issues are of concerning the processing of digital image archives and other applications where there is neither control over the image acquisition process, nor knowledge about any processing done on th data beforehand.

Optimization of digital image processing to determine quantum dots' height and density from atomic force microscopy.

PubMed

Ruiz, J E; Paciornik, S; Pinto, L D; Ptak, F; Pires, M P; Souza, P L

2018-01-01

An optimized method of digital image processing to interpret quantum dots' height measurements obtained by atomic force microscopy is presented. The method was developed by combining well-known digital image processing techniques and particle recognition algorithms. The properties of quantum dot structures strongly depend on dots' height, among other features. Determination of their height is sensitive to small variations in their digital image processing parameters, which can generate misleading results. Comparing the results obtained with two image processing techniques - a conventional method and the new method proposed herein - with the data obtained by determining the height of quantum dots one by one within a fixed area, showed that the optimized method leads to more accurate results. Moreover, the log-normal distribution, which is often used to represent natural processes, shows a better fit to the quantum dots' height histogram obtained with the proposed method. Finally, the quantum dots' height obtained were used to calculate the predicted photoluminescence peak energies which were compared with the experimental data. Again, a better match was observed when using the proposed method to evaluate the quantum dots' height. Copyright © 2017 Elsevier B.V. All rights reserved.

A similarity-based data warehousing environment for medical images.

PubMed

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Development of a Text-Data Based Learning Tool That Integrates Image Processing and Displaying].

PubMed

Shinohara, Hiroyuki; Hashimoto, Takeyuki

2015-01-01

We developed a text-data based learning tool that integrates image processing and displaying by Excel. Knowledge required for programing this tool is limited to using absolute, relative, and composite cell references and learning approximately 20 mathematical functions available in Excel. The new tool is capable of resolution translation, geometric transformation, spatial-filter processing, Radon transform, Fourier transform, convolutions, correlations, deconvolutions, wavelet transform, mutual information, and simulation of proton density-, T1-, and T2-weighted MR images. The processed images of 128 x 128 pixels or 256 x 256 pixels are observed directly within Excel worksheets without using any particular image display software. The results of image processing using this tool were compared with those using C language and the new tool was judged to have sufficient accuracy to be practically useful. The images displayed on Excel worksheets were compared with images using binary-data display software. This comparison indicated that the image quality of the Excel worksheets was nearly equal to the latter in visual impressions. Since image processing is performed by using text-data, the process is visible and facilitates making contrasts by using mathematical equations within the program. We concluded that the newly developed tool is adequate as a computer-assisted learning tool for use in medical image processing.

Analysis of ROC on chest direct digital radiography (DR) after image processing in diagnosis of SARS

NASA Astrophysics Data System (ADS)

Lv, Guozheng; Lan, Rihui; Zeng, Qingsi; Zheng, Zhong

2004-05-01

The Severe Acute Respiratory Syndrome (SARS, also called Infectious Atypical Pneumonia), which initially broke out in late 2002, has threatened the public"s health seriously. How to confirm the patients contracting SARS becomes an urgent issue in diagnosis. This paper intends to evaluate the importance of Image Processing in the diagnosis on SARS at the early stage. Receiver Operating Characteristics (ROC) analysis has been employed in this study to compare the value of DR images in the diagnosis of SARS patients before and after image processing by Symphony Software supplied by E-Com Technology Ltd., and DR image study of 72 confirmed or suspected SARS patients were reviewed respectively. All the images taken from the studied patients were processed by Symphony. Both the original and processed images were taken into ROC analysis, based on which the ROC graph for each group of images has been produced as described below: For processed images: a = 1.9745, b = 1.4275, SA = 0.8714; For original images: a = 0.9066, b = 0.8310, SA = 0.7572; (a - intercept, b - slop, SA - Area below the curve). The result shows significant difference between the original images and processed images (P<0.01). In summary, the images processed by Symphony are superior to the original ones in detecting the opacity lesion, and increases the accuracy of SARS diagnosis.

Compressive sensing method for recognizing cat-eye effect targets.

PubMed

Li, Li; Li, Hui; Dang, Ersheng; Liu, Bo

2013-10-01

This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.

The effect of image sharpness on quantitative eye movement data and on image quality evaluation while viewing natural images

NASA Astrophysics Data System (ADS)

Vuori, Tero; Olkkonen, Maria

2006-01-01

The aim of the study is to test both customer image quality rating (subjective image quality) and physical measurement of user behavior (eye movements tracking) to find customer satisfaction differences in imaging technologies. Methodological aim is to find out whether eye movements could be quantitatively used in image quality preference studies. In general, we want to map objective or physically measurable image quality to subjective evaluations and eye movement data. We conducted a series of image quality tests, in which the test subjects evaluated image quality while we recorded their eye movements. Results show that eye movement parameters consistently change according to the instructions given to the user, and according to physical image quality, e.g. saccade duration increased with increasing blur. Results indicate that eye movement tracking could be used to differentiate image quality evaluation strategies that the users have. Results also show that eye movements would help mapping between technological and subjective image quality. Furthermore, these results give some empirical emphasis to top-down perception processes in image quality perception and evaluation by showing differences between perceptual processes in situations when cognitive task varies.

Graphics Processing Unit (GPU) implementation of image processing algorithms to improve system performance of the Control, Acquisition, Processing, and Image Display System (CAPIDS) of the Micro-Angiographic Fluoroscope (MAF).

PubMed

Vasan, S N Swetadri; Ionita, Ciprian N; Titus, A H; Cartwright, A N; Bednarek, D R; Rudin, S

2012-02-23

We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame.

ART AND SCIENCE OF IMAGE MAPS.

USGS Publications Warehouse

Kidwell, Richard D.; McSweeney, Joseph A.

1985-01-01

The visual image of reflected light is influenced by the complex interplay of human color discrimination, spatial relationships, surface texture, and the spectral purity of light, dyes, and pigments. Scientific theories of image processing may not always achieve acceptable results as the variety of factors, some psychological, are in part, unpredictable. Tonal relationships that affect digital image processing and the transfer functions used to transform from the continuous-tone source image to a lithographic image, may be interpreted for an insight of where art and science fuse in the production process. The application of art and science in image map production at the U. S. Geological Survey is illustrated and discussed.

Content-aware dark image enhancement through channel division.

PubMed

Rivera, Adin Ramirez; Ryu, Byungyong; Chae, Oksam

2012-09-01

The current contrast enhancement algorithms occasionally result in artifacts, overenhancement, and unnatural effects in the processed images. These drawbacks increase for images taken under poor illumination conditions. In this paper, we propose a content-aware algorithm that enhances dark images, sharpens edges, reveals details in textured regions, and preserves the smoothness of flat regions. The algorithm produces an ad hoc transformation for each image, adapting the mapping functions to each image's characteristics to produce the maximum enhancement. We analyze the contrast of the image in the boundary and textured regions, and group the information with common characteristics. These groups model the relations within the image, from which we extract the transformation functions. The results are then adaptively mixed, by considering the human vision system characteristics, to boost the details in the image. Results show that the algorithm can automatically process a wide range of images-e.g., mixed shadow and bright areas, outdoor and indoor lighting, and face images-without introducing artifacts, which is an improvement over many existing methods.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Gamma activity modulated by naming of ambiguous and unambiguous images: intracranial recording

PubMed Central

Cho-Hisamoto, Yoshimi; Kojima, Katsuaki; Brown, Erik C; Matsuzaki, Naoyuki; Asano, Eishi

2014-01-01

OBJECTIVE Humans sometimes need to recognize objects based on vague and ambiguous silhouettes. Recognition of such images may require an intuitive guess. We determined the spatial-temporal characteristics of intracranially-recorded gamma activity (at 50–120 Hz) augmented differentially by naming of ambiguous and unambiguous images. METHODS We studied ten patients who underwent epilepsy surgery. Ambiguous and unambiguous images were presented during extraoperative electrocorticography recording, and patients were instructed to overtly name the object as it is first perceived. RESULTS Both naming tasks were commonly associated with gamma-augmentation sequentially involving the occipital and occipital-temporal regions, bilaterally, within 200 ms after the onset of image presentation. Naming of ambiguous images elicited gamma-augmentation specifically involving portions of the inferior-frontal, orbitofrontal, and inferior-parietal regions at 400 ms and after. Unambiguous images were associated with more intense gamma-augmentation in portions of the occipital and occipital-temporal regions. CONCLUSIONS Frontal-parietal gamma-augmentation specific to ambiguous images may reflect the additional cortical processing involved in exerting intuitive guess. Occipital gamma-augmentation enhanced during naming of unambiguous images can be explained by visual processing of stimuli with richer detail. SIGNIFICANCE Our results support the theoretical model that guessing processes in visual domain occur following the accumulation of sensory evidence resulting from the bottom-up processing in the occipital-temporal visual pathways. PMID:24815577

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, J; Yang, D

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets,more » and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.« less

Beyond arousal and valence: The importance of the biological versus social relevance of emotional stimuli

PubMed Central

Sakaki, Michiko; Niki, Kazuhisa; Mather, Mara

2012-01-01

The present study addressed the hypothesis that emotional stimuli relevant to survival or reproduction (biologically emotional stimuli) automatically affect cognitive processing (e.g., attention; memory), while those relevant to social life (socially emotional stimuli) require elaborative processing to modulate attention and memory. Results of our behavioral studies showed that: a) biologically emotional images hold attention more strongly than socially emotional images, b) memory for biologically emotional images was enhanced even with limited cognitive resources, but c) memory for socially emotional images was enhanced only when people had sufficient cognitive resources at encoding. Neither images’ subjective arousal nor their valence modulated these patterns. A subsequent functional magnetic resonance imaging study revealed that biologically emotional images induced stronger activity in visual cortex and greater functional connectivity between amygdala and visual cortex than did socially emotional images. These results suggest that the interconnection between the amygdala and visual cortex supports enhanced attention allocation to biological stimuli. In contrast, socially emotional images evoked greater activity in medial prefrontal cortex (MPFC) and yielded stronger functional connectivity between amygdala and MPFC than biological images. Thus, it appears that emotional processing of social stimuli involves elaborative processing requiring frontal lobe activity. PMID:21964552

Improving the quality of reconstructed X-ray CT images of polymer gel dosimeters: zero-scan coupled with adaptive mean filtering.

PubMed

Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V

2017-03-01

This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.

Eye movement related brain responses to emotional scenes during free viewing

PubMed Central

Simola, Jaana; Torniainen, Jari; Moisala, Mona; Kivikangas, Markus; Krause, Christina M.

2013-01-01

Emotional stimuli are preferentially processed over neutral stimuli. Previous studies, however, disagree on whether emotional stimuli capture attention preattentively or whether the processing advantage is dependent on allocation of attention. The present study investigated attention and emotion processes by measuring brain responses related to eye movement events while 11 participants viewed images selected from the International Affective Picture System (IAPS). Brain responses to emotional stimuli were compared between serial and parallel presentation. An “emotional” set included one image with high positive or negative valence among neutral images. A “neutral” set comprised four neutral images. The participants were asked to indicate which picture—if any—was emotional and to rate that picture on valence and arousal. In the serial condition, the event-related potentials (ERPs) were time-locked to the stimulus onset. In the parallel condition, the ERPs were time-locked to the first eye entry on an image. The eye movement results showed facilitated processing of emotional, especially unpleasant information. The EEG results in both presentation conditions showed that the LPP (“late positive potential”) amplitudes at 400–500 ms were enlarged for the unpleasant and pleasant pictures as compared to neutral pictures. Moreover, the unpleasant scenes elicited stronger responses than pleasant scenes. The ERP results did not support parafoveal emotional processing, although the eye movement results suggested faster attention capture by emotional stimuli. Our findings, thus, suggested that emotional processing depends on overt attentional resources engaged in the processing of emotional content. The results also indicate that brain responses to emotional images can be analyzed time-locked to eye movement events, although the response amplitudes were larger during serial presentation. PMID:23970856

Geologic analyses of LANDSAT-1 multispectral imagery of a possible power plant site employing digital and analog image processing. [in Pennsylvania

NASA Technical Reports Server (NTRS)

Lovegreen, J. R.; Prosser, W. J.; Millet, R. A.

1975-01-01

A site in the Great Valley subsection of the Valley and Ridge physiographic province in eastern Pennsylvania was studied to evaluate the use of digital and analog image processing for geologic investigations. Ground truth at the site was obtained by a field mapping program, a subsurface exploration investigation and a review of available published and unpublished literature. Remote sensing data were analyzed using standard manual techniques. LANDSAT-1 imagery was analyzed using digital image processing employing the multispectral Image 100 system and using analog color processing employing the VP-8 image analyzer. This study deals primarily with linears identified employing image processing and correlation of these linears with known structural features and with linears identified manual interpretation; and the identification of rock outcrops in areas of extensive vegetative cover employing image processing. The results of this study indicate that image processing can be a cost-effective tool for evaluating geologic and linear features for regional studies encompassing large areas such as for power plant siting. Digital image processing can be an effective tool for identifying rock outcrops in areas of heavy vegetative cover.

Information theoretic analysis of linear shift-invariant edge-detection operators

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2012-06-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

Hiding Information Using different lighting Color images

NASA Astrophysics Data System (ADS)

Majead, Ahlam; Awad, Rash; Salman, Salema S.

2018-05-01

The host medium for the secret message is one of the important principles for the designers of steganography method. In this study, the best color image was studied to carrying any secret image.The steganography approach based Lifting Wavelet Transform (LWT) and Least Significant Bits (LSBs) substitution. The proposed method offers lossless and unnoticeable changes in the contrast carrier color image and imperceptible by human visual system (HVS), especially the host images which was captured in dark lighting conditions. The aim of the study was to study the process of masking the data in colored images with different light intensities. The effect of the masking process was examined on the images that are classified by a minimum distance and the amount of noise and distortion in the image. The histogram and statistical characteristics of the cover image the results showed the efficient use of images taken with different light intensities in hiding data using the least important bit substitution method. This method succeeded in concealing textual data without distorting the original image (low light) Lire developments due to the concealment process.The digital image segmentation technique was used to distinguish small areas with masking. The result is that smooth homogeneous areas are less affected as a result of hiding comparing with high light areas. It is possible to use dark color images to send any secret message between two persons for the purpose of secret communication with good security.

Volumetric image interpretation in radiology: scroll behavior and cognitive processes.

PubMed

den Boer, Larissa; van der Schaaf, Marieke F; Vincken, Koen L; Mol, Chris P; Stuijfzand, Bobby G; van der Gijp, Anouk

2018-05-16

The interpretation of medical images is a primary task for radiologists. Besides two-dimensional (2D) images, current imaging technologies allow for volumetric display of medical images. Whereas current radiology practice increasingly uses volumetric images, the majority of studies on medical image interpretation is conducted on 2D images. The current study aimed to gain deeper insight into the volumetric image interpretation process by examining this process in twenty radiology trainees who all completed four volumetric image cases. Two types of data were obtained concerning scroll behaviors and think-aloud data. Types of scroll behavior concerned oscillations, half runs, full runs, image manipulations, and interruptions. Think-aloud data were coded by a framework of knowledge and skills in radiology including three cognitive processes: perception, analysis, and synthesis. Relating scroll behavior to cognitive processes showed that oscillations and half runs coincided more often with analysis and synthesis than full runs, whereas full runs coincided more often with perception than oscillations and half runs. Interruptions were characterized by synthesis and image manipulations by perception. In addition, we investigated relations between cognitive processes and found an overall bottom-up way of reasoning with dynamic interactions between cognitive processes, especially between perception and analysis. In sum, our results highlight the dynamic interactions between these processes and the grounding of cognitive processes in scroll behavior. It suggests, that the types of scroll behavior are relevant to describe how radiologists interact with and manipulate volumetric images.

The representation of conceptual knowledge: visual, auditory, and olfactory imagery compared with semantic processing.

PubMed

Palmiero, Massimiliano; Di Matteo, Rosalia; Belardinelli, Marta Olivetti

2014-05-01

Two experiments comparing imaginative processing in different modalities and semantic processing were carried out to investigate the issue of whether conceptual knowledge can be represented in different format. Participants were asked to judge the similarity between visual images, auditory images, and olfactory images in the imaginative block, if two items belonged to the same category in the semantic block. Items were verbally cued in both experiments. The degree of similarity between the imaginative and semantic items was changed across experiments. Experiment 1 showed that the semantic processing was faster than the visual and the auditory imaginative processing, whereas no differentiation was possible between the semantic processing and the olfactory imaginative processing. Experiment 2 revealed that only the visual imaginative processing could be differentiated from the semantic processing in terms of accuracy. These results showed that the visual and auditory imaginative processing can be differentiated from the semantic processing, although both visual and auditory images strongly rely on semantic representations. On the contrary, no differentiation is possible within the olfactory domain. Results are discussed in the frame of the imagery debate.

A method of fast mosaic for massive UAV images

NASA Astrophysics Data System (ADS)

Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong

2014-11-01

With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

PyDBS: an automated image processing workflow for deep brain stimulation surgery.

PubMed

D'Albis, Tiziano; Haegelen, Claire; Essert, Caroline; Fernández-Vidal, Sara; Lalys, Florent; Jannin, Pierre

2015-02-01

Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery. PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system's robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases. The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient. The results obtained are compatible with the adoption of PyDBS in clinical practice.

Autocorrelation techniques for soft photogrammetry

NASA Astrophysics Data System (ADS)

Yao, Wu

In this thesis research is carried out on image processing, image matching searching strategies, feature type and image matching, and optimal window size in image matching. To make comparisons, the soft photogrammetry package SoftPlotter is used. Two aerial photographs from the Iowa State University campus high flight 94 are scanned into digital format. In order to create a stereo model from them, interior orientation, single photograph rectification and stereo rectification are done. Two new image matching methods, multi-method image matching (MMIM) and unsquare window image matching are developed and compared. MMIM is used to determine the optimal window size in image matching. Twenty four check points from four different types of ground features are used for checking the results from image matching. Comparison between these four types of ground feature shows that the methods developed here improve the speed and the precision of image matching. A process called direct transformation is described and compared with the multiple steps in image processing. The results from image processing are consistent with those from SoftPlotter. A modified LAN image header is developed and used to store the information about the stereo model and image matching. A comparison is also made between cross correlation image matching (CCIM), least difference image matching (LDIM) and least square image matching (LSIM). The quality of image matching in relation to ground features are compared using two methods developed in this study, the coefficient surface for CCIM and the difference surface for LDIM. To reduce the amount of computation in image matching, the best-track searching algorithm, developed in this research, is used instead of the whole range searching algorithm.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

MOPEX: a software package for astronomical image processing and visualization

NASA Astrophysics Data System (ADS)

Makovoz, David; Roby, Trey; Khan, Iffat; Booth, Hartley

2006-06-01

We present MOPEX - a software package for astronomical image processing and display. The package is a combination of command-line driven image processing software written in C/C++ with a Java-based GUI. The main image processing capabilities include creating mosaic images, image registration, background matching, point source extraction, as well as a number of minor image processing tasks. The combination of the image processing and display capabilities allows for much more intuitive and efficient way of performing image processing. The GUI allows for the control over the image processing and display to be closely intertwined. Parameter setting, validation, and specific processing options are entered by the user through a set of intuitive dialog boxes. Visualization feeds back into further processing by providing a prompt feedback of the processing results. The GUI also allows for further analysis by accessing and displaying data from existing image and catalog servers using a virtual observatory approach. Even though originally designed for the Spitzer Space Telescope mission, a lot of functionalities are of general usefulness and can be used for working with existing astronomical data and for new missions. The software used in the package has undergone intensive testing and benefited greatly from effective software reuse. The visualization part has been used for observation planning for both the Spitzer and Herschel Space Telescopes as part the tool Spot. The visualization capabilities of Spot have been enhanced and integrated with the image processing functionality of the command-line driven MOPEX. The image processing software is used in the Spitzer automated pipeline processing, which has been in operation for nearly 3 years. The image processing capabilities have also been tested in off-line processing by numerous astronomers at various institutions around the world. The package is multi-platform and includes automatic update capabilities. The software package has been developed by a small group of software developers and scientists at the Spitzer Science Center. It is available for distribution at the Spitzer Science Center web page.

Correlation processing for correction of phase distortions in subaperture imaging.

PubMed

Tavh, B; Karaman, M

1999-01-01

Ultrasonic subaperture imaging combines synthetic aperture and phased array approaches and permits low-cost systems with improved image quality. In subaperture processing, a large array is synthesized using echo signals collected from a number of receive subapertures by multiple firings of a phased transmit subaperture. Tissue inhomogeneities and displacements in subaperture imaging may cause significant phase distortions on received echo signals. Correlation processing on reference echo signals can be used for correction of the phase distortions, for which the accuracy and robustness are critically limited by the signal correlation. In this study, we explore correlation processing techniques for adaptive subaperture imaging with phase correction for motion and tissue inhomogeneities. The proposed techniques use new subaperture data acquisition schemes to produce reference signal sets with improved signal correlation. The experimental test results were obtained using raw radio frequency (RF) data acquired from two different phantoms with 3.5 MHz, 128-element transducer array. The results show that phase distortions can effectively be compensated by the proposed techniques in real-time adaptive subaperture imaging.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

Direct microscopic image and measurement of the atomization process of a port fuel injector

NASA Astrophysics Data System (ADS)

Esmail, Mohamed; Kawahara, Nobuyuki; Tomita, Eiji; Sumida, Mamoru

2010-07-01

The main objective of this study is to observe and investigate the phenomena of atomization, i.e. the fuel break-up process very close to the nozzle exit of a practical port fuel injector (PFI). In order to achieve this objective, direct microscopic images of the atomization process were obtained using an ultra-high-speed video camera that could record 102 frames at rates of up to 1 Mfps, coupled with a long-distance microscope and Barlow lens. The experiments were carried out using a PFI in a closed chamber at atmospheric pressure. Time-series images of the spray behaviour were obtained with a high temporal resolution using backlighting. The direct microscopic images of a liquid column break-up were compared with experimental results from laser-induced exciplex fluorescence (LIEF), and the wavelength obtained from the experimental results compared with that predicated from the Kelvin-Helmholtz break-up model. The droplet size diameters from a ligament break-up were compared with results predicated from Weber's analysis. Furthermore, experimental results of the mean droplet diameter from a direct microscopic image were compared with the results obtained from phase Doppler anemometry (PDA) experimental results. Three conclusions were obtained from this study. The atomization processes and detailed characterizations of the break-up of a liquid column were identified; the direct microscopic image results were in good agreement with the results obtained from LIEF, experimental results of the wavelength were in good agreement with those from the Kelvin-Helmholtz break-up model. The break-up process of liquid ligaments into droplets was investigated, and Weber's analysis of the predicated droplet diameter from ligament break-up was found to be applicable only at larger wavelengths. Finally, the direct microscopic image method and PDA method give qualitatively similar trends for droplet size distribution and quantitatively similar values of Sauter mean diameter.

Automatic Sea Bird Detection from High Resolution Aerial Imagery

NASA Astrophysics Data System (ADS)

Mader, S.; Grenzdörffer, G. J.

2016-06-01

Great efforts are presently taken in the scientific community to develop computerized and (fully) automated image processing methods allowing for an efficient and automatic monitoring of sea birds and marine mammals in ever-growing amounts of aerial imagery. Currently the major part of the processing, however, is still conducted by especially trained professionals, visually examining the images and detecting and classifying the requested subjects. This is a very tedious task, particularly when the rate of void images regularly exceeds the mark of 90%. In the content of this contribution we will present our work aiming to support the processing of aerial images by modern methods from the field of image processing. We will especially focus on the combination of local, region-based feature detection and piecewise global image segmentation for automatic detection of different sea bird species. Large image dimensions resulting from the use of medium and large-format digital cameras in aerial surveys inhibit the applicability of image processing methods based on global operations. In order to efficiently handle those image sizes and to nevertheless take advantage of globally operating segmentation algorithms, we will describe the combined usage of a simple performant feature detector based on local operations on the original image with a complex global segmentation algorithm operating on extracted sub-images. The resulting exact segmentation of possible candidates then serves as a basis for the determination of feature vectors for subsequent elimination of false candidates and for classification tasks.

CSAM Metrology Software Tool

NASA Technical Reports Server (NTRS)

Vu, Duc; Sandor, Michael; Agarwal, Shri

2005-01-01

CSAM Metrology Software Tool (CMeST) is a computer program for analysis of false-color CSAM images of plastic-encapsulated microcircuits. (CSAM signifies C-mode scanning acoustic microscopy.) The colors in the images indicate areas of delamination within the plastic packages. Heretofore, the images have been interpreted by human examiners. Hence, interpretations have not been entirely consistent and objective. CMeST processes the color information in image-data files to detect areas of delamination without incurring inconsistencies of subjective judgement. CMeST can be used to create a database of baseline images of packages acquired at given times for comparison with images of the same packages acquired at later times. Any area within an image can be selected for analysis, which can include examination of different delamination types by location. CMeST can also be used to perform statistical analyses of image data. Results of analyses are available in a spreadsheet format for further processing. The results can be exported to any data-base-processing software.

Measurement of smaller colon polyp in CT colonography images using morphological image processing.

PubMed

Manjunath, K N; Siddalingaswamy, P C; Prabhu, G K

2017-11-01

Automated measurement of the size and shape of colon polyps is one of the challenges in Computed tomography colonography (CTC). The objective of this retrospective study was to improve the sensitivity and specificity of smaller polyp measurement in CTC using image processing techniques. A domain knowledge-based method has been implemented with hybrid method of colon segmentation, morphological image processing operators for detecting the colonic structures, and the decision-making system for delineating the smaller polyp-based on a priori knowledge. The method was applied on 45 CTC dataset. The key finding was that the smaller polyps were accurately measured. In addition to 6-9 mm range, polyps of even <5 mm were also detected. The results were validated qualitatively and quantitatively using both 2D MPR and 3D view. Implementation was done on a high-performance computer with parallel processing. It takes [Formula: see text] min for measuring the smaller polyp in a dataset of 500 CTC images. With this method, [Formula: see text] and [Formula: see text] were achieved. The domain-based approach with morphological image processing has given good results. The smaller polyps were measured accurately which helps in making right clinical decisions. Qualitatively and quantitatively the results were acceptable when compared to the ground truth at [Formula: see text].

Noise removal using factor analysis of dynamic structures: application to cardiac gated studies.

PubMed

Bruyant, P P; Sau, J; Mallet, J J

1999-10-01

Factor analysis of dynamic structures (FADS) facilitates the extraction of relevant data, usually with physiologic meaning, from a dynamic set of images. The result of this process is a set of factor images and curves plus some residual activity. The set of factor images and curves can be used to retrieve the original data with reduced noise using an inverse factor analysis process (iFADS). This improvement in image quality is expected because the inverse process does not use the residual activity, assumed to be made of noise. The goal of this work is to quantitate and assess the efficiency of this method on gated cardiac images. A computer simulation of a planar cardiac gated study was performed. The simulated images were added with noise and processed by the FADS-iFADS program. The signal-to-noise ratios (SNRs) were compared between original and processed data. Planar gated cardiac studies from 10 patients were tested. The data processed by FADS-iFADS were subtracted to the original data. The result of the substraction was studied to evaluate its noisy nature. The SNR is about five times greater after the FADS-iFADS process. The difference between original and processed data is noise only, i.e., processed data equals original data minus some white noise. The FADS-iFADS process is successful in the removal of an important part of the noise and therefore is a tool to improve the image quality of cardiac images. This tool does not decrease the spatial resolution (compared with smoothing filters) and does not lose details (compared with frequential filters). Once the number of factors is chosen, this method is not operator dependent.

Automatic cloud coverage assessment of Formosat-2 image

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

a Metadata Based Approach for Analyzing Uav Datasets for Photogrammetric Applications

NASA Astrophysics Data System (ADS)

Dhanda, A.; Remondino, F.; Santana Quintero, M.

2018-05-01

This paper proposes a methodology for pre-processing and analysing Unmanned Aerial Vehicle (UAV) datasets before photogrammetric processing. In cases where images are gathered without a detailed flight plan and at regular acquisition intervals the datasets can be quite large and be time consuming to process. This paper proposes a method to calculate the image overlap and filter out images to reduce large block sizes and speed up photogrammetric processing. The python-based algorithm that implements this methodology leverages the metadata in each image to determine the end and side overlap of grid-based UAV flights. Utilizing user input, the algorithm filters out images that are unneeded for photogrammetric processing. The result is an algorithm that can speed up photogrammetric processing and provide valuable information to the user about the flight path.

A motion deblurring method with long/short exposure image pairs

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Hua, Weiping; Zhao, Jufeng; Gong, Xiaoli; Zhu, Liyao

2018-01-01

In this paper, a motion deblurring method with long/short exposure image pairs is presented. The long/short exposure image pairs are captured for the same scene under different exposure time. The image pairs are treated as the input of the deblurring method and more information could be used to obtain a deblurring result with high image quality. Firstly, the luminance equalization process is carried out to the short exposure image. And the blur kernel is estimated with the image pair under the maximum a posteriori (MAP) framework using conjugate gradient algorithm. Then a L0 image smoothing based denoising method is applied to the luminance equalized image. And the final deblurring result is obtained with the gain controlled residual image deconvolution process with the edge map as the gain map. Furthermore, a real experimental optical system is built to capture the image pair in order to demonstrate the effectiveness of the proposed deblurring framework. The long/short image pairs are obtained under different exposure time and camera gain control. Experimental results show that the proposed method could provide a superior deblurring result in both subjective and objective assessment compared with other deblurring approaches.

Applications of High-speed motion analysis system on Solid Rocket Motor (SRM)

NASA Astrophysics Data System (ADS)

Liu, Yang; He, Guo-qiang; Li, Jiang; Liu, Pei-jin; Chen, Jian

2007-01-01

High-speed motion analysis system could record images up to 12,000fps and analyzed with the image processing system. The system stored data and images directly in electronic memory convenient for managing and analyzing. The high-speed motion analysis system and the X-ray radiography system were established the high-speed real-time X-ray radiography system, which could diagnose and measure the dynamic and high-speed process in opaque. The image processing software was developed for improve quality of the original image for acquiring more precise information. The typical applications of high-speed motion analysis system on solid rocket motor (SRM) were introduced in the paper. The research of anomalous combustion of solid propellant grain with defects, real-time measurement experiment of insulator eroding, explosion incision process of motor, structure and wave character of plume during the process of ignition and flameout, measurement of end burning of solid propellant, measurement of flame front and compatibility between airplane and missile during the missile launching were carried out using high-speed motion analysis system. The significative results were achieved through the research. Aim at application of high-speed motion analysis system on solid rocket motor, the key problem, such as motor vibrancy, electrical source instability, geometry aberrance, and yawp disturbance, which damaged the image quality, was solved. The image processing software was developed which improved the capability of measuring the characteristic of image. The experimental results showed that the system was a powerful facility to study instantaneous and high-speed process in solid rocket motor. With the development of the image processing technique, the capability of high-speed motion analysis system was enhanced.

Estimation of Damaged Areas due to the 2010 Chile Earthquake and Tsunami Using SAR Imagery of Alos/palsar

NASA Astrophysics Data System (ADS)

Made, Pertiwi Jaya Ni; Miura, Fusanori; Besse Rimba, A.

2016-06-01

A large-scale earthquake and tsunami affect thousands of people and cause serious damages worldwide every year. Quick observation of the disaster damage is extremely important for planning effective rescue operations. In the past, acquiring damage information was limited to only field surveys or using aerial photographs. In the last decade, space-borne images were used in many disaster researches, such as tsunami damage detection. In this study, SAR data of ALOS/PALSAR satellite images were used to estimate tsunami damage in the form of inundation areas in Talcahuano, the area near the epicentre of the 2010 Chile earthquake. The image processing consisted of three stages, i.e. pre-processing, analysis processing, and post-processing. It was conducted using multi-temporal images before and after the disaster. In the analysis processing, inundation areas were extracted through the masking processing. It consisted of water masking using a high-resolution optical image of ALOS/AVNIR-2 and elevation masking which built upon the inundation height using DEM image of ASTER-GDEM. The area result was 8.77 Km2. It showed a good result and corresponded to the inundation map of Talcahuano. Future study in another area is needed in order to strengthen the estimation processing method.

Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

NASA Astrophysics Data System (ADS)

Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

Advances in medical image computing.

PubMed

Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

2009-01-01

Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Restoration of singularities in reconstructed phase of crystal image in electron holography.

PubMed

Li, Wei; Tanji, Takayoshi

2014-12-01

Off-axis electron holography can be used to measure the inner potential of a specimen from its reconstructed phase image and is thus a powerful technique for materials scientists. However, abrupt reversals of contrast from white to black may sometimes occur in a digitally reconstructed phase image, which results in inaccurate information. Such phase distortion is mainly due to the digital reconstruction process and weak electron wave amplitude in some areas of the specimen. Therefore, digital image processing can be applied to the reconstruction and restoration of phase images. In this paper, fringe reconnection processing is applied to phase image restoration of a crystal structure image. The disconnection and wrong connection of interference fringes in the hologram that directly cause a 2π phase jump imperfection are correctly reconnected. Experimental results show that the phase distortion is significantly reduced after the processing. The quality of the reconstructed phase image was improved by the removal of imperfections in the final phase. © The Author 2014. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

PubMed

Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

2017-11-27

We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

Data analysis for GOPEX image frames

NASA Technical Reports Server (NTRS)

Levine, B. M.; Shaik, K. S.; Yan, T.-Y.

1993-01-01

The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing

NASA Astrophysics Data System (ADS)

Tatebe, Hironobu; Kato, Kunihito; Yamamoto, Kazuhiko; Katsuta, Yukio; Nonaka, Masahiko

2005-12-01

Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

Image processing analysis on the air-water slug two-phase flow in a horizontal pipe

NASA Astrophysics Data System (ADS)

Dinaryanto, Okto; Widyatama, Arif; Majid, Akmal Irfan; Deendarlianto, Indarto

2016-06-01

Slug flow is a part of intermittent flow which is avoided in industrial application because of its irregularity and high pressure fluctuation. Those characteristics cause some problems such as internal corrosion and the damage of the pipeline construction. In order to understand the slug characteristics, some of the measurement techniques can be applied such as wire-mesh sensors, CECM, and high speed camera. The present study was aimed to determine slug characteristics by using image processing techniques. Experiment has been carried out in 26 mm i.d. acrylic horizontal pipe with 9 m long. Air-water flow was recorded 5 m from the air-water mixer using high speed video camera. Each of image sequence was processed using MATLAB. There are some steps including image complement, background subtraction, and image filtering that used in this algorithm to produce binary images. Special treatments also were applied to reduce the disturbance effect of dispersed bubble around the bubble. Furthermore, binary images were used to describe bubble contour and calculate slug parameter such as gas slug length, gas slug velocity, and slug frequency. As a result the effect of superficial gas velocity and superficial liquid velocity on the fundamental parameters can be understood. After comparing the results to the previous experimental results, the image processing techniques is a useful and potential technique to explain the slug characteristics.

Developing an ANSI standard for image quality tools for the testing of active millimeter wave imaging systems

NASA Astrophysics Data System (ADS)

Barber, Jeffrey; Greca, Joseph; Yam, Kevin; Weatherall, James C.; Smith, Peter R.; Smith, Barry T.

2017-05-01

In 2016, the millimeter wave (MMW) imaging community initiated the formation of a standard for millimeter wave image quality metrics. This new standard, American National Standards Institute (ANSI) N42.59, will apply to active MMW systems for security screening of humans. The Electromagnetic Signatures of Explosives Laboratory at the Transportation Security Laboratory is supporting the ANSI standards process via the creation of initial prototypes for round-robin testing with MMW imaging system manufacturers and experts. Results obtained for these prototypes will be used to inform the community and lead to consensus objective standards amongst stakeholders. Images collected with laboratory systems are presented along with results of preliminary image analysis. Future directions for object design, data collection and image processing are discussed.

Colour application on mammography image segmentation

NASA Astrophysics Data System (ADS)

Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

2017-09-01

The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).

Segmentation of the spinous process and its acoustic shadow in vertebral ultrasound images.

PubMed

Berton, Florian; Cheriet, Farida; Miron, Marie-Claude; Laporte, Catherine

2016-05-01

Spinal ultrasound imaging is emerging as a low-cost, radiation-free alternative to conventional X-ray imaging for the clinical follow-up of patients with scoliosis. Currently, deformity measurement relies almost entirely on manual identification of key vertebral landmarks. However, the interpretation of vertebral ultrasound images is challenging, primarily because acoustic waves are entirely reflected by bone. To alleviate this problem, we propose an algorithm to segment these images into three regions: the spinous process, its acoustic shadow and other tissues. This method consists, first, in the extraction of several image features and the selection of the most relevant ones for the discrimination of the three regions. Then, using this set of features and linear discriminant analysis, each pixel of the image is classified as belonging to one of the three regions. Finally, the image is segmented by regularizing the pixel-wise classification results to account for some geometrical properties of vertebrae. The feature set was first validated by analyzing the classification results across a learning database. The database contained 107 vertebral ultrasound images acquired with convex and linear probes. Classification rates of 84%, 92% and 91% were achieved for the spinous process, the acoustic shadow and other tissues, respectively. Dice similarity coefficients of 0.72 and 0.88 were obtained respectively for the spinous process and acoustic shadow, confirming that the proposed method accurately segments the spinous process and its acoustic shadow in vertebral ultrasound images. Furthermore, the centroid of the automatically segmented spinous process was located at an average distance of 0.38 mm from that of the manually labeled spinous process, which is on the order of image resolution. This suggests that the proposed method is a promising tool for the measurement of the Spinous Process Angle and, more generally, for assisting ultrasound-based assessment of scoliosis progression. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Graph Based Interface for Representing Volume Visualization Results

NASA Technical Reports Server (NTRS)

Patten, James M.; Ma, Kwan-Liu

1998-01-01

This paper discusses a graph based user interface for representing the results of the volume visualization process. As images are rendered, they are connected to other images in a graph based on their rendering parameters. The user can take advantage of the information in this graph to understand how certain rendering parameter changes affect a dataset, making the visualization process more efficient. Because the graph contains more information than is contained in an unstructured history of images, the image graph is also helpful for collaborative visualization and animation.

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

NASA Technical Reports Server (NTRS)

Wemet, Mark P.

2008-01-01

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

NASA Astrophysics Data System (ADS)

Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

2017-10-01

Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

Hyperspectral imaging in medicine: image pre-processing problems and solutions in Matlab.

PubMed

Koprowski, Robert

2015-11-01

The paper presents problems and solutions related to hyperspectral image pre-processing. New methods of preliminary image analysis are proposed. The paper shows problems occurring in Matlab when trying to analyse this type of images. Moreover, new methods are discussed which provide the source code in Matlab that can be used in practice without any licensing restrictions. The proposed application and sample result of hyperspectral image analysis. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High quality image-pair-based deblurring method using edge mask and improved residual deconvolution

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Zhao, Jufeng; Gao, Xiumin; Feng, Huajun; Chen, Yueting

2017-04-01

Image deconvolution problem is a challenging task in the field of image process. Using image pairs could be helpful to provide a better restored image compared with the deblurring method from a single blurred image. In this paper, a high quality image-pair-based deblurring method is presented using the improved RL algorithm and the gain-controlled residual deconvolution technique. The input image pair includes a non-blurred noisy image and a blurred image captured for the same scene. With the estimated blur kernel, an improved RL deblurring method based on edge mask is introduced to obtain the preliminary deblurring result with effective ringing suppression and detail preservation. Then the preliminary deblurring result is served as the basic latent image and the gain-controlled residual deconvolution is utilized to recover the residual image. A saliency weight map is computed as the gain map to further control the ringing effects around the edge areas in the residual deconvolution process. The final deblurring result is obtained by adding the preliminary deblurring result with the recovered residual image. An optical experimental vibration platform is set up to verify the applicability and performance of the proposed algorithm. Experimental results demonstrate that the proposed deblurring framework obtains a superior performance in both subjective and objective assessments and has a wide application in many image deblurring fields.

High-performance image processing on the desktop

NASA Astrophysics Data System (ADS)

Jordan, Stephen D.

1996-04-01

The suitability of computers to the task of medical image visualization for the purposes of primary diagnosis and treatment planning depends on three factors: speed, image quality, and price. To be widely accepted the technology must increase the efficiency of the diagnostic and planning processes. This requires processing and displaying medical images of various modalities in real-time, with accuracy and clarity, on an affordable system. Our approach to meeting this challenge began with market research to understand customer image processing needs. These needs were translated into system-level requirements, which in turn were used to determine which image processing functions should be implemented in hardware. The result is a computer architecture for 2D image processing that is both high-speed and cost-effective. The architectural solution is based on the high-performance PA-RISC workstation with an HCRX graphics accelerator. The image processing enhancements are incorporated into the image visualization accelerator (IVX) which attaches to the HCRX graphics subsystem. The IVX includes a custom VLSI chip which has a programmable convolver, a window/level mapper, and an interpolator supporting nearest-neighbor, bi-linear, and bi-cubic modes. This combination of features can be used to enable simultaneous convolution, pan, zoom, rotate, and window/level control into 1 k by 1 k by 16-bit medical images at 40 frames/second.

Quantitative analysis of geomorphic processes using satellite image data at different scales

NASA Technical Reports Server (NTRS)

Williams, R. S., Jr.

1985-01-01

When aerial and satellite photographs and images are used in the quantitative analysis of geomorphic processes, either through direct observation of active processes or by analysis of landforms resulting from inferred active or dormant processes, a number of limitations in the use of such data must be considered. Active geomorphic processes work at different scales and rates. Therefore, the capability of imaging an active or dormant process depends primarily on the scale of the process and the spatial-resolution characteristic of the imaging system. Scale is an important factor in recording continuous and discontinuous active geomorphic processes, because what is not recorded will not be considered or even suspected in the analysis of orbital images. If the geomorphic process of landform change caused by the process is less than 200 m in x to y dimension, then it will not be recorded. Although the scale factor is critical, in the recording of discontinuous active geomorphic processes, the repeat interval of orbital-image acquisition of a planetary surface also is a consideration in order to capture a recurring short-lived geomorphic process or to record changes caused by either a continuous or a discontinuous geomorphic process.

Grid Computing Application for Brain Magnetic Resonance Image Processing

NASA Astrophysics Data System (ADS)

Valdivia, F.; Crépeault, B.; Duchesne, S.

2012-02-01

This work emphasizes the use of grid computing and web technology for automatic post-processing of brain magnetic resonance images (MRI) in the context of neuropsychiatric (Alzheimer's disease) research. Post-acquisition image processing is achieved through the interconnection of several individual processes into pipelines. Each process has input and output data ports, options and execution parameters, and performs single tasks such as: a) extracting individual image attributes (e.g. dimensions, orientation, center of mass), b) performing image transformations (e.g. scaling, rotation, skewing, intensity standardization, linear and non-linear registration), c) performing image statistical analyses, and d) producing the necessary quality control images and/or files for user review. The pipelines are built to perform specific sequences of tasks on the alphanumeric data and MRIs contained in our database. The web application is coded in PHP and allows the creation of scripts to create, store and execute pipelines and their instances either on our local cluster or on high-performance computing platforms. To run an instance on an external cluster, the web application opens a communication tunnel through which it copies the necessary files, submits the execution commands and collects the results. We present result on system tests for the processing of a set of 821 brain MRIs from the Alzheimer's Disease Neuroimaging Initiative study via a nonlinear registration pipeline composed of 10 processes. Our results show successful execution on both local and external clusters, and a 4-fold increase in performance if using the external cluster. However, the latter's performance does not scale linearly as queue waiting times and execution overhead increase with the number of tasks to be executed.

A Framework of Hyperspectral Image Compression using Neural Networks

DOE PAGES

Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; ...

2015-01-01

Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows usmore » to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.« less

Research on pre-processing of QR Code

NASA Astrophysics Data System (ADS)

Sun, Haixing; Xia, Haojie; Dong, Ning

2013-10-01

QR code encodes many kinds of information because of its advantages: large storage capacity, high reliability, full arrange of utter-high-speed reading, small printing size and high-efficient representation of Chinese characters, etc. In order to obtain the clearer binarization image from complex background, and improve the recognition rate of QR code, this paper researches on pre-processing methods of QR code (Quick Response Code), and shows algorithms and results of image pre-processing for QR code recognition. Improve the conventional method by changing the Souvola's adaptive text recognition method. Additionally, introduce the QR code Extraction which adapts to different image size, flexible image correction approach, and improve the efficiency and accuracy of QR code image processing.

Application of off-line image processing for optimization in chest computed radiography using a low cost system.

PubMed

Muhogora, Wilbroad E; Msaki, Peter; Padovani, Renato

2015-03-08

 The objective of this study was to improve the visibility of anatomical details by applying off-line postimage processing in chest computed radiography (CR). Four spatial domain-based external image processing techniques were developed by using MATLAB software version 7.0.0.19920 (R14) and image processing tools. The developed techniques were implemented to sample images and their visual appearances confirmed by two consultant radiologists to be clinically adequate. The techniques were then applied to 200 chest clinical images and randomized with other 100 images previously processed online. These 300 images were presented to three experienced radiologists for image quality assessment using standard quality criteria. The mean and ranges of the average scores for three radiologists were characterized for each of the developed technique and imaging system. The Mann-Whitney U-test was used to test the difference of details visibility between the images processed using each of the developed techniques and the corresponding images processed using default algorithms. The results show that the visibility of anatomical features improved significantly (0.005 ≤ p ≤ 0.02) with combinations of intensity values adjustment and/or spatial linear filtering techniques for images acquired using 60 ≤ kVp ≤ 70. However, there was no improvement for images acquired using 102 ≤ kVp ≤ 107 (0.127 ≤ p ≤ 0.48). In conclusion, the use of external image processing for optimization can be effective in chest CR, but should be implemented in consultations with the radiologists.

Application of off‐line image processing for optimization in chest computed radiography using a low cost system

PubMed Central

Msaki, Peter; Padovani, Renato

2015-01-01

The objective of this study was to improve the visibility of anatomical details by applying off‐line postimage processing in chest computed radiography (CR). Four spatial domain‐based external image processing techniques were developed by using MATLAB software version 7.0.0.19920 (R14) and image processing tools. The developed techniques were implemented to sample images and their visual appearances confirmed by two consultant radiologists to be clinically adequate. The techniques were then applied to 200 chest clinical images and randomized with other 100 images previously processed online. These 300 images were presented to three experienced radiologists for image quality assessment using standard quality criteria. The mean and ranges of the average scores for three radiologists were characterized for each of the developed technique and imaging system. The Mann‐Whitney U‐test was used to test the difference of details visibility between the images processed using each of the developed techniques and the corresponding images processed using default algorithms. The results show that the visibility of anatomical features improved significantly (0.005≤p≤0.02) with combinations of intensity values adjustment and/or spatial linear filtering techniques for images acquired using 60≤kVp≤70. However, there was no improvement for images acquired using 102≤kVp≤107 (0.127≤p≤0.48). In conclusion, the use of external image processing for optimization can be effective in chest CR, but should be implemented in consultations with the radiologists. PACS number: 87.59.−e, 87.59.−B, 87.59.−bd PMID:26103165

Research on fast Fourier transforms algorithm of huge remote sensing image technology with GPU and partitioning technology.

PubMed

Yang, Xue; Li, Xue-You; Li, Jia-Guo; Ma, Jun; Zhang, Li; Yang, Jan; Du, Quan-Ye

2014-02-01

Fast Fourier transforms (FFT) is a basic approach to remote sensing image processing. With the improvement of capacity of remote sensing image capture with the features of hyperspectrum, high spatial resolution and high temporal resolution, how to use FFT technology to efficiently process huge remote sensing image becomes the critical step and research hot spot of current image processing technology. FFT algorithm, one of the basic algorithms of image processing, can be used for stripe noise removal, image compression, image registration, etc. in processing remote sensing image. CUFFT function library is the FFT algorithm library based on CPU and FFTW. FFTW is a FFT algorithm developed based on CPU in PC platform, and is currently the fastest CPU based FFT algorithm function library. However there is a common problem that once the available memory or memory is less than the capacity of image, there will be out of memory or memory overflow when using the above two methods to realize image FFT arithmetic. To address this problem, a CPU and partitioning technology based Huge Remote Fast Fourier Transform (HRFFT) algorithm is proposed in this paper. By improving the FFT algorithm in CUFFT function library, the problem of out of memory and memory overflow is solved. Moreover, this method is proved rational by experiment combined with the CCD image of HJ-1A satellite. When applied to practical image processing, it improves effect of the image processing, speeds up the processing, which saves the time of computation and achieves sound result.

A web service system supporting three-dimensional post-processing of medical images based on WADO protocol.

PubMed

He, Longjun; Xu, Lang; Ming, Xing; Liu, Qian

2015-02-01

Three-dimensional post-processing operations on the volume data generated by a series of CT or MR images had important significance on image reading and diagnosis. As a part of the DIOCM standard, WADO service defined how to access DICOM objects on the Web, but it didn't involve three-dimensional post-processing operations on the series images. This paper analyzed the technical features of three-dimensional post-processing operations on the volume data, and then designed and implemented a web service system for three-dimensional post-processing operations of medical images based on the WADO protocol. In order to improve the scalability of the proposed system, the business tasks and calculation operations were separated into two modules. As results, it was proved that the proposed system could support three-dimensional post-processing service of medical images for multiple clients at the same moment, which met the demand of accessing three-dimensional post-processing operations on the volume data on the web.

What difference reveals about similarity.

PubMed

Sagi, Eyal; Gentner, Dedre; Lovett, Andrew

2012-08-01

Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ--that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, "different" responses are faster for low-similarity than for high-similarity pairs. In contrast, identifying a specific difference generally requires a full structural alignment of the two images, and this alignment process is faster for high-similarity pairs. We described four experiments that demonstrate this dissociation and show that the results can be simulated using the Structure-Mapping Engine. These results pose a significant challenge for nonstructural accounts of similarity comparison and suggest that structural alignment processes play a significant role in visual comparison. Copyright © 2012 Cognitive Science Society, Inc.

Semi-automated Image Processing for Preclinical Bioluminescent Imaging.

PubMed

Slavine, Nikolai V; McColl, Roderick W

Bioluminescent imaging is a valuable noninvasive technique for investigating tumor dynamics and specific biological molecular events in living animals to better understand the effects of human disease in animal models. The purpose of this study was to develop and test a strategy behind automated methods for bioluminescence image processing from the data acquisition to obtaining 3D images. In order to optimize this procedure a semi-automated image processing approach with multi-modality image handling environment was developed. To identify a bioluminescent source location and strength we used the light flux detected on the surface of the imaged object by CCD cameras. For phantom calibration tests and object surface reconstruction we used MLEM algorithm. For internal bioluminescent sources we used the diffusion approximation with balancing the internal and external intensities on the boundary of the media and then determined an initial order approximation for the photon fluence we subsequently applied a novel iterative deconvolution method to obtain the final reconstruction result. We find that the reconstruction techniques successfully used the depth-dependent light transport approach and semi-automated image processing to provide a realistic 3D model of the lung tumor. Our image processing software can optimize and decrease the time of the volumetric imaging and quantitative assessment. The data obtained from light phantom and lung mouse tumor images demonstrate the utility of the image reconstruction algorithms and semi-automated approach for bioluminescent image processing procedure. We suggest that the developed image processing approach can be applied to preclinical imaging studies: characteristics of tumor growth, identify metastases, and potentially determine the effectiveness of cancer treatment.

Fast processing of microscopic images using object-based extended depth of field.

PubMed

Intarapanich, Apichart; Kaewkamnerd, Saowaluck; Pannarut, Montri; Shaw, Philip J; Tongsima, Sissades

2016-12-22

Microscopic analysis requires that foreground objects of interest, e.g. cells, are in focus. In a typical microscopic specimen, the foreground objects may lie on different depths of field necessitating capture of multiple images taken at different focal planes. The extended depth of field (EDoF) technique is a computational method for merging images from different depths of field into a composite image with all foreground objects in focus. Composite images generated by EDoF can be applied in automated image processing and pattern recognition systems. However, current algorithms for EDoF are computationally intensive and impractical, especially for applications such as medical diagnosis where rapid sample turnaround is important. Since foreground objects typically constitute a minor part of an image, the EDoF technique could be made to work much faster if only foreground regions are processed to make the composite image. We propose a novel algorithm called object-based extended depths of field (OEDoF) to address this issue. The OEDoF algorithm consists of four major modules: 1) color conversion, 2) object region identification, 3) good contrast pixel identification and 4) detail merging. First, the algorithm employs color conversion to enhance contrast followed by identification of foreground pixels. A composite image is constructed using only these foreground pixels, which dramatically reduces the computational time. We used 250 images obtained from 45 specimens of confirmed malaria infections to test our proposed algorithm. The resulting composite images with all in-focus objects were produced using the proposed OEDoF algorithm. We measured the performance of OEDoF in terms of image clarity (quality) and processing time. The features of interest selected by the OEDoF algorithm are comparable in quality with equivalent regions in images processed by the state-of-the-art complex wavelet EDoF algorithm; however, OEDoF required four times less processing time. This work presents a modification of the extended depth of field approach for efficiently enhancing microscopic images. This selective object processing scheme used in OEDoF can significantly reduce the overall processing time while maintaining the clarity of important image features. The empirical results from parasite-infected red cell images revealed that our proposed method efficiently and effectively produced in-focus composite images. With the speed improvement of OEDoF, this proposed algorithm is suitable for processing large numbers of microscope images, e.g., as required for medical diagnosis.

Nondestructive, fast, and cost-effective image processing method for roughness measurement of randomly rough metallic surfaces.

PubMed

Ghodrati, Sajjad; Kandi, Saeideh Gorji; Mohseni, Mohsen

2018-06-01

In recent years, various surface roughness measurement methods have been proposed as alternatives to the commonly used stylus profilometry, which is a low-speed, destructive, expensive but precise method. In this study, a novel method, called "image profilometry," has been introduced for nondestructive, fast, and low-cost surface roughness measurement of randomly rough metallic samples based on image processing and machine vision. The impacts of influential parameters such as image resolution and filtering approach for elimination of the long wavelength surface undulations on the accuracy of the image profilometry results have been comprehensively investigated. Ten surface roughness parameters were measured for the samples using both the stylus and image profilometry. Based on the results, the best image resolution was 800 dpi, and the most practical filtering method was Gaussian convolution+cutoff. In these conditions, the best and worst correlation coefficients (R 2 ) between the stylus and image profilometry results were 0.9892 and 0.9313, respectively. Our results indicated that the image profilometry predicted the stylus profilometry results with high accuracy. Consequently, it could be a viable alternative to the stylus profilometry, particularly in online applications.

Framework for hyperspectral image processing and quantification for cancer detection during animal tumor surgery.

PubMed

Lu, Guolan; Wang, Dongsheng; Qin, Xulei; Halig, Luma; Muller, Susan; Zhang, Hongzheng; Chen, Amy; Pogue, Brian W; Chen, Zhuo Georgia; Fei, Baowei

2015-01-01

Hyperspectral imaging (HSI) is an imaging modality that holds strong potential for rapid cancer detection during image-guided surgery. But the data from HSI often needs to be processed appropriately in order to extract the maximum useful information that differentiates cancer from normal tissue. We proposed a framework for hyperspectral image processing and quantification, which includes a set of steps including image preprocessing, glare removal, feature extraction, and ultimately image classification. The framework has been tested on images from mice with head and neck cancer, using spectra from 450- to 900-nm wavelength. The image analysis computed Fourier coefficients, normalized reflectance, mean, and spectral derivatives for improved accuracy. The experimental results demonstrated the feasibility of the hyperspectral image processing and quantification framework for cancer detection during animal tumor surgery, in a challenging setting where sensitivity can be low due to a modest number of features present, but potential for fast image classification can be high. This HSI approach may have potential application in tumor margin assessment during image-guided surgery, where speed of assessment may be the dominant factor.

Framework for hyperspectral image processing and quantification for cancer detection during animal tumor surgery

NASA Astrophysics Data System (ADS)

Lu, Guolan; Wang, Dongsheng; Qin, Xulei; Halig, Luma; Muller, Susan; Zhang, Hongzheng; Chen, Amy; Pogue, Brian W.; Chen, Zhuo Georgia; Fei, Baowei

2015-12-01

Hyperspectral imaging (HSI) is an imaging modality that holds strong potential for rapid cancer detection during image-guided surgery. But the data from HSI often needs to be processed appropriately in order to extract the maximum useful information that differentiates cancer from normal tissue. We proposed a framework for hyperspectral image processing and quantification, which includes a set of steps including image preprocessing, glare removal, feature extraction, and ultimately image classification. The framework has been tested on images from mice with head and neck cancer, using spectra from 450- to 900-nm wavelength. The image analysis computed Fourier coefficients, normalized reflectance, mean, and spectral derivatives for improved accuracy. The experimental results demonstrated the feasibility of the hyperspectral image processing and quantification framework for cancer detection during animal tumor surgery, in a challenging setting where sensitivity can be low due to a modest number of features present, but potential for fast image classification can be high. This HSI approach may have potential application in tumor margin assessment during image-guided surgery, where speed of assessment may be the dominant factor.

Real-time image-processing algorithm for markerless tumour tracking using X-ray fluoroscopic imaging.

PubMed

Mori, S

2014-05-01

To ensure accuracy in respiratory-gating treatment, X-ray fluoroscopic imaging is used to detect tumour position in real time. Detection accuracy is strongly dependent on image quality, particularly positional differences between the patient and treatment couch. We developed a new algorithm to improve the quality of images obtained in X-ray fluoroscopic imaging and report the preliminary results. Two oblique X-ray fluoroscopic images were acquired using a dynamic flat panel detector (DFPD) for two patients with lung cancer. The weighting factor was applied to the DFPD image in respective columns, because most anatomical structures, as well as the treatment couch and port cover edge, were aligned in the superior-inferior direction when the patient lay on the treatment couch. The weighting factors for the respective columns were varied until the standard deviation of the pixel values within the image region was minimized. Once the weighting factors were calculated, the quality of the DFPD image was improved by applying the factors to multiframe images. Applying the image-processing algorithm produced substantial improvement in the quality of images, and the image contrast was increased. The treatment couch and irradiation port edge, which were not related to a patient's position, were removed. The average image-processing time was 1.1 ms, showing that this fast image processing can be applied to real-time tumour-tracking systems. These findings indicate that this image-processing algorithm improves the image quality in patients with lung cancer and successfully removes objects not related to the patient. Our image-processing algorithm might be useful in improving gated-treatment accuracy.

The Design and Development of Test Platform for Wheat Precision Seeding Based on Image Processing Techniques

NASA Astrophysics Data System (ADS)

Li, Qing; Lin, Haibo; Xiu, Yu-Feng; Wang, Ruixue; Yi, Chuijie

The test platform of wheat precision seeding based on image processing techniques is designed to develop the wheat precision seed metering device with high efficiency and precision. Using image processing techniques, this platform gathers images of seeds (wheat) on the conveyer belt which are falling from seed metering device. Then these data are processed and analyzed to calculate the qualified rate, reseeding rate and leakage sowing rate, etc. This paper introduces the whole structure, design parameters of the platform and hardware & software of the image acquisition system were introduced, as well as the method of seed identification and seed-space measurement using image's threshold and counting the seed's center. By analyzing the experimental result, the measurement error is less than ± 1mm.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

PubMed Central

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

Three-dimensional image contrast using biospeckle

NASA Astrophysics Data System (ADS)

Godinho, Robson Pierangeli; Braga, Roberto A., Jr.

2010-09-01

The biospeckle laser (BSL) has been applied in many areas of knowledge and a variety of approaches has been presented to address the best results in biological and non-biological samples, in fast or slow activities, or else in defined flow of materials or in random activities. The methodologies accounted in the literature consider the apparatus used in the image assembling and the way the collected data is processed. The image processing steps presents in turn a variety of procedures with first or second order statistics analysis, and as well with different sizes of data collected. One way to access the biospeckle in defined flow, such as in capillary blood flow in alive animals, was the adoption of the image contrast technique which uses only one image from the illuminated sample. That approach presents some problems related to the resolution of the image, which is reduced during the image contrast processing. In order to help the visualization of the low resolution image formed by the contrast technique, this work presents the three-dimensional procedure as a reliable alternative to enhance the final image. The work based on a parallel processing, with the generation of a virtual map of amplitudes, and maintaining the quasi-online characteristic of the contrast technique. Therefore, it was possible to generate in the same display the observed material, the image contrast result and in addiction the three-dimensional image with adjustable options of rotation. The platform also offers to the user the possibility to access the 3D image offline.

An approach of point cloud denoising based on improved bilateral filtering

NASA Astrophysics Data System (ADS)

Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

2018-04-01

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

Image reconstruction: an overview for clinicians.

PubMed

Hansen, Michael S; Kellman, Peter

2015-03-01

Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI). The MRI raw data is not acquired in image space and the role of the image reconstruction process is to transform the acquired raw data into images that can be interpreted clinically. This process involves multiple signal processing steps that each have an impact on the image quality. This review explains the basic terminology used for describing and quantifying image quality in terms of signal-to-noise ratio and point spread function. In this context, several commonly used image reconstruction components are discussed. The image reconstruction components covered include noise prewhitening for phased array data acquisition, interpolation needed to reconstruct square pixels, raw data filtering for reducing Gibbs ringing artifacts, Fourier transforms connecting the raw data with image space, and phased array coil combination. The treatment of phased array coils includes a general explanation of parallel imaging as a coil combination technique. The review is aimed at readers with no signal processing experience and should enable them to understand what role basic image reconstruction steps play in the formation of clinical images and how the resulting image quality is described. © 2014 Wiley Periodicals, Inc.

Initial Results from Fitting Resolved Modes using HMI Intensity Observations

NASA Astrophysics Data System (ADS)

Korzennik, Sylvain G.

2017-08-01

The HMI project recently started processing the continuum intensity images following global helioseismology procedures similar to those used to process the velocity images. The spatial decomposition of these images has produced time series of spherical harmonic coefficients for degrees up to l=300, using a different apodization than the one used for velocity observations. The first 360 days of observations were processed and made available. I present initial results from fitting these time series using my state of the art fitting methodology and compare the derived mode characteristics to those estimated using co-eval velocity observations.

Research and implementation of the algorithm for unwrapped and distortion correction basing on CORDIC for panoramic image

NASA Astrophysics Data System (ADS)

Zhang, Zhenhai; Li, Kejie; Wu, Xiaobing; Zhang, Shujiang

2008-03-01

The unwrapped and correcting algorithm based on Coordinate Rotation Digital Computer (CORDIC) and bilinear interpolation algorithm was presented in this paper, with the purpose of processing dynamic panoramic annular image. An original annular panoramic image captured by panoramic annular lens (PAL) can be unwrapped and corrected to conventional rectangular image without distortion, which is much more coincident with people's vision. The algorithm for panoramic image processing is modeled by VHDL and implemented in FPGA. The experimental results show that the proposed panoramic image algorithm for unwrapped and distortion correction has the lower computation complexity and the architecture for dynamic panoramic image processing has lower hardware cost and power consumption. And the proposed algorithm is valid.

Colour Based Image Processing Method for Recognizing Ribbed Smoked Sheet Grade

NASA Astrophysics Data System (ADS)

Fibriani, Ike; Sumardi; Bayu Satriya, Alfredo; Budi Utomo, Satryo

2017-03-01

This research proposes a colour based image processing technique to recognize the Ribbed Smoked Sheet (RSS) grade so that the RSS sorting process can be faster and more accurate than the traditional one. The RSS sheet image captured by the camera is transformed into grayscale image to simplify the recognition of rust and mould on the RSS sheet. Then the grayscale image is transformed into binary image using threshold value which is obtained from the RSS 1 reference colour. The grade recognition is determined by counting the white pixel percentage. The result shows that the system has 88% of accuracy. Most faults exist on RSS 2 recognition. This is due to the illumination distribution which is not equal over the RSS image.

Architecture Of High Speed Image Processing System

NASA Astrophysics Data System (ADS)

Konishi, Toshio; Hayashi, Hiroshi; Ohki, Tohru

1988-01-01

One of architectures for a high speed image processing system which corresponds to a new algorithm for a shape understanding is proposed. And the hardware system which is based on the archtecture was developed. Consideration points of the architecture are mainly that using processors should match with the processing sequence of the target image and that the developed system should be used practically in an industry. As the result, it was possible to perform each processing at a speed of 80 nano-seconds a pixel.

Developing Matlab scripts for image analysis and quality assessment

NASA Astrophysics Data System (ADS)

Vaiopoulos, A. D.

2011-11-01

Image processing is a very helpful tool in many fields of modern sciences that involve digital imaging examination and interpretation. Processed images however, often need to be correlated with the original image, in order to ensure that the resulting image fulfills its purpose. Aside from the visual examination, which is mandatory, image quality indices (such as correlation coefficient, entropy and others) are very useful, when deciding which processed image is the most satisfactory. For this reason, a single program (script) was written in Matlab language, which automatically calculates eight indices by utilizing eight respective functions (independent function scripts). The program was tested in both fused hyperspectral (Hyperion-ALI) and multispectral (ALI, Landsat) imagery and proved to be efficient. Indices were found to be in agreement with visual examination and statistical observations.

Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

NASA Astrophysics Data System (ADS)

Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

2017-11-01

This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

Overview of CMOS process and design options for image sensor dedicated to space applications

NASA Astrophysics Data System (ADS)

Martin-Gonthier, P.; Magnan, P.; Corbiere, F.

2005-10-01

With the growth of huge volume markets (mobile phones, digital cameras...) CMOS technologies for image sensor improve significantly. New process flows appear in order to optimize some parameters such as quantum efficiency, dark current, and conversion gain. Space applications can of course benefit from these improvements. To illustrate this evolution, this paper reports results from three technologies that have been evaluated with test vehicles composed of several sub arrays designed with some space applications as target. These three technologies are CMOS standard, improved and sensor optimized process in 0.35μm generation. Measurements are focussed on quantum efficiency, dark current, conversion gain and noise. Other measurements such as Modulation Transfer Function (MTF) and crosstalk are depicted in [1]. A comparison between results has been done and three categories of CMOS process for image sensors have been listed. Radiation tolerance has been also studied for the CMOS improved process in the way of hardening the imager by design. Results at 4, 15, 25 and 50 krad prove a good ionizing dose radiation tolerance applying specific techniques.

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). A description of the sensor, ground data processing facility, laboratory calibration, and first results

NASA Technical Reports Server (NTRS)

Vane, Gregg (Editor)

1987-01-01

The papers in this document were presented at the Imaging Spectroscopy 2 Conference of the 31st International Symposium on Optical and Optoelectronic Applied Science and Engineering, in San Diego, California, on 20 and 21 August 1987. They describe the design and performance of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and its subsystems, the ground data processing facility, laboratory calibration, and first results.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1990-01-01

A process is disclosed for x ray registration and differencing which results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

Digital Data Registration and Differencing Compression System

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1996-01-01

A process for X-ray registration and differencing results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic X-ray digital images.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1992-01-01

A process for x ray registration and differencing results in more efficient compression is discussed. Differencing of registered modeled subject image with a modeled reference image forms a differential image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three dimensional model, which three dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

MilxXplore: a web-based system to explore large imaging datasets.

PubMed

Bourgeat, P; Dore, V; Villemagne, V L; Rowe, C C; Salvado, O; Fripp, J

2013-01-01

As large-scale medical imaging studies are becoming more common, there is an increasing reliance on automated software to extract quantitative information from these images. As the size of the cohorts keeps increasing with large studies, there is a also a need for tools that allow results from automated image processing and analysis to be presented in a way that enables fast and efficient quality checking, tagging and reporting on cases in which automatic processing failed or was problematic. MilxXplore is an open source visualization platform, which provides an interface to navigate and explore imaging data in a web browser, giving the end user the opportunity to perform quality control and reporting in a user friendly, collaborative and efficient way. Compared to existing software solutions that often provide an overview of the results at the subject's level, MilxXplore pools the results of individual subjects and time points together, allowing easy and efficient navigation and browsing through the different acquisitions of a subject over time, and comparing the results against the rest of the population. MilxXplore is fast, flexible and allows remote quality checks of processed imaging data, facilitating data sharing and collaboration across multiple locations, and can be easily integrated into a cloud computing pipeline. With the growing trend of open data and open science, such a tool will become increasingly important to share and publish results of imaging analysis.

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles

PubMed Central

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe

2017-01-01

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work. PMID:28718788

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

PubMed

Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe; Thom, Christian

2017-07-18

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N -th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

Image processing and reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chartrand, Rick

2012-06-15

This talk will examine some mathematical methods for image processing and the solution of underdetermined, linear inverse problems. The talk will have a tutorial flavor, mostly accessible to undergraduates, while still presenting research results. The primary approach is the use of optimization problems. We will find that relaxing the usual assumption of convexity will give us much better results.

Methods for destriping Landsat Thematic Mapper images - A feasibility study for an online destriping process in the Thematic Mapper Image Processing System (TIPS)

NASA Technical Reports Server (NTRS)

Poros, D. J.; Peterson, C. J.

1985-01-01

Methods for destriping TM images and results of the application of these methods to selected TM scenes with sensor and scan striping, which was not removed by the radiometric correction during the TM Archive Generation Phase in TIPS, are presented. These methods correct only for gain and offset differences between detectors over many image lines and do not consider within-line effects. The feasibility of implementing a destriping process online in TIPS is also described.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

PubMed

Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

2017-04-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy, and nearly a six-fold improvement over a commonly available network file system (NFS) approach even for relatively small file sets. Moreover, file access latency is lower than network attached storage.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Visualization Support for an Army Reconnaissance Mission

DTIC Science & Technology

1994-02-01

transform an aerial photographic image into an orthophoto image. In this process, the horizontal coordinates and elevation of a point on the ground are...to the corresponding horizontal position on the orthophoto . The result is a new digital image without relief displacement. This orthophoto image will...process, the orthophotos were generated. The generation of one orthophoto for every other photo was sufficient to ensure complete coverage of the test

Survey: interpolation methods for whole slide image processing.

PubMed

Roszkowiak, L; Korzynska, A; Zak, J; Pijanowska, D; Swiderska-Chadaj, Z; Markiewicz, T

2017-02-01

Evaluating whole slide images of histological and cytological samples is used in pathology for diagnostics, grading and prognosis . It is often necessary to rescale whole slide images of a very large size. Image resizing is one of the most common applications of interpolation. We collect the advantages and drawbacks of nine interpolation methods, and as a result of our analysis, we try to select one interpolation method as the preferred solution. To compare the performance of interpolation methods, test images were scaled and then rescaled to the original size using the same algorithm. The modified image was compared to the original image in various aspects. The time needed for calculations and results of quantification performance on modified images were also compared. For evaluation purposes, we used four general test images and 12 specialized biological immunohistochemically stained tissue sample images. The purpose of this survey is to determine which method of interpolation is the best to resize whole slide images, so they can be further processed using quantification methods. As a result, the interpolation method has to be selected depending on the task involving whole slide images. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

A New Color Image Encryption Scheme Using CML and a Fractional-Order Chaotic System

PubMed Central

Wu, Xiangjun; Li, Yang; Kurths, Jürgen

2015-01-01

The chaos-based image cryptosystems have been widely investigated in recent years to provide real-time encryption and transmission. In this paper, a novel color image encryption algorithm by using coupled-map lattices (CML) and a fractional-order chaotic system is proposed to enhance the security and robustness of the encryption algorithms with a permutation-diffusion structure. To make the encryption procedure more confusing and complex, an image division-shuffling process is put forward, where the plain-image is first divided into four sub-images, and then the position of the pixels in the whole image is shuffled. In order to generate initial conditions and parameters of two chaotic systems, a 280-bit long external secret key is employed. The key space analysis, various statistical analysis, information entropy analysis, differential analysis and key sensitivity analysis are introduced to test the security of the new image encryption algorithm. The cryptosystem speed is analyzed and tested as well. Experimental results confirm that, in comparison to other image encryption schemes, the new algorithm has higher security and is fast for practical image encryption. Moreover, an extensive tolerance analysis of some common image processing operations such as noise adding, cropping, JPEG compression, rotation, brightening and darkening, has been performed on the proposed image encryption technique. Corresponding results reveal that the proposed image encryption method has good robustness against some image processing operations and geometric attacks. PMID:25826602

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Donald F.; Schulz, Carl; Konijnenburg, Marco

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, butmore » requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.« less

Processing the image gradient field using a topographic primal sketch approach.

PubMed

Gambaruto, A M

2015-03-01

The spatial derivatives of the image intensity provide topographic information that may be used to identify and segment objects. The accurate computation of the derivatives is often hampered in medical images by the presence of noise and a limited resolution. This paper focuses on accurate computation of spatial derivatives and their subsequent use to process an image gradient field directly, from which an image with improved characteristics can be reconstructed. The improvements include noise reduction, contrast enhancement, thinning object contours and the preservation of edges. Processing the gradient field directly instead of the image is shown to have numerous benefits. The approach is developed such that the steps are modular, allowing the overall method to be improved and possibly tailored to different applications. As presented, the approach relies on a topographic representation and primal sketch of an image. Comparisons with existing image processing methods on a synthetic image and different medical images show improved results and accuracy in segmentation. Here, the focus is on objects with low spatial resolution, which is often the case in medical images. The methods developed show the importance of improved accuracy in derivative calculation and the potential in processing the image gradient field directly. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Computer vision applications for coronagraphic optical alignment and image processing.

PubMed

Savransky, Dmitry; Thomas, Sandrine J; Poyneer, Lisa A; Macintosh, Bruce A

2013-05-10

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

Error-proofing test system of industrial components based on image processing

NASA Astrophysics Data System (ADS)

Huang, Ying; Huang, Tao

2018-05-01

Due to the improvement of modern industrial level and accuracy, conventional manual test fails to satisfy the test standards of enterprises, so digital image processing technique should be utilized to gather and analyze the information on the surface of industrial components, so as to achieve the purpose of test. To test the installation parts of automotive engine, this paper employs camera to capture the images of the components. After these images are preprocessed including denoising, the image processing algorithm relying on flood fill algorithm is used to test the installation of the components. The results prove that this system has very high test accuracy.

An open data mining framework for the analysis of medical images: application on obstructive nephropathy microscopy images.

PubMed

Doukas, Charalampos; Goudas, Theodosis; Fischer, Simon; Mierswa, Ingo; Chatziioannou, Aristotle; Maglogiannis, Ilias

2010-01-01

This paper presents an open image-mining framework that provides access to tools and methods for the characterization of medical images. Several image processing and feature extraction operators have been implemented and exposed through Web Services. Rapid-Miner, an open source data mining system has been utilized for applying classification operators and creating the essential processing workflows. The proposed framework has been applied for the detection of salient objects in Obstructive Nephropathy microscopy images. Initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.

Standardizing Quality Assessment of Fused Remotely Sensed Images

NASA Astrophysics Data System (ADS)

Pohl, C.; Moellmann, J.; Fries, K.

2017-09-01

The multitude of available operational remote sensing satellites led to the development of many image fusion techniques to provide high spatial, spectral and temporal resolution images. The comparison of different techniques is necessary to obtain an optimized image for the different applications of remote sensing. There are two approaches in assessing image quality: 1. Quantitatively by visual interpretation and 2. Quantitatively using image quality indices. However an objective comparison is difficult due to the fact that a visual assessment is always subject and a quantitative assessment is done by different criteria. Depending on the criteria and indices the result varies. Therefore it is necessary to standardize both processes (qualitative and quantitative assessment) in order to allow an objective image fusion quality evaluation. Various studies have been conducted at the University of Osnabrueck (UOS) to establish a standardized process to objectively compare fused image quality. First established image fusion quality assessment protocols, i.e. Quality with No Reference (QNR) and Khan's protocol, were compared on varies fusion experiments. Second the process of visual quality assessment was structured and standardized with the aim to provide an evaluation protocol. This manuscript reports on the results of the comparison and provides recommendations for future research.

Computer-Aided Light Sheet Flow Visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

Computer-aided light sheet flow visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

Graph theory for feature extraction and classification: a migraine pathology case study.

PubMed

Jorge-Hernandez, Fernando; Garcia Chimeno, Yolanda; Garcia-Zapirain, Begonya; Cabrera Zubizarreta, Alberto; Gomez Beldarrain, Maria Angeles; Fernandez-Ruanova, Begonya

2014-01-01

Graph theory is also widely used as a representational form and characterization of brain connectivity network, as is machine learning for classifying groups depending on the features extracted from images. Many of these studies use different techniques, such as preprocessing, correlations, features or algorithms. This paper proposes an automatic tool to perform a standard process using images of the Magnetic Resonance Imaging (MRI) machine. The process includes pre-processing, building the graph per subject with different correlations, atlas, relevant feature extraction according to the literature, and finally providing a set of machine learning algorithms which can produce analyzable results for physicians or specialists. In order to verify the process, a set of images from prescription drug abusers and patients with migraine have been used. In this way, the proper functioning of the tool has been proved, providing results of 87% and 92% of success depending on the classifier used.

Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images

NASA Astrophysics Data System (ADS)

Gelroth, A.; Rodríguez, D.; Salvatelli, A.; Drozdowicz, B.; Bizai, G.

2011-12-01

We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.

Asymmetry and irregularity border as discrimination factor between melanocytic lesions

NASA Astrophysics Data System (ADS)

Sbrissa, David; Pratavieira, Sebastião.; Salvio, Ana Gabriela; Kurachi, Cristina; Bagnato, Vanderlei Salvadori; Costa, Luciano Da Fontoura; Travieso, Gonzalo

2015-06-01

Image processing tools have been widely used in systems supporting medical diagnosis. The use of mobile devices for the diagnosis of melanoma can assist doctors and improve their diagnosis of a melanocytic lesion. This study proposes a method of image analysis for melanoma discrimination from other types of melanocytic lesions, such as regular and atypical nevi. The process is based on extracting features related with asymmetry and border irregularity. It were collected 104 images, from medical database of two years. The images were obtained with standard digital cameras without lighting and scale control. Metrics relating to the characteristics of shape, asymmetry and curvature of the contour were extracted from segmented images. Linear Discriminant Analysis was performed for dimensionality reduction and data visualization. Segmentation results showed good efficiency in the process, with approximately 88:5% accuracy. Validation results presents sensibility and specificity 85% and 70% for melanoma detection, respectively.

Halftoning processing on a JPEG-compressed image

NASA Astrophysics Data System (ADS)

Sibade, Cedric; Barizien, Stephane; Akil, Mohamed; Perroton, Laurent

2003-12-01

Digital image processing algorithms are usually designed for the raw format, that is on an uncompressed representation of the image. Therefore prior to transforming or processing a compressed format, decompression is applied; then, the result of the processing application is finally re-compressed for further transfer or storage. The change of data representation is resource-consuming in terms of computation, time and memory usage. In the wide format printing industry, this problem becomes an important issue: e.g. a 1 m2 input color image, scanned at 600 dpi exceeds 1.6 GB in its raw representation. However, some image processing algorithms can be performed in the compressed-domain, by applying an equivalent operation on the compressed format. This paper is presenting an innovative application of the halftoning processing operation by screening, to be applied on JPEG-compressed image. This compressed-domain transform is performed by computing the threshold operation of the screening algorithm in the DCT domain. This algorithm is illustrated by examples for different halftone masks. A pre-sharpening operation, applied on a JPEG-compressed low quality image is also described; it allows to de-noise and to enhance the contours of this image.

Three-dimensional image signals: processing methods

NASA Astrophysics Data System (ADS)

Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

2010-11-01

Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

MIA - A free and open source software for gray scale medical image analysis

PubMed Central

2013-01-01

Background Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large. Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers. One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development. Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don’t provide an clear approach when one wants to shape a new command line tool from a prototype shell script. Results The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. Conclusion In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed. PMID:24119305

Using digital photo technology to improve visualization of gastric lumen CT images

NASA Astrophysics Data System (ADS)

Pyrgioti, M.; Kyriakidis, A.; Chrysostomou, S.; Panaritis, V.

2006-12-01

In order to evaluate the gastric lumen CT images better, a new method is being applied to images using an Image Processing software. During a 12-month period, 69 patients with various gastric symptoms and 20 normal (as far as it concerns the upper gastrointestinal system) volunteers underwent computed tomography of the upper gastrointestinal system. Just before the examination the patients and the normal volunteers underwent preparation with 40 ml soda water and 10 ml gastrografin. All the CT images were digitized with an Olympus 3.2 Mpixel digital camera and further processed with an Image Processing software. The administration per os of gastrografin and soda water resulted in the distension of the stomach and consequently better visualization of all the anatomic parts. By using an Image Processing software in a PC, all the pathological and normal images of the stomach were better diagnostically estimated. We believe that the photo digital technology improves the diagnostic capacity not only of the CT image but also in MRI and probably many other imaging methods.

Associations between the oxytocin receptor gene (OXTR) rs53576 polymorphism and emotional processing of social and nonsocial cues: an event-related potential (ERP) study.

PubMed

Choi, Damee; Minote, Natsumi; Watanuki, Shigeki

2017-01-26

Oxytocin receptor (OXTR) gene polymorphisms are related to individual differences in emotional processing of social cues. However, whether OXTR polymorphisms affect emotional processing of nonsocial cues remains unclear. The present study investigated the relationship between the OXTR rs53576 polymorphism and emotional processing of social cues and nonsocial cues. Event-related potentials were recorded from 88 male participants while images of humans and images of objects were presented as social cues and nonsocial cues, respectively. First, the results showed that GG carriers of OXTR rs53576 showed more negative N1 (50-200 ms) than AA carriers in response to images of both humans and objects. Second, GG carriers showed more negative N2 (200-320 ms) than AA carriers in response to images of humans but not in response to images of objects. Third, GG carriers showed more negative N2 in response to images of humans than images of objects, whereas AA carriers showed the opposite pattern. Fourth, we observed no difference in late positive potential (600-1000 ms) to images of humans or objects that depended on the OXTR rs53576 polymorphism. These results suggest that the OXTR rs53576 polymorphism affects emotional processing of not only social cues but also nonsocial cues in the very early stage (reflected in N1); however, the data also suggest that the OXTR rs53576 polymorphism is related specifically to increased emotional processing of social cues in the middle stage (reflected in N2).

Causes of cine image quality deterioration in cardiac catheterization laboratories.

PubMed

Levin, D C; Dunham, L R; Stueve, R

1983-10-01

Deterioration of cineangiographic image quality can result from malfunctions or technical errors at a number of points along the cine imaging chain: generator and automatic brightness control, x-ray tube, x-ray beam geometry, image intensifier, optics, cine camera, cine film, film processing, and cine projector. Such malfunctions or errors can result in loss of image contrast, loss of spatial resolution, improper control of film optical density (brightness), or some combination thereof. While the electronic and photographic technology involved is complex, physicians who perform cardiac catheterization should be conversant with the problems and what can be done to solve them. Catheterization laboratory personnel have control over a number of factors that directly affect image quality, including radiation dose rate per cine frame, kilovoltage or pulse width (depending on type of automatic brightness control), cine run time, selection of small or large focal spot, proper object-intensifier distance and beam collimation, aperture of the cine camera lens, selection of cine film, processing temperature, processing immersion time, and selection of developer.

Reconstructing Face Image from the Thermal Infrared Spectrum to the Visible Spectrum †

PubMed Central

Kresnaraman, Brahmastro; Deguchi, Daisuke; Takahashi, Tomokazu; Mekada, Yoshito; Ide, Ichiro; Murase, Hiroshi

2016-01-01

During the night or in poorly lit areas, thermal cameras are a better choice instead of normal cameras for security surveillance because they do not rely on illumination. A thermal camera is able to detect a person within its view, but identification from only thermal information is not an easy task. The purpose of this paper is to reconstruct the face image of a person from the thermal spectrum to the visible spectrum. After the reconstruction, further image processing can be employed, including identification/recognition. Concretely, we propose a two-step thermal-to-visible-spectrum reconstruction method based on Canonical Correlation Analysis (CCA). The reconstruction is done by utilizing the relationship between images in both thermal infrared and visible spectra obtained by CCA. The whole image is processed in the first step while the second step processes patches in an image. Results show that the proposed method gives satisfying results with the two-step approach and outperforms comparative methods in both quality and recognition evaluations. PMID:27110781

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

NASA Astrophysics Data System (ADS)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

[Research applications in digital radiology. Big data and co].

PubMed

Müller, H; Hanbury, A

2016-02-01

Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

PubMed

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

TU-B-19A-01: Image Registration II: TG132-Quality Assurance for Image Registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brock, K; Mutic, S

2014-06-15

AAPM Task Group 132 was charged with a review of the current approaches and solutions for image registration in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes. As the results of image registration are always used as the input of another process for planning or delivery, it is important for the user to understand and document the uncertainty associate with the algorithm in general and the Result of a specific registration. The recommendations of this task group, which at the time of abstract submission are currently being reviewed by the AAPM, include themore » following components. The user should understand the basic image registration techniques and methods of visualizing image fusion. The disclosure of basic components of the image registration by commercial vendors is critical in this respect. The physicists should perform end-to-end tests of imaging, registration, and planning/treatment systems if image registration is performed on a stand-alone system. A comprehensive commissioning process should be performed and documented by the physicist prior to clinical use of the system. As documentation is important to the safe implementation of this process, a request and report system should be integrated into the clinical workflow. Finally, a patient specific QA practice should be established for efficient evaluation of image registration results. The implementation of these recommendations will be described and illustrated during this educational session. Learning Objectives: Highlight the importance of understanding the image registration techniques used in their clinic. Describe the end-to-end tests needed for stand-alone registration systems. Illustrate a comprehensive commissioning program using both phantom data and clinical images. Describe a request and report system to ensure communication and documentation. Demonstrate an clinically-efficient patient QA practice for efficient evaluation of image registration.« less

Twofold processing for denoising ultrasound medical images.

PubMed

Kishore, P V V; Kumar, K V V; Kumar, D Anil; Prasad, M V D; Goutham, E N D; Rahul, R; Krishna, C B S Vamsi; Sandeep, Y

2015-01-01

Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing speckle and also inducing object of interest blurring. The second fold process initiates to restore object boundaries and texture with adaptive wavelet fusion. The degraded object restoration in block thresholded US image is carried through wavelet coefficient fusion of object in original US mage and block thresholded US image. Fusion rules and wavelet decomposition levels are made adaptive for each block using gradient histograms with normalized differential mean (NDF) to introduce highest level of contrast between the denoised pixels and the object pixels in the resultant image. Thus the proposed twofold methods are named as adaptive NDF block fusion with hard and soft thresholding (ANBF-HT and ANBF-ST). The results indicate visual quality improvement to an interesting level with the proposed twofold processing, where the first fold removes noise and second fold restores object properties. Peak signal to noise ratio (PSNR), normalized cross correlation coefficient (NCC), edge strength (ES), image quality Index (IQI) and structural similarity index (SSIM), measure the quantitative quality of the twofold processing technique. Validation of the proposed method is done by comparing with anisotropic diffusion (AD), total variational filtering (TVF) and empirical mode decomposition (EMD) for enhancement of US images. The US images are provided by AMMA hospital radiology labs at Vijayawada, India.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

NASA Astrophysics Data System (ADS)

Jermyn, Michael; Ghadyani, Hamid; Mastanduno, Michael A.; Turner, Wes; Davis, Scott C.; Dehghani, Hamid; Pogue, Brian W.

2013-08-01

Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

Computational analysis of Pelton bucket tip erosion using digital image processing

NASA Astrophysics Data System (ADS)

Shrestha, Bim Prasad; Gautam, Bijaya; Bajracharya, Tri Ratna

2008-03-01

Erosion of hydro turbine components through sand laden river is one of the biggest problems in Himalayas. Even with sediment trapping systems, complete removal of fine sediment from water is impossible and uneconomical; hence most of the turbine components in Himalayan Rivers are exposed to sand laden water and subject to erode. Pelton bucket which are being wildly used in different hydropower generation plant undergoes erosion on the continuous presence of sand particles in water. The subsequent erosion causes increase in splitter thickness, which is supposed to be theoretically zero. This increase in splitter thickness gives rise to back hitting of water followed by decrease in turbine efficiency. This paper describes the process of measurement of sharp edges like bucket tip using digital image processing. Image of each bucket is captured and allowed to run for 72 hours; sand concentration in water hitting the bucket is closely controlled and monitored. Later, the image of the test bucket is taken in the same condition. The process is repeated for 10 times. In this paper digital image processing which encompasses processes that performs image enhancement in both spatial and frequency domain. In addition, the processes that extract attributes from images, up to and including the measurement of splitter's tip. Processing of image has been done in MATLAB 6.5 platform. The result shows that quantitative measurement of edge erosion of sharp edges could accurately be detected and the erosion profile could be generated using image processing technique.

Medical Image Processing Server applied to Quality Control of Nuclear Medicine.

NASA Astrophysics Data System (ADS)

Vergara, C.; Graffigna, J. P.; Marino, E.; Omati, S.; Holleywell, P.

2016-04-01

This paper is framed within the area of medical image processing and aims to present the process of installation, configuration and implementation of a processing server of medical images (MIPS) in the Fundación Escuela de Medicina Nuclear located in Mendoza, Argentina (FUESMEN). It has been developed in the Gabinete de Tecnologia Médica (GA.TE.ME), Facultad de Ingeniería-Universidad Nacional de San Juan. MIPS is a software that using the DICOM standard, can receive medical imaging studies of different modalities or viewing stations, then it executes algorithms and finally returns the results to other devices. To achieve the objectives previously mentioned, preliminary tests were conducted in the laboratory. More over, tools were remotely installed in clinical enviroment. The appropiate protocols for setting up and using them in different services were established once defined those suitable algorithms. Finally, it’s important to focus on the implementation and training that is provided in FUESMEN, using nuclear medicine quality control processes. Results on implementation are exposed in this work.

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

Ultramap: the all in One Photogrammetric Solution

NASA Astrophysics Data System (ADS)

Wiechert, A.; Gruber, M.; Karner, K.

2012-07-01

This paper describes in detail the dense matcher developed since years by Vexcel Imaging in Graz for Microsoft's Bing Maps project. This dense matcher was exclusively developed for and used by Microsoft for the production of the 3D city models of Virtual Earth. It will now be made available to the public with the UltraMap software release mid-2012. That represents a revolutionary step in digital photogrammetry. The dense matcher generates digital surface models (DSM) and digital terrain models (DTM) automatically out of a set of overlapping UltraCam images. The models have an outstanding point density of several hundred points per square meter and sub-pixel accuracy and are generated automatically. The dense matcher consists of two steps. The first step rectifies overlapping image areas to speed up the dense image matching process. This rectification step ensures a very efficient processing and detects occluded areas by applying a back-matching step. In this dense image matching process a cost function consisting of a matching score as well as a smoothness term is minimized. In the second step the resulting range image patches are fused into a DSM by optimizing a global cost function. The whole process is optimized for multi-core CPUs and optionally uses GPUs if available. UltraMap 3.0 features also an additional step which is presented in this paper, a complete automated true-ortho and ortho workflow. For this, the UltraCam images are combined with the DSM or DTM in an automated rectification step and that results in high quality true-ortho or ortho images as a result of a highly automated workflow. The paper presents the new workflow and first results.

SU-F-P-06: Moving From Computed Radiography to Digital Radiography: A Collaborative Approach to Improve Image Quality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sandoval, D; Mlady, G; Selwyn, R

Purpose: To bring together radiologists, technologists, and physicists to utilize post-processing techniques in digital radiography (DR) in order to optimize image acquisition and improve image quality. Methods: Sub-optimal images acquired on a new General Electric (GE) DR system were flagged for follow-up by radiologists and reviewed by technologists and medical physicists. Various exam types from adult musculoskeletal (n=35), adult chest (n=4), and pediatric (n=7) were chosen for review. 673 total images were reviewed. These images were processed using five customized algorithms provided by GE. An image score sheet was created allowing the radiologist to assign a numeric score to eachmore » of the processed images, this allowed for objective comparison to the original images. Each image was scored based on seven properties: 1) overall image look, 2) soft tissue contrast, 3) high contrast, 4) latitude, 5) tissue equalization, 6) edge enhancement, 7) visualization of structures. Additional space allowed for additional comments not captured in scoring categories. Radiologists scored the images from 1 – 10 with 1 being non-diagnostic quality and 10 being superior diagnostic quality. Scores for each custom algorithm for each image set were summed. The algorithm with the highest score for each image set was then set as the default processing. Results: Images placed into the PACS “QC folder” for image processing reasons decreased. Feedback from radiologists was, overall, that image quality for these studies had improved. All default processing for these image types was changed to the new algorithm. Conclusion: This work is an example of the collaboration between radiologists, technologists, and physicists at the University of New Mexico to add value to the radiology department. The significant amount of work required to prepare the processing algorithms, reprocessing and scoring of the images was eagerly taken on by all team members in order to produce better quality images and improve patient care.« less

Restoration of motion blurred images

NASA Astrophysics Data System (ADS)

Gaxiola, Leopoldo N.; Juarez-Salazar, Rigoberto; Diaz-Ramirez, Victor H.

2017-08-01

Image restoration is a classic problem in image processing. Image degradations can occur due to several reasons, for instance, imperfections of imaging systems, quantization errors, atmospheric turbulence, relative motion between camera or objects, among others. Motion blur is a typical degradation in dynamic imaging systems. In this work, we present a method to estimate the parameters of linear motion blur degradation from a captured blurred image. The proposed method is based on analyzing the frequency spectrum of a captured image in order to firstly estimate the degradation parameters, and then, to restore the image with a linear filter. The performance of the proposed method is evaluated by processing synthetic and real-life images. The obtained results are characterized in terms of accuracy of image restoration given by an objective criterion.

Comparison of approaches for mobile document image analysis using server supported smartphones

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

With the recent advances in mobile technologies, new capabilities are emerging, such as mobile document image analysis. However, mobile phones are still less powerful than servers, and they have some resource limitations. One approach to overcome these limitations is performing resource-intensive processes of the application on remote servers. In mobile document image analysis, the most resource consuming process is the Optical Character Recognition (OCR) process, which is used to extract text in mobile phone captured images. In this study, our goal is to compare the in-phone and the remote server processing approaches for mobile document image analysis in order to explore their trade-offs. For the inphone approach, all processes required for mobile document image analysis run on the mobile phone. On the other hand, in the remote-server approach, core OCR process runs on the remote server and other processes run on the mobile phone. Results of the experiments show that the remote server approach is considerably faster than the in-phone approach in terms of OCR time, but adds extra delays such as network delay. Since compression and downscaling of images significantly reduce file sizes and extra delays, the remote server approach overall outperforms the in-phone approach in terms of selected speed and correct recognition metrics, if the gain in OCR time compensates for the extra delays. According to the results of the experiments, using the most preferable settings, the remote server approach performs better than the in-phone approach in terms of speed and acceptable correct recognition metrics.

Evaluation of solar angle variation over digital processing of LANDSAT imagery. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

1984-01-01

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Original images are transformed by means of digital filtering to enhance their spatial features. The resulting images are used to obtain an unsupervised classification of relief units. After defining relief classes, which are supposed to be spectrally different, topographic variables (declivity, altitude, relief range and slope length) are used to identify the true relief units existing on the ground. The samples are also clustered by means of an unsupervised classification option. The results obtained for each LANDSAT overpass are compared. Digital processing is highly affected by illumination geometry. There is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

Higher resolution satellite remote sensing and the impact on image mapping

USGS Publications Warehouse

Watkins, Allen H.; Thormodsgard, June M.

1987-01-01

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges.The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Hyperspectral imaging for food processing automation

NASA Astrophysics Data System (ADS)

Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Smith, Doug P.; Feldner, Peggy W.

2002-11-01

This paper presents the research results that demonstrates hyperspectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses, and potential application for real-time, on-line processing of poultry for automatic safety inspection. The hyperspectral imaging system included a line scan camera with prism-grating-prism spectrograph, fiber optic line lighting, motorized lens control, and hyperspectral image processing software. Hyperspectral image processing algorithms, specifically band ratio of dual-wavelength (565/517) images and thresholding were effective on the identification of fecal and ingesta contamination of poultry carcasses. A multispectral imaging system including a common aperture camera with three optical trim filters (515.4 nm with 8.6- nm FWHM), 566.4 nm with 8.8-nm FWHM, and 631 nm with 10.2-nm FWHM), which were selected and validated by a hyperspectral imaging system, was developed for a real-time, on-line application. A total image processing time required to perform the current multispectral images captured by a common aperture camera was approximately 251 msec or 3.99 frames/sec. A preliminary test shows that the accuracy of real-time multispectral imaging system to detect feces and ingesta on corn/soybean fed poultry carcasses was 96%. However, many false positive spots that cause system errors were also detected.

Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance

PubMed Central

2017-01-01

This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529

New generation of meteorology cameras

NASA Astrophysics Data System (ADS)

Janout, Petr; Blažek, Martin; Páta, Petr

2017-12-01

A new generation of the WILLIAM (WIde-field aLL-sky Image Analyzing Monitoring system) camera includes new features such as monitoring of rain and storm clouds during the day observation. Development of the new generation of weather monitoring cameras responds to the demand for monitoring of sudden weather changes. However, new WILLIAM cameras are ready to process acquired image data immediately, release warning against sudden torrential rains, and send it to user's cell phone and email. Actual weather conditions are determined from image data, and results of image processing are complemented by data from sensors of temperature, humidity, and atmospheric pressure. In this paper, we present the architecture, image data processing algorithms of mentioned monitoring camera and spatially-variant model of imaging system aberrations based on Zernike polynomials.

Similarity analysis between quantum images

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou

2018-06-01

Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.

Image fusion based on millimeter-wave for concealed weapon detection

NASA Astrophysics Data System (ADS)

Zhu, Weiwen; Zhao, Yuejin; Deng, Chao; Zhang, Cunlin; Zhang, Yalin; Zhang, Jingshui

2010-11-01

This paper describes a novel multi sensors image fusion technology which is presented for concealed weapon detection (CWD). It is known to all, because of the good transparency of the clothes at millimeter wave band, a millimeter wave radiometer can be used to image and distinguish concealed contraband beneath clothes, for example guns, knives, detonator and so on. As a result, we adopt the passive millimeter wave (PMMW) imaging technology for airport security. However, in consideration of the wavelength of millimeter wave and the single channel mechanical scanning, the millimeter wave image has law optical resolution, which can't meet the need of practical application. Therefore, visible image (VI), which has higher resolution, is proposed for the image fusion with the millimeter wave image to enhance the readability. Before the image fusion, a novel image pre-processing which specifics to the fusion of millimeter wave imaging and visible image is adopted. And in the process of image fusion, multi resolution analysis (MRA) based on Wavelet Transform (WT) is adopted. In this way, the experiment result shows that this method has advantages in concealed weapon detection and has practical significance.

Information theoretical assessment of visual communication with subband coding

NASA Astrophysics Data System (ADS)

Rahman, Zia-ur; Fales, Carl L.; Huck, Friedrich O.

1994-09-01

A well-designed visual communication channel is one which transmits the most information about a radiance field with the fewest artifacts. The role of image processing, encoding and restoration is to improve the quality of visual communication channels by minimizing the error in the transmitted data. Conventionally this role has been analyzed strictly in the digital domain neglecting the effects of image-gathering and image-display devices on the quality of the image. This results in the design of a visual communication channel which is `suboptimal.' We propose an end-to-end assessment of the imaging process which incorporates the influences of these devices in the design of the encoder and the restoration process. This assessment combines Shannon's communication theory with Wiener's restoration filter and with the critical design factors of the image gathering and display devices, thus providing the metrics needed to quantify and optimize the end-to-end performance of the visual communication channel. Results show that the design of the image-gathering device plays a significant role in determining the quality of the visual communication channel and in designing the analysis filters for subband encoding.

Original non-stationary eddy current imaging process for the evaluation of defects in metallic structures

NASA Astrophysics Data System (ADS)

Placko, Dominique; Bore, Thierry; Rivollet, Alain; Joubert, Pierre-Yves

2015-10-01

This paper deals with the problem of imaging defects in metallic structures through eddy current (EC) inspections, and proposes an original process for a possible tomographical crack evaluation. This process is based on a semi analytical modeling, called "distributed point source method" (DPSM) which is used to describe and equate the interactions between the implemented EC probes and the structure under test. Several steps will be successively described, illustrating the feasibility of this new imaging process dedicated to the quantitative evaluation of defects. The basic principles of this imaging process firstly consist in creating a 3D grid by meshing the volume potentially inspected by the sensor. As a result, a given number of elemental volumes (called voxels) are obtained. Secondly, the DPSM modeling is used to compute an image for all occurrences in which only one of the voxels has a different conductivity among all the other ones. The assumption consists to consider that a real defect may be truly represented by a superimposition of elemental voxels: the resulting accuracy will naturally depend on the density of space sampling. On other hand, the excitation device of the EC imager has the capability to be oriented in several directions, and driven by an excitation current at variable frequency. So, the simulation will be performed for several frequencies and directions of the eddy currents induced in the structure, which increases the signal entropy. All these results are merged in a so-called "observation matrix" containing all the probe/structure interaction configurations. This matrix is then used in an inversion scheme in order to perform the evaluation of the defect location and geometry. The modeled EC data provided by the DPSM are compared to the experimental images provided by an eddy current imager (ECI), implemented on aluminum plates containing some buried defects. In order to validate the proposed inversion process, we feed it with computed images of various acquisition configurations. Additive noise was added to the images so that they are more representative of actual EC data. In the case of simple notch type defects, for which the relative conductivity may only take two extreme values (1 or 0), a threshold was introduced on the inverted images, in a post processing step, taking advantage of a priori knowledge of the statistical properties of the restored images. This threshold allowed to enhance the image contrast and has contributed to eliminate both the residual noise and the pixels showing non-realistic values.

3D optical imagery for motion compensation in a limb ultrasound system

NASA Astrophysics Data System (ADS)

Ranger, Bryan J.; Feigin, Micha; Zhang, Xiang; Mireault, Al; Raskar, Ramesh; Herr, Hugh M.; Anthony, Brian W.

2016-04-01

Conventional processes for prosthetic socket fabrication are heavily subjective, often resulting in an interface to the human body that is neither comfortable nor completely functional. With nearly 100% of amputees reporting that they experience discomfort with the wearing of their prosthetic limb, designing an effective interface to the body can significantly affect quality of life and future health outcomes. Active research in medical imaging and biomechanical tissue modeling of residual limbs has led to significant advances in computer aided prosthetic socket design, demonstrating an interest in moving toward more quantifiable processes that are still patient-specific. In our work, medical ultrasonography is being pursued to acquire data that may quantify and improve the design process and fabrication of prosthetic sockets while greatly reducing cost compared to an MRI-based framework. This paper presents a prototype limb imaging system that uses a medical ultrasound probe, mounted to a mechanical positioning system and submerged in a water bath. The limb imaging is combined with three-dimensional optical imaging for motion compensation. Images are collected circumferentially around the limb and combined into cross-sectional axial image slices, resulting in a compound image that shows tissue distributions and anatomical boundaries similar to magnetic resonance imaging. In this paper we provide a progress update on our system development, along with preliminary results as we move toward full volumetric imaging of residual limbs for prosthetic socket design. This demonstrates a novel multi-modal approach to residual limb imaging.

a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.

2015-07-01

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.

Animal Detection in Natural Images: Effects of Color and Image Database

PubMed Central

Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.

2013-01-01

The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used. PMID:24130744

Assessing the impact of graphical quality on automatic text recognition in digital maps

NASA Astrophysics Data System (ADS)

Chiang, Yao-Yi; Leyk, Stefan; Honarvar Nazari, Narges; Moghaddam, Sima; Tan, Tian Xiang

2016-08-01

Converting geographic features (e.g., place names) in map images into a vector format is the first step for incorporating cartographic information into a geographic information system (GIS). With the advancement in computational power and algorithm design, map processing systems have been considerably improved over the last decade. However, the fundamental map processing techniques such as color image segmentation, (map) layer separation, and object recognition are sensitive to minor variations in graphical properties of the input image (e.g., scanning resolution). As a result, most map processing results would not meet user expectations if the user does not "properly" scan the map of interest, pre-process the map image (e.g., using compression or not), and train the processing system, accordingly. These issues could slow down the further advancement of map processing techniques as such unsuccessful attempts create a discouraged user community, and less sophisticated tools would be perceived as more viable solutions. Thus, it is important to understand what kinds of maps are suitable for automatic map processing and what types of results and process-related errors can be expected. In this paper, we shed light on these questions by using a typical map processing task, text recognition, to discuss a number of map instances that vary in suitability for automatic processing. We also present an extensive experiment on a diverse set of scanned historical maps to provide measures of baseline performance of a standard text recognition tool under varying map conditions (graphical quality) and text representations (that can vary even within the same map sheet). Our experimental results help the user understand what to expect when a fully or semi-automatic map processing system is used to process a scanned map with certain (varying) graphical properties and complexities in map content.

Image data-processing system for solar astronomy

NASA Technical Reports Server (NTRS)

Wilson, R. M.; Teuber, D. L.; Watkins, J. R.; Thomas, D. T.; Cooper, C. M.

1977-01-01

The paper describes an image data processing system (IDAPS), its hardware/software configuration, and interactive and batch modes of operation for the analysis of the Skylab/Apollo Telescope Mount S056 X-Ray Telescope experiment data. Interactive IDAPS is primarily designed to provide on-line interactive user control of image processing operations for image familiarization, sequence and parameter optimization, and selective feature extraction and analysis. Batch IDAPS follows the normal conventions of card control and data input and output, and is best suited where the desired parameters and sequence of operations are known and when long image-processing times are required. Particular attention is given to the way in which this system has been used in solar astronomy and other investigations. Some recent results obtained by means of IDAPS are presented.

Structural and functional correlates for language efficiency in auditory word processing.

PubMed

Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.

Structural and functional correlates for language efficiency in auditory word processing

PubMed Central

Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503

Measuring the complexity of design in real-time imaging software

NASA Astrophysics Data System (ADS)

Sangwan, Raghvinder S.; Vercellone-Smith, Pamela; Laplante, Phillip A.

2007-02-01

Due to the intricacies in the algorithms involved, the design of imaging software is considered to be more complex than non-image processing software (Sangwan et al, 2005). A recent investigation (Larsson and Laplante, 2006) examined the complexity of several image processing and non-image processing software packages along a wide variety of metrics, including those postulated by McCabe (1976), Chidamber and Kemerer (1994), and Martin (2003). This work found that it was not always possible to quantitatively compare the complexity between imaging applications and nonimage processing systems. Newer research and an accompanying tool (Structure 101, 2006), however, provides a greatly simplified approach to measuring software complexity. Therefore it may be possible to definitively quantify the complexity differences between imaging and non-imaging software, between imaging and real-time imaging software, and between software programs of the same application type. In this paper, we review prior results and describe the methodology for measuring complexity in imaging systems. We then apply a new complexity measurement methodology to several sets of imaging and non-imaging code in order to compare the complexity differences between the two types of applications. The benefit of such quantification is far reaching, for example, leading to more easily measured performance improvement and quality in real-time imaging code.

MilxXplore: a web-based system to explore large imaging datasets

PubMed Central

Bourgeat, P; Dore, V; Villemagne, V L; Rowe, C C; Salvado, O; Fripp, J

2013-01-01

Objective As large-scale medical imaging studies are becoming more common, there is an increasing reliance on automated software to extract quantitative information from these images. As the size of the cohorts keeps increasing with large studies, there is a also a need for tools that allow results from automated image processing and analysis to be presented in a way that enables fast and efficient quality checking, tagging and reporting on cases in which automatic processing failed or was problematic. Materials and methods MilxXplore is an open source visualization platform, which provides an interface to navigate and explore imaging data in a web browser, giving the end user the opportunity to perform quality control and reporting in a user friendly, collaborative and efficient way. Discussion Compared to existing software solutions that often provide an overview of the results at the subject's level, MilxXplore pools the results of individual subjects and time points together, allowing easy and efficient navigation and browsing through the different acquisitions of a subject over time, and comparing the results against the rest of the population. Conclusions MilxXplore is fast, flexible and allows remote quality checks of processed imaging data, facilitating data sharing and collaboration across multiple locations, and can be easily integrated into a cloud computing pipeline. With the growing trend of open data and open science, such a tool will become increasingly important to share and publish results of imaging analysis. PMID:23775173

The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

NASA Astrophysics Data System (ADS)

Tan, Linglong; Li, Changkai; Wang, Yueqin

2018-04-01

SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

X-ray agricultural product inspection: segmentation and classification

NASA Astrophysics Data System (ADS)

Casasent, David P.; Talukder, Ashit; Lee, Ha-Woon

1997-09-01

Processing of real-time x-ray images of randomly oriented and touching pistachio nuts for product inspection is considered. We describe the image processing used to isolate individual nuts (segmentation). This involves a new watershed transform algorithm. Segmentation results on approximately 3000 x-ray (film) and real time x-ray (linescan) nut images were excellent (greater than 99.9% correct). Initial classification results on film images are presented that indicate that the percentage of infested nuts can be reduced to 1.6% of the crop with only 2% of the good nuts rejected; this performance is much better than present manual methods and other automated classifiers have achieved.

Semi-automated camera trap image processing for the detection of ungulate fence crossing events.

PubMed

Janzen, Michael; Visser, Kaitlyn; Visscher, Darcy; MacLeod, Ian; Vujnovic, Dragomir; Vujnovic, Ksenija

2017-09-27

Remote cameras are an increasingly important tool for ecological research. While remote camera traps collect field data with minimal human attention, the images they collect require post-processing and characterization before it can be ecologically and statistically analyzed, requiring the input of substantial time and money from researchers. The need for post-processing is due, in part, to a high incidence of non-target images. We developed a stand-alone semi-automated computer program to aid in image processing, categorization, and data reduction by employing background subtraction and histogram rules. Unlike previous work that uses video as input, our program uses still camera trap images. The program was developed for an ungulate fence crossing project and tested against an image dataset which had been previously processed by a human operator. Our program placed images into categories representing the confidence of a particular sequence of images containing a fence crossing event. This resulted in a reduction of 54.8% of images that required further human operator characterization while retaining 72.6% of the known fence crossing events. This program can provide researchers using remote camera data the ability to reduce the time and cost required for image post-processing and characterization. Further, we discuss how this procedure might be generalized to situations not specifically related to animal use of linear features.

Measurement and image processing evaluation of surface modifications of dental implants G4 pure titanium created by different techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bulutsuz, A. G., E-mail: asligunaya@gmail.com; Demircioglu, P., E-mail: pinar.demircioglu@adu.edu.tr; Bogrekci, I., E-mail: ismail.bogrekci@adu.edu.tr

Foreign substances and organic tissue interaction placed into the jaw in order to eliminate tooth loss involves a highly complex process. Many biological reactions take place as well as the biomechanical forces that influence this formation. Osseointegration denotes to the direct structural and functional association between the living bone and the load-bearing artificial implant's surface. Taking into consideration of the requirements in the manufacturing processes of the implants, surface characterizations with high precise measurement techniques are investigated and thus long-term success of dental implant is emphasized on the importance of these processes in this study. In this research, the detailedmore » surface characterization was performed to identify the dependence of the manufacturing techniques on the surface properties by using the image processing methods and using the scanning electron microscope (SEM) for morphological properties in 3D and Taylor Hobson stylus profilometer for roughness properties in 2D. Three implant surfaces fabricated by different manufacturing techniques were inspected, and a machined surface was included into the study as a reference specimen. The results indicated that different surface treatments were strongly influenced surface morphology. Thus 2D and 3D precise inspection techniques were highlighted on the importance for surface characterization. Different image analyses techniques such as Dark-light technique were used to verify the surface measurement results. The computational phase was performed using image processing toolbox in Matlab with precise evaluation of the roughness for the implant surfaces. The relationship between the number of black and white pixels and surface roughness is presented. FFT image processing and analyses results explicitly imply that the technique is useful in the determination of surface roughness. The results showed that the number of black pixels in the image increases with increase in surface roughness.« less

Form or function: Does focusing on body functionality protect women from body dissatisfaction when viewing media images?

PubMed

Mulgrew, Kate E; Tiggemann, Marika

2018-01-01

We examined whether shifting young women's ( N =322) attention toward functionality components of media-portrayed idealized images would protect against body dissatisfaction. Image type was manipulated via images of models in either an objectified body-as-object form or active body-as-process form; viewing focus was manipulated via questions about the appearance or functionality of the models. Social comparison was examined as a moderator. Negative outcomes were most pronounced within the process-related conditions (body-as-process images or functionality viewing focus) and for women who reported greater functionality comparison. Results suggest that functionality-based depictions, reflections, and comparisons may actually produce worse outcomes than those based on appearance.

Chromaticity based smoke removal in endoscopic images

NASA Astrophysics Data System (ADS)

Tchaka, Kevin; Pawar, Vijay M.; Stoyanov, Danail

2017-02-01

In minimally invasive surgery, image quality is a critical pre-requisite to ensure a surgeons ability to perform a procedure. In endoscopic procedures, image quality can deteriorate for a number of reasons such as fogging due to the temperature gradient after intra-corporeal insertion, lack of focus and due to smoke generated when using electro-cautery to dissect tissues without bleeding. In this paper we investigate the use of vision processing techniques to remove surgical smoke and improve the clarity of the image. We model the image formation process by introducing a haze medium to account for the degradation of visibility. For simplicity and computational efficiency we use an adapted dark-channel prior method combined with histogram equalization to remove smoke artifacts to recover the radiance image and enhance the contrast and brightness of the final result. Our initial results on images from robotic assisted procedures are promising and show that the proposed approach may be used to enhance image quality during surgery without additional suction devices. In addition, the processing pipeline may be used as an important part of a robust surgical vision pipeline that can continue working in the presence of smoke.

Contribution of non-negative matrix factorization to the classification of remote sensing images

NASA Astrophysics Data System (ADS)

Karoui, M. S.; Deville, Y.; Hosseini, S.; Ouamri, A.; Ducrot, D.

2008-10-01

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. The classification process requires some pre-processing, especially for data size reduction. The most usual technique is Principal Component Analysis. Another approach consists in regarding each pixel of the multispectral image as a mixture of pure elements contained in the observed area. Using Blind Source Separation (BSS) methods, one can hope to unmix each pixel and to perform the recognition of the classes constituting the observed scene. Our contribution consists in using Non-negative Matrix Factorization (NMF) combined with sparse coding as a solution to BSS, in order to generate new images (which are at least partly separated images) using HRV SPOT images from Oran area, Algeria). These images are then used as inputs of a supervised classifier integrating textural information. The results of classifications of these "separated" images show a clear improvement (correct pixel classification rate improved by more than 20%) compared to classification of initial (i.e. non separated) images. These results show the contribution of NMF as an attractive pre-processing for classification of multispectral remote sensing imagery.

Normalized Temperature Contrast Processing in Infrared Flash Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

Process perspective on image quality evaluation

NASA Astrophysics Data System (ADS)

Leisti, Tuomas; Halonen, Raisa; Kokkonen, Anna; Weckman, Hanna; Mettänen, Marja; Lensu, Lasse; Ritala, Risto; Oittinen, Pirkko; Nyman, Göte

2008-01-01

The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Information theoretic analysis of edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

Rapid visuomotor processing of phobic images in spider- and snake-fearful participants.

PubMed

Haberkamp, Anke; Schmidt, Filipp; Schmidt, Thomas

2013-10-01

This study investigates enhanced visuomotor processing of phobic compared to fear-relevant and neutral stimuli. We used a response priming design to measure rapid, automatic motor activation by natural images (spiders, snakes, mushrooms, and flowers) in spider-fearful, snake-fearful, and control participants. We found strong priming effects in all tasks and conditions; however, results showed marked differences between groups. Most importantly, in the group of spider-fearful individuals, spider pictures had a strong and specific influence on even the fastest motor responses: Phobic primes entailed the largest priming effects, and phobic targets accelerated responses, both effects indicating speeded response activation by phobic images. In snake-fearful participants, this processing enhancement for phobic material was less pronounced and extended to both snake and spider images. We conclude that spider phobia leads to enhanced processing capacity for phobic images. We argue that this is enabled by long-term perceptual learning processes. © 2013.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Flood mapping from Sentinel-1 and Landsat-8 data: a case study from river Evros, Greece

NASA Astrophysics Data System (ADS)

Kyriou, Aggeliki; Nikolakopoulos, Konstantinos

2015-10-01

Floods are suddenly and temporary natural events, affecting areas which are not normally covered by water. The influence of floods plays a significant role both in society and the natural environment, therefore flood mapping is crucial. Remote sensing data can be used to develop flood map in an efficient and effective way. This work is focused on expansion of water bodies overtopping natural levees of the river Evros, invading the surroundings areas and converting them in flooded. Different techniques of flood mapping were used using data from active and passive remote sensing sensors like Sentinlel-1 and Landsat-8 respectively. Space borne pairs obtained from Sentinel-1 were processed in this study. Each pair included an image during the flood, which is called "crisis image" and another one before the event, which is called "archived image". Both images covering the same area were processed producing a map, which shows the spread of the flood. Multispectral data From Landsat-8 were also processed in order to detect and map the flooded areas. Different image processing techniques were applied and the results were compared to the respective results of the radar data processing.

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination

NASA Astrophysics Data System (ADS)

Rocha, José Celso; Passalia, Felipe José; Matos, Felipe Delestro; Takahashi, Maria Beatriz; Maserati, Marc Peter, Jr.; Alves, Mayra Fernanda; de Almeida, Tamie Guibu; Cardoso, Bruna Lopes; Basso, Andrea Cristina; Nogueira, Marcelo Fábio Gouveia

2017-12-01

There is currently no objective, real-time and non-invasive method for evaluating the quality of mammalian embryos. In this study, we processed images of in vitro produced bovine blastocysts to obtain a deeper comprehension of the embryonic morphological aspects that are related to the standard evaluation of blastocysts. Information was extracted from 482 digital images of blastocysts. The resulting imaging data were individually evaluated by three experienced embryologists who graded their quality. To avoid evaluation bias, each image was related to the modal value of the evaluations. Automated image processing produced 36 quantitative variables for each image. The images, the modal and individual quality grades, and the variables extracted could potentially be used in the development of artificial intelligence techniques (e.g., evolutionary algorithms and artificial neural networks), multivariate modelling and the study of defined structures of the whole blastocyst.

Spaceborne SAR Imaging Algorithm for Coherence Optimized.

PubMed

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application.

Spaceborne SAR Imaging Algorithm for Coherence Optimized

PubMed Central

Qiu, Zhiwei; Yue, Jianping; Wang, Xueqin; Yue, Shun

2016-01-01

This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. PMID:26871446

Earth Observation Services (Image Processing Software)

NASA Technical Reports Server (NTRS)

1992-01-01

San Diego State University and Environmental Systems Research Institute, with other agencies, have applied satellite imaging and image processing techniques to geographic information systems (GIS) updating. The resulting images display land use and are used by a regional planning agency for applications like mapping vegetation distribution and preserving wildlife habitats. The EOCAP program provides government co-funding to encourage private investment in, and to broaden the use of NASA-developed technology for analyzing information about Earth and ocean resources.

Mirion--a software package for automatic processing of mass spectrometric images.

PubMed

Paschke, C; Leisner, A; Hester, A; Maass, K; Guenther, S; Bouschen, W; Spengler, B

2013-08-01

Mass spectrometric imaging (MSI) techniques are of growing interest for the Life Sciences. In recent years, the development of new instruments employing ion sources that are tailored for spatial scanning allowed the acquisition of large data sets. A subsequent data processing, however, is still a bottleneck in the analytical process, as a manual data interpretation is impossible within a reasonable time frame. The transformation of mass spectrometric data into spatial distribution images of detected compounds turned out to be the most appropriate method to visualize the results of such scans, as humans are able to interpret images faster and easier than plain numbers. Image generation, thus, is a time-consuming and complex yet very efficient task. The free software package "Mirion," presented in this paper, allows the handling and analysis of data sets acquired by mass spectrometry imaging. Mirion can be used for image processing of MSI data obtained from many different sources, as it uses the HUPO-PSI-based standard data format imzML, which is implemented in the proprietary software of most of the mass spectrometer companies. Different graphical representations of the recorded data are available. Furthermore, automatic calculation and overlay of mass spectrometric images promotes direct comparison of different analytes for data evaluation. The program also includes tools for image processing and image analysis.

Content-based retrieval of historical Ottoman documents stored as textual images.

PubMed

Saykol, Ediz; Sinop, Ali Kemal; Güdükbay, Ugur; Ulusoy, Ozgür; Cetin, A Enis

2004-03-01

There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts.

Identification of optimal mask size parameter for noise filtering in 99mTc-methylene diphosphonate bone scintigraphy images.

PubMed

Pandey, Anil K; Bisht, Chandan S; Sharma, Param D; ArunRaj, Sreedharan Thankarajan; Taywade, Sameer; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-11-01

Tc-methylene diphosphonate (Tc-MDP) bone scintigraphy images have limited number of counts per pixel. A noise filtering method based on local statistics of the image produces better results than a linear filter. However, the mask size has a significant effect on image quality. In this study, we have identified the optimal mask size that yields a good smooth bone scan image. Forty four bone scan images were processed using mask sizes 3, 5, 7, 9, 11, 13, and 15 pixels. The input and processed images were reviewed in two steps. In the first step, the images were inspected and the mask sizes that produced images with significant loss of clinical details in comparison with the input image were excluded. In the second step, the image quality of the 40 sets of images (each set had input image, and its corresponding three processed images with 3, 5, and 7-pixel masks) was assessed by two nuclear medicine physicians. They selected one good smooth image from each set of images. The image quality was also assessed quantitatively with a line profile. Fisher's exact test was used to find statistically significant differences in image quality processed with 5 and 7-pixel mask at a 5% cut-off. A statistically significant difference was found between the image quality processed with 5 and 7-pixel mask at P=0.00528. The identified optimal mask size to produce a good smooth image was found to be 7 pixels. The best mask size for the John-Sen Lee filter was found to be 7×7 pixels, which yielded Tc-methylene diphosphonate bone scan images with the highest acceptable smoothness.

The Study of Residential Areas Extraction Based on GF-3 Texture Image Segmentation

NASA Astrophysics Data System (ADS)

Shao, G.; Luo, H.; Tao, X.; Ling, Z.; Huang, Y.

2018-04-01

The study chooses the standard stripe and dual polarization SAR images of GF-3 as the basic data. Residential areas extraction processes and methods based upon GF-3 images texture segmentation are compared and analyzed. GF-3 images processes include radiometric calibration, complex data conversion, multi-look processing, images filtering, and then conducting suitability analysis for different images filtering methods, the filtering result show that the filtering method of Kuan is efficient for extracting residential areas, then, we calculated and analyzed the texture feature vectors using the GLCM (the Gary Level Co-occurrence Matrix), texture feature vectors include the moving window size, step size and angle, the result show that window size is 11*11, step is 1, and angle is 0°, which is effective and optimal for the residential areas extracting. And with the FNEA (Fractal Net Evolution Approach), we segmented the GLCM texture images, and extracted the residential areas by threshold setting. The result of residential areas extraction verified and assessed by confusion matrix. Overall accuracy is 0.897, kappa is 0.881, and then we extracted the residential areas by SVM classification based on GF-3 images, the overall accuracy is less 0.09 than the accuracy of extraction method based on GF-3 Texture Image Segmentation. We reached the conclusion that residential areas extraction based on GF-3 SAR texture image multi-scale segmentation is simple and highly accurate. although, it is difficult to obtain multi-spectrum remote sensing image in southern China, in cloudy and rainy weather throughout the year, this paper has certain reference significance.

Possibilities of Processing Archival Photogrammetric Images Captured by Rollei 6006 Metric Camera Using Current Method

NASA Astrophysics Data System (ADS)

Dlesk, A.; Raeva, P.; Vach, K.

2018-05-01

Processing of analog photogrammetric negatives using current methods brings new challenges and possibilities, for example, creation of a 3D model from archival images which enables the comparison of historical state and current state of cultural heritage objects. The main purpose of this paper is to present possibilities of processing archival analog images captured by photogrammetric camera Rollei 6006 metric. In 1994, the Czech company EuroGV s.r.o. carried out photogrammetric measurements of former limestone quarry the Great America located in the Central Bohemian Region in the Czech Republic. All the negatives of photogrammetric images, complete documentation, coordinates of geodetically measured ground control points, calibration reports and external orientation of images calculated in the Combined Adjustment Program are preserved and were available for the current processing. Negatives of images were scanned and processed using structure from motion method (SfM). The result of the research is a statement of what accuracy is possible to expect from the proposed methodology using Rollei metric images originally obtained for terrestrial intersection photogrammetry while adhering to the proposed methodology.

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, Guoqing

1992-01-01

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.

PubMed

Göbl, Rüdiger; Navab, Nassir; Hennersperger, Christoph

2018-06-01

Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms. With SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time. The pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time. Our software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.

Multi-frame image processing with panning cameras and moving subjects

NASA Astrophysics Data System (ADS)

Paolini, Aaron; Humphrey, John; Curt, Petersen; Kelmelis, Eric

2014-06-01

Imaging scenarios commonly involve erratic, unpredictable camera behavior or subjects that are prone to movement, complicating multi-frame image processing techniques. To address these issues, we developed three techniques that can be applied to multi-frame image processing algorithms in order to mitigate the adverse effects observed when cameras are panning or subjects within the scene are moving. We provide a detailed overview of the techniques and discuss the applicability of each to various movement types. In addition to this, we evaluated algorithm efficacy with demonstrated benefits using field test video, which has been processed using our commercially available surveillance product. Our results show that algorithm efficacy is significantly improved in common scenarios, expanding our software's operational scope. Our methods introduce little computational burden, enabling their use in real-time and low-power solutions, and are appropriate for long observation periods. Our test cases focus on imaging through turbulence, a common use case for multi-frame techniques. We present results of a field study designed to test the efficacy of these techniques under expanded use cases.

Electrocortical consequences of image processing: The influence of working memory load and worry.

PubMed

White, Evan J; Grant, DeMond M

2017-03-30

Research suggests that worry precludes emotional processing as well as biases attentional processes. Although there is burgeoning evidence for the relationship between executive functioning and worry, more research in this area is needed. A recent theory suggests one mechanism for the negative effects of worry on neural indicators of attention may be working memory load, however few studies have examined this directly. The goal of the current study was to document the influence of both visual and verbal working memory load and worry on attention allocation during processing of emotional images in a cued image paradigm. It was hypothesized that working memory load will decrease attention allocation during processing of emotional images. This was tested among 38 participants using a modified S1-S2 paradigm. Results indicated that both the visual and verbal working memory tasks resulted in a reduction of attention allocation to the processing of images across stimulus types compared to the baseline task, although only for individuals low in worry. These data extend the literature by documenting decreased neural responding (i.e., LPP amplitude) to imagery both the visual and verbal working memory load, particularly among individuals low in worry. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Current Trends in Image Assessment. Working Paper Series.

ERIC Educational Resources Information Center

Fellers, John

Image assessment in higher education and procedures for conducting image assessments are discussed. Image assessment is the process of finding out what others think about an organization. It is proposed that when image assessments are approached objectively, the results can help determine constituent needs, anticipate vocational trends, survey…

Infrared thermal facial image sequence registration analysis and verification

NASA Astrophysics Data System (ADS)

Chen, Chieh-Li; Jian, Bo-Lin

2015-03-01

To study the emotional responses of subjects to the International Affective Picture System (IAPS), infrared thermal facial image sequence is preprocessed for registration before further analysis such that the variance caused by minor and irregular subject movements is reduced. Without affecting the comfort level and inducing minimal harm, this study proposes an infrared thermal facial image sequence registration process that will reduce the deviations caused by the unconscious head shaking of the subjects. A fixed image for registration is produced through the localization of the centroid of the eye region as well as image translation and rotation processes. Thermal image sequencing will then be automatically registered using the two-stage genetic algorithm proposed. The deviation before and after image registration will be demonstrated by image quality indices. The results show that the infrared thermal image sequence registration process proposed in this study is effective in localizing facial images accurately, which will be beneficial to the correlation analysis of psychological information related to the facial area.

Implementation of Remote 3-Dimensional Image Guided Radiation Therapy Quality Assurance for Radiation Therapy Oncology Group Clinical Trials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui Yunfeng; Galvin, James M.; Radiation Therapy Oncology Group, American College of Radiology, Philadelphia, Pennsylvania

2013-01-01

Purpose: To report the process and initial experience of remote credentialing of three-dimensional (3D) image guided radiation therapy (IGRT) as part of the quality assurance (QA) of submitted data for Radiation Therapy Oncology Group (RTOG) clinical trials; and to identify major issues resulting from this process and analyze the review results on patient positioning shifts. Methods and Materials: Image guided radiation therapy datasets including in-room positioning CT scans and daily shifts applied were submitted through the Image Guided Therapy QA Center from institutions for the IGRT credentialing process, as required by various RTOG trials. A centralized virtual environment is establishedmore » at the RTOG Core Laboratory, containing analysis tools and database infrastructure for remote review by the Physics Principal Investigators of each protocol. The appropriateness of IGRT technique and volumetric image registration accuracy were evaluated. Registration accuracy was verified by repeat registration with a third-party registration software system. With the accumulated review results, registration differences between those obtained by the Physics Principal Investigators and from the institutions were analyzed for different imaging sites, shift directions, and imaging modalities. Results: The remote review process was successfully carried out for 87 3D cases (out of 137 total cases, including 2-dimensional and 3D) during 2010. Frequent errors in submitted IGRT data and challenges in the review of image registration for some special cases were identified. Workarounds for these issues were developed. The average differences of registration results between reviewers and institutions ranged between 2 mm and 3 mm. Large discrepancies in the superior-inferior direction were found for megavoltage CT cases, owing to low spatial resolution in this direction for most megavoltage CT cases. Conclusion: This first experience indicated that remote review for 3D IGRT as part of QA for RTOG clinical trials is feasible and effective. The magnitude of registration discrepancy between institution and reviewer was presented, and the major issues were investigated to further improve this remote evaluation process.« less

Studies in optical parallel processing. [All optical and electro-optic approaches

NASA Technical Reports Server (NTRS)

Lee, S. H.

1978-01-01

Threshold and A/D devices for converting a gray scale image into a binary one were investigated for all-optical and opto-electronic approaches to parallel processing. Integrated optical logic circuits (IOC) and optical parallel logic devices (OPA) were studied as an approach to processing optical binary signals. In the IOC logic scheme, a single row of an optical image is coupled into the IOC substrate at a time through an array of optical fibers. Parallel processing is carried out out, on each image element of these rows, in the IOC substrate and the resulting output exits via a second array of optical fibers. The OPAL system for parallel processing which uses a Fabry-Perot interferometer for image thresholding and analog-to-digital conversion, achieves a higher degree of parallel processing than is possible with IOC.

Retinal imaging analysis based on vessel detection.

PubMed

Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

2017-07-01

With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art. © 2017 Wiley Periodicals, Inc.

Smart Camera Technology Increases Quality

NASA Technical Reports Server (NTRS)

2004-01-01

When it comes to real-time image processing, everyone is an expert. People begin processing images at birth and rapidly learn to control their responses through the real-time processing of the human visual system. The human eye captures an enormous amount of information in the form of light images. In order to keep the brain from becoming overloaded with all the data, portions of an image are processed at a higher resolution than others, such as a traffic light changing colors. changing colors. In the same manner, image processing products strive to extract the information stored in light in the most efficient way possible. Digital cameras available today capture millions of pixels worth of information from incident light. However, at frame rates more than a few per second, existing digital interfaces are overwhelmed. All the user can do is store several frames to memory until that memory is full and then subsequent information is lost. New technology pairs existing digital interface technology with an off-the-shelf complementary metal oxide semiconductor (CMOS) imager to provide more than 500 frames per second of specialty image processing. The result is a cost-effective detection system unlike any other.

“Lucky Averaging”: Quality improvement on Adaptive Optics Scanning Laser Ophthalmoscope Images

PubMed Central

Huang, Gang; Zhong, Zhangyi; Zou, Weiyao; Burns, Stephen A.

2012-01-01

Adaptive optics(AO) has greatly improved retinal image resolution. However, even with AO, temporal and spatial variations in image quality still occur due to wavefront fluctuations, intra-frame focus shifts and other factors. As a result, aligning and averaging images can produce a mean image that has lower resolution or contrast than the best images within a sequence. To address this, we propose an image post-processing scheme called “lucky averaging”, analogous to lucky imaging (Fried, 1978) based on computing the best local contrast over time. Results from eye data demonstrate improvements in image quality. PMID:21964097

Supervised restoration of degraded medical images using multiple-point geostatistics.

PubMed

Pham, Tuan D

2012-06-01

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Endemic Images and the Desensitization Process.

ERIC Educational Resources Information Center

Saigh, Philip A.; Antoun, Fouad T.

1984-01-01

Examined the effects of endemic images on levels of anxiety and achievement of 48 high school students. Results suggested that a combination of endemic images and study skills training was as effective as desensitization plus study skills training. Includes the endemic image questionnaire. (JAC)

Visualizing tissue molecular structure of a black type of canola (Brassica) seed with a thick seed coat after heat-related processing in a chemical way.

PubMed

Yu, Peiqiang

2013-02-20

Heat-related processing of cereal grains, legume seeds, and oil seeds could be used to improve nutrient availability in ruminants. However, different types of processing may have a different impact on intrinsic structure of tissues. To date, there is little research on structure changes after processing within intact tissues. The synchrotron-based molecular imaging technique enables us to detect inherent structure change on a molecular level. The objective of this study was to visualize tissue of black-type canola (Brassica) seed with a thick seed coat after heat-related processing in a chemical way using the synchrotron imaging technique. The results showed that the chemical images of protein amides were obtained through the imaging technique for the raw, wet, and dry heated black type of canola seed tissues. It seems that different types of processing have a different impact on the protein spectral profile in the black type of canola tissues. Wet heating had a greater impact on the protein α-helix to β-sheet ratio than dry heating. Both dry and wet heating resulted in different patterns in amide I, the second derivative, and FSD spectra. However, the exact differences in the tissue images are relatively difficult to be obtained through visual comparison. Future studies should focus on (1) comparing the response and sensitivity of canola seeds to various processing methods between the yellow-type and black-type of canola seeds; (2) developing a sensitive method to compare the image difference between tissues and between treatments; (3) developing a method to link images to nutrient digestion, and (4) revealing how structure changes affect nutrient absorption in humans and animals.

Image processing and machine learning for fully automated probabilistic evaluation of medical images.

PubMed

Sajn, Luka; Kukar, Matjaž

2011-12-01

The paper presents results of our long-term study on using image processing and data mining methods in a medical imaging. Since evaluation of modern medical images is becoming increasingly complex, advanced analytical and decision support tools are involved in integration of partial diagnostic results. Such partial results, frequently obtained from tests with substantial imperfections, are integrated into ultimate diagnostic conclusion about the probability of disease for a given patient. We study various topics such as improving the predictive power of clinical tests by utilizing pre-test and post-test probabilities, texture representation, multi-resolution feature extraction, feature construction and data mining algorithms that significantly outperform medical practice. Our long-term study reveals three significant milestones. The first improvement was achieved by significantly increasing post-test diagnostic probabilities with respect to expert physicians. The second, even more significant improvement utilizes multi-resolution image parametrization. Machine learning methods in conjunction with the feature subset selection on these parameters significantly improve diagnostic performance. However, further feature construction with the principle component analysis on these features elevates results to an even higher accuracy level that represents the third milestone. With the proposed approach clinical results are significantly improved throughout the study. The most significant result of our study is improvement in the diagnostic power of the whole diagnostic process. Our compound approach aids, but does not replace, the physician's judgment and may assist in decisions on cost effectiveness of tests. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Study of ionospheric anomalies due to impact of typhoon using Principal Component Analysis and image processing

NASA Astrophysics Data System (ADS)

LIN, JYH-WOEI

2012-08-01

Principal Component Analysis (PCA) and image processing are used to determine Total Electron Content (TEC) anomalies in the F-layer of the ionosphere relating to Typhoon Nakri for 29 May, 2008 (UTC). PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00-14:00 UT on 29 May, 2008 when the wind was most intense. Results show that at a height of approximately 150-200 km the TEC anomaly is highly localized; however, it becomes more intense and widespread with height. Potential causes of these results are discussed with emphasis given to acoustic gravity waves caused by wind force.

Low-cost, high-speed back-end processing system for high-frequency ultrasound B-mode imaging.

PubMed

Chang, Jin Ho; Sun, Lei; Yen, Jesse T; Shung, K Kirk

2009-07-01

For real-time visualization of the mouse heart (6 to 13 beats per second), a back-end processing system involving high-speed signal processing functions to form and display images has been developed. This back-end system was designed with new signal processing algorithms to achieve a frame rate of more than 400 images per second. These algorithms were implemented in a simple and cost-effective manner with a single field-programmable gate array (FPGA) and software programs written in C++. The operating speed of the back-end system was investigated by recording the time required for transferring an image to a personal computer. Experimental results showed that the back-end system is capable of producing 433 images per second. To evaluate the imaging performance of the back-end system, a complete imaging system was built. This imaging system, which consisted of a recently reported high-speed mechanical sector scanner assembled with the back-end system, was tested by imaging a wire phantom, a pig eye (in vitro), and a mouse heart (in vivo). It was shown that this system is capable of providing high spatial resolution images with fast temporal resolution.

Low-Cost, High-Speed Back-End Processing System for High-Frequency Ultrasound B-Mode Imaging

PubMed Central

Chang, Jin Ho; Sun, Lei; Yen, Jesse T.; Shung, K. Kirk

2009-01-01

For real-time visualization of the mouse heart (6 to 13 beats per second), a back-end processing system involving high-speed signal processing functions to form and display images has been developed. This back-end system was designed with new signal processing algorithms to achieve a frame rate of more than 400 images per second. These algorithms were implemented in a simple and cost-effective manner with a single field-programmable gate array (FPGA) and software programs written in C++. The operating speed of the back-end system was investigated by recording the time required for transferring an image to a personal computer. Experimental results showed that the back-end system is capable of producing 433 images per second. To evaluate the imaging performance of the back-end system, a complete imaging system was built. This imaging system, which consisted of a recently reported high-speed mechanical sector scanner assembled with the back-end system, was tested by imaging a wire phantom, a pig eye (in vitro), and a mouse heart (in vivo). It was shown that this system is capable of providing high spatial resolution images with fast temporal resolution. PMID:19574160

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Image processing of angiograms: A pilot study

NASA Technical Reports Server (NTRS)

Larsen, L. E.; Evans, R. A.; Roehm, J. O., Jr.

1974-01-01

The technology transfer application this report describes is the result of a pilot study of image-processing methods applied to the image enhancement, coding, and analysis of arteriograms. Angiography is a subspecialty of radiology that employs the introduction of media with high X-ray absorption into arteries in order to study vessel pathology as well as to infer disease of the organs supplied by the vessel in question.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

PubMed Central

Bao, Shunxing; Plassard, Andrew J.; Landman, Bennett A.; Gokhale, Aniruddha

2017-01-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based “medical image processing-as-a-service” offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop’s distributed file system. Despite this promise, HBase’s load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy, and nearly a six-fold improvement over a commonly available network file system (NFS) approach even for relatively small file sets. Moreover, file access latency is lower than network attached storage. PMID:28884169

Combining Digital Watermarking and Fingerprinting Techniques to Identify Copyrights for Color Images

PubMed Central

Hsieh, Shang-Lin; Chen, Chun-Che; Shen, Wen-Shan

2014-01-01

This paper presents a copyright identification scheme for color images that takes advantage of the complementary nature of watermarking and fingerprinting. It utilizes an authentication logo and the extracted features of the host image to generate a fingerprint, which is then stored in a database and also embedded in the host image to produce a watermarked image. When a dispute over the copyright of a suspect image occurs, the image is first processed by watermarking. If the watermark can be retrieved from the suspect image, the copyright can then be confirmed; otherwise, the watermark then serves as the fingerprint and is processed by fingerprinting. If a match in the fingerprint database is found, then the suspect image will be considered a duplicated one. Because the proposed scheme utilizes both watermarking and fingerprinting, it is more robust than those that only adopt watermarking, and it can also obtain the preliminary result more quickly than those that only utilize fingerprinting. The experimental results show that when the watermarked image suffers slight attacks, watermarking alone is enough to identify the copyright. The results also show that when the watermarked image suffers heavy attacks that render watermarking incompetent, fingerprinting can successfully identify the copyright, hence demonstrating the effectiveness of the proposed scheme. PMID:25114966

Planning applications in image analysis

NASA Technical Reports Server (NTRS)

Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

1994-01-01

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

Detection of fuze defects by image-processing methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, M.J.

1988-03-01

This paper describes experimental studies of the detection of mechanical defects by the application of computer-processing methods to real-time radiographic images of fuze assemblies. The experimental results confirm that a new algorithm developed at Materials Research Laboratory has potential for the automatic inspection of these assemblies and of others that contain discrete components. The algorithm was applied to images that contain a range of grey levels and has been found to be tolerant to image variations encountered under simulated production conditions.

A modeling analysis program for the JPL table mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1984-01-01

A detailed review of 110 of the 263 Region B/C images of the 1981 data set is undertaken and a preliminary assessment of 39 images of the 1976-79 data set is presented. The basic spatial characteristics of these images are discussed. Modeling analysis of these images after further data processing will provide useful information about Io and the planetary magnetosphere. Plans for data processing and modeling analysis are outlined. Results of very preliminary modeling activities are presented.

Three-dimensional non-destructive optical evaluation of laser-processing performance using optical coherence tomography.

PubMed

Kim, Youngseop; Choi, Eun Seo; Kwak, Wooseop; Shin, Yongjin; Jung, Woonggyu; Ahn, Yeh-Chan; Chen, Zhongping

2008-06-01

We demonstrate the use of optical coherence tomography (OCT) as a non-destructive diagnostic tool for evaluating laser-processing performance by imaging the features of a pit and a rim. A pit formed on a material at different laser-processing conditions is imaged using both a conventional scanning electron microscope (SEM) and OCT. Then using corresponding images, the geometrical characteristics of the pit are analyzed and compared. From the results, we could verify the feasibility and the potential of the application of OCT to the monitoring of the laser-processing performance.

Three-dimensional non-destructive optical evaluation of laser-processing performance using optical coherence tomography

PubMed Central

Kim, Youngseop; Choi, Eun Seo; Kwak, Wooseop; Shin, Yongjin; Jung, Woonggyu; Ahn, Yeh-Chan; Chen, Zhongping

2014-01-01

We demonstrate the use of optical coherence tomography (OCT) as a non-destructive diagnostic tool for evaluating laser-processing performance by imaging the features of a pit and a rim. A pit formed on a material at different laser-processing conditions is imaged using both a conventional scanning electron microscope (SEM) and OCT. Then using corresponding images, the geometrical characteristics of the pit are analyzed and compared. From the results, we could verify the feasibility and the potential of the application of OCT to the monitoring of the laser-processing performance. PMID:24932051

Developing tools for digital radar image data evaluation

NASA Technical Reports Server (NTRS)

Domik, G.; Leberl, F.; Raggam, J.

1986-01-01

The refinement of radar image analysis methods has led to a need for a systems approach to radar image processing software. Developments stimulated through satellite radar are combined with standard image processing techniques to create a user environment to manipulate and analyze airborne and satellite radar images. One aim is to create radar products for the user from the original data to enhance the ease of understanding the contents. The results are called secondary image products and derive from the original digital images. Another aim is to support interactive SAR image analysis. Software methods permit use of a digital height model to create ortho images, synthetic images, stereo-ortho images, radar maps or color combinations of different component products. Efforts are ongoing to integrate individual tools into a combined hardware/software environment for interactive radar image analysis.

Spatial Standard Observer

NASA Technical Reports Server (NTRS)

Watson, Andrw B. (Inventor)

2010-01-01

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image. or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image . Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer. SSO. Some embodiments include masking functions. window functions. special treatment for images lying on or near border and pre-processing of test images.

Spatial Standard Observer

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

2012-01-01

The present invention relates to devices and methods for the measurement and/or for the specification of the perceptual intensity of a visual image, or the perceptual distance between a pair of images. Grayscale test and reference images are processed to produce test and reference luminance images. A luminance filter function is convolved with the reference luminance image to produce a local mean luminance reference image. Test and reference contrast images are produced from the local mean luminance reference image and the test and reference luminance images respectively, followed by application of a contrast sensitivity filter. The resulting images are combined according to mathematical prescriptions to produce a Just Noticeable Difference, JND value, indicative of a Spatial Standard Observer, SSO. Some embodiments include masking functions, window functions, special treatment for images lying on or near borders and pre-processing of test images.

Processing and refinement of steel microstructure images for assisting in computerized heat treatment of plain carbon steel

NASA Astrophysics Data System (ADS)

Gupta, Shubhank; Panda, Aditi; Naskar, Ruchira; Mishra, Dinesh Kumar; Pal, Snehanshu

2017-11-01

Steels are alloys of iron and carbon, widely used in construction and other applications. The evolution of steel microstructure through various heat treatment processes is an important factor in controlling properties and performance of steel. Extensive experimentations have been performed to enhance the properties of steel by customizing heat treatment processes. However, experimental analyses are always associated with high resource requirements in terms of cost and time. As an alternative solution, we propose an image processing-based technique for refinement of raw plain carbon steel microstructure images, into a digital form, usable in experiments related to heat treatment processes of steel in diverse applications. The proposed work follows the conventional steps practiced by materials engineers in manual refinement of steel images; and it appropriately utilizes basic image processing techniques (including filtering, segmentation, opening, and clustering) to automate the whole process. The proposed refinement of steel microstructure images is aimed to enable computer-aided simulations of heat treatment of plain carbon steel, in a timely and cost-efficient manner; hence it is beneficial for the materials and metallurgy industry. Our experimental results prove the efficiency and effectiveness of the proposed technique.

On-Ground Processing of Yaogan-24 Remote Sensing Satellite Attitude Data and Verification Using Geometric Field Calibration

PubMed Central

Wang, Mi; Fan, Chengcheng; Yang, Bo; Jin, Shuying; Pan, Jun

2016-01-01

Satellite attitude accuracy is an important factor affecting the geometric processing accuracy of high-resolution optical satellite imagery. To address the problem whereby the accuracy of the Yaogan-24 remote sensing satellite’s on-board attitude data processing is not high enough and thus cannot meet its image geometry processing requirements, we developed an approach involving on-ground attitude data processing and digital orthophoto (DOM) and the digital elevation model (DEM) verification of a geometric calibration field. The approach focuses on three modules: on-ground processing based on bidirectional filter, overall weighted smoothing and fitting, and evaluation in the geometric calibration field. Our experimental results demonstrate that the proposed on-ground processing method is both robust and feasible, which ensures the reliability of the observation data quality, convergence and stability of the parameter estimation model. In addition, both the Euler angle and quaternion could be used to build a mathematical fitting model, while the orthogonal polynomial fitting model is more suitable for modeling the attitude parameter. Furthermore, compared to the image geometric processing results based on on-board attitude data, the image uncontrolled and relative geometric positioning result accuracy can be increased by about 50%. PMID:27483287

Alpha-band rhythm modulation under the condition of subliminal face presentation: MEG study.

PubMed

Sakuraba, Satoshi; Kobayashi, Hana; Sakai, Shinya; Yokosawa, Koichi

2013-01-01

The human brain has two streams to process visual information: a dorsal stream and a ventral stream. Negative potential N170 or its magnetic counterpart M170 is known as the face-specific signal originating from the ventral stream. It is possible to present a visual image unconsciously by using continuous flash suppression (CFS), which is a visual masking technique adopting binocular rivalry. In this work, magnetoencephalograms were recorded during presentation of the three invisible images: face images, which are processed by the ventral stream; tool images, which could be processed by the dorsal stream, and a blank image. Alpha-band activities detected by sensors that are sensitive to M170 were compared. The alpha-band rhythm was suppressed more during presentation of face images than during presentation of the blank image (p=.028). The suppression remained for about 1 s after ending presentations. However, no significant difference was observed between tool and other images. These results suggest that alpha-band rhythm can be modulated also by unconscious visual images.

Assessment of Restoration Methods of X-Ray Images with Emphasis on Medical Photogrammetric Usage

NASA Astrophysics Data System (ADS)

Hosseinian, S.; Arefi, H.

2016-06-01

Nowadays, various medical X-ray imaging methods such as digital radiography, computed tomography and fluoroscopy are used as important tools in diagnostic and operative processes especially in the computer and robotic assisted surgeries. The procedures of extracting information from these images require appropriate deblurring and denoising processes on the pre- and intra-operative images in order to obtain more accurate information. This issue becomes more considerable when the X-ray images are planned to be employed in the photogrammetric processes for 3D reconstruction from multi-view X-ray images since, accurate data should be extracted from images for 3D modelling and the quality of X-ray images affects directly on the results of the algorithms. For restoration of X-ray images, it is essential to consider the nature and characteristics of these kinds of images. X-ray images exhibit severe quantum noise due to limited X-ray photons involved. The assumptions of Gaussian modelling are not appropriate for photon-limited images such as X-ray images, because of the nature of signal-dependant quantum noise. These images are generally modelled by Poisson distribution which is the most common model for low-intensity imaging. In this paper, existing methods are evaluated. For this purpose, after demonstrating the properties of medical X-ray images, the more efficient and recommended methods for restoration of X-ray images would be described and assessed. After explaining these approaches, they are implemented on samples from different kinds of X-ray images. By considering the results, it is concluded that using PURE-LET, provides more effective and efficient denoising than other examined methods in this research.

Fingerprint image enhancement by differential hysteresis processing.

PubMed

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

Evaluation of the effects of the seasonal variation of solar elevation angle and azimuth on the processes of digital filtering and thematic classification of relief units

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

1983-01-01

The effects of the seasonal variation of illumination over digital processing of LANDSAT images are evaluated. Two sets of LANDSAT data referring to the orbit 150 and row 28 were selected with illumination parameters varying from 43 deg to 64 deg for azimuth and from 30 deg to 36 deg for solar elevation respectively. IMAGE-100 system permitted the digital processing of LANDSAT data. Original images were transformed by means of digital filtering so as to enhance their spatial features. The resulting images were used to obtain an unsupervised classification of relief units. Topographic variables (declivity, altitude, relief range and slope length) were used to identify the true relief units existing on the ground. The LANDSAT over pass data show that digital processing is highly affected by illumination geometry, and there is no correspondence between relief units as defined by spectral features and those resulting from topographic features.

The integration processing of the visual and auditory information in videos of real-world events: an ERP study.

PubMed

Liu, Baolin; Wang, Zhongning; Jin, Zhixing

2009-09-11

In real life, the human brain usually receives information through visual and auditory channels and processes the multisensory information, but studies on the integration processing of the dynamic visual and auditory information are relatively few. In this paper, we have designed an experiment, where through the presentation of common scenario, real-world videos, with matched and mismatched actions (images) and sounds as stimuli, we aimed to study the integration processing of synchronized visual and auditory information in videos of real-world events in the human brain, through the use event-related potentials (ERPs) methods. Experimental results showed that videos of mismatched actions (images) and sounds would elicit a larger P400 as compared to videos of matched actions (images) and sounds. We believe that the P400 waveform might be related to the cognitive integration processing of mismatched multisensory information in the human brain. The results also indicated that synchronized multisensory information would interfere with each other, which would influence the results of the cognitive integration processing.

Application of ultrasound processed images in space: Quanitative assessment of diffuse affectations

NASA Astrophysics Data System (ADS)

Pérez-Poch, A.; Bru, C.; Nicolau, C.

The purpose of this study was to evaluate diffuse affectations in the liver using texture image processing techniques. Ultrasound diagnose equipments are the election of choice to be used in space environments as they are free from hazardous effects on health. However, due to the need for highly trained radiologists to assess the images, this imaging method is mainly applied on focal lesions rather than on non-focal ones. We have conducted a clinical study on 72 patients with different degrees of chronic hepatopaties and a group of control of 18 individuals. All subjects' clinical reports and results of biopsies were compared to the degree of affectation calculated by our computer system , thus validating the method. Full statistical results are given in the present paper showing a good correlation (r=0.61) between pathologist's report and analysis of the heterogenicity of the processed images from the liver. This computer system to analyze diffuse affectations may be used in-situ or via telemedicine to the ground.

Application of ultrasound processed images in space: assessing diffuse affectations

NASA Astrophysics Data System (ADS)

Pérez-Poch, A.; Bru, C.; Nicolau, C.

The purpose of this study was to evaluate diffuse affectations in the liver using texture image processing techniques. Ultrasound diagnose equipments are the election of choice to be used in space environments as they are free from hazardous effects on health. However, due to the need for highly trained radiologists to assess the images, this imaging method is mainly applied on focal lesions rather than on non-focal ones. We have conducted a clinical study on 72 patients with different degrees of chronic hepatopaties and a group of control of 18 individuals. All subjects' clinical reports and results of biopsies were compared to the degree of affectation calculated by our computer system , thus validating the method. Full statistical results are given in the present paper showing a good correlation (r=0.61) between pathologist's report and analysis of the heterogenicity of the processed images from the liver. This computer system to analyze diffuse affectations may be used in-situ or via telemedicine to the ground.

A user's guide to the Mariner 9 television reduced data record

NASA Technical Reports Server (NTRS)

Seidman, J. B.; Green, W. B.; Jepsen, P. L.; Ruiz, R. M.; Thorpe, T. E.

1973-01-01

The Mariner 9 television experiment used two cameras to photograph Mars from an orbiting spacecraft. For quantitative analysis of the image data transmitted to earth, the pictures were processed by digital computer to remove camera-induced distortions. The removal process was performed by the JPL Image Processing Laboratory (IPL) using calibration data measured during prelaunch testing of the cameras. The Reduced Data Record (RDR) is the set of data which results from the distortion-removal, or decalibration, process. The principal elements of the RDR are numerical data on magnetic tape and photographic data. Numerical data are the result of correcting for geometric and photometric distortions and residual-image effects. Photographic data are reproduced on negative and positive transparency films, strip contact and enlargement prints, and microfiche positive transparency film. The photographic data consist of two versions of each TV frame created by applying two special enhancement processes to the numerical data.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

An improved K-means clustering algorithm in agricultural image segmentation

NASA Astrophysics Data System (ADS)

Cheng, Huifeng; Peng, Hui; Liu, Shanmei

Image segmentation is the first important step to image analysis and image processing. In this paper, according to color crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial clustering center and cluster number in application of mean-variance approach and rough set theory followed by clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the computation amounts and enhance precision and accuracy of clustering.

Speckle noise removal applied to ultrasound image of carotid artery based on total least squares model.

PubMed

Yang, Lei; Lu, Jun; Dai, Ming; Ren, Li-Jie; Liu, Wei-Zong; Li, Zhen-Zhou; Gong, Xue-Hao

2016-10-06

An ultrasonic image speckle noise removal method by using total least squares model is proposed and applied onto images of cardiovascular structures such as the carotid artery. On the basis of the least squares principle, the related principle of minimum square method is applied to cardiac ultrasound image speckle noise removal process to establish the model of total least squares, orthogonal projection transformation processing is utilized for the output of the model, and the denoising processing for the cardiac ultrasound image speckle noise is realized. Experimental results show that the improved algorithm can greatly improve the resolution of the image, and meet the needs of clinical medical diagnosis and treatment of the cardiovascular system for the head and neck. Furthermore, the success in imaging of carotid arteries has strong implications in neurological complications such as stroke.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

Research based on the SoPC platform of feature-based image registration

NASA Astrophysics Data System (ADS)

Shi, Yue-dong; Wang, Zhi-hui

2015-12-01

This paper focuses on the study of implementing feature-based image registration by System on a Programmable Chip (SoPC) hardware platform. We solidify the image registration algorithm on the FPGA chip, in which embedded soft core processor Nios II can speed up the image processing system. In this way, we can make image registration technology get rid of the PC. And, consequently, this kind of technology will be got an extensive use. The experiment result indicates that our system shows stable performance, particularly in terms of matching processing which noise immunity is good. And feature points of images show a reasonable distribution.

Performance of an image analysis processing system for hen tracking in an environmental preference chamber.

PubMed

Kashiha, Mohammad Amin; Green, Angela R; Sales, Tatiana Glogerley; Bahr, Claudia; Berckmans, Daniel; Gates, Richard S

2014-10-01

Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared with the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed. ©2014 Poultry Science Association Inc.

Fingerprint pattern restoration by digital image processing techniques.

PubMed

Wen, Che-Yen; Yu, Chiu-Chung

2003-09-01

Fingerprint evidence plays an important role in solving criminal problems. However, defective (lacking information needed for completeness) or contaminated (undesirable information included) fingerprint patterns make identifying and recognizing processes difficult. Unfortunately. this is the usual case. In the recognizing process (enhancement of patterns, or elimination of "false alarms" so that a fingerprint pattern can be searched in the Automated Fingerprint Identification System (AFIS)), chemical and physical techniques have been proposed to improve pattern legibility. In the identifying process, a fingerprint examiner can enhance contaminated (but not defective) fingerprint patterns under guidelines provided by the Scientific Working Group on Friction Ridge Analysis, Study and Technology (SWGFAST), the Scientific Working Group on Imaging Technology (SWGIT), and an AFIS working group within the National Institute of Justice. Recently, the image processing techniques have been successfully applied in forensic science. For example, we have applied image enhancement methods to improve the legibility of digital images such as fingerprints and vehicle plate numbers. In this paper, we propose a novel digital image restoration technique based on the AM (amplitude modulation)-FM (frequency modulation) reaction-diffusion method to restore defective or contaminated fingerprint patterns. This method shows its potential application to fingerprint pattern enhancement in the recognizing process (but not for the identifying process). Synthetic and real images are used to show the capability of the proposed method. The results of enhancing fingerprint patterns by the manual process and our method are evaluated and compared.

Thermal imaging as a biometrics approach to facial signature authentication.

PubMed

Guzman, A M; Goryawala, M; Wang, Jin; Barreto, A; Andrian, J; Rishe, N; Adjouadi, M

2013-01-01

A new thermal imaging framework with unique feature extraction and similarity measurements for face recognition is presented. The research premise is to design specialized algorithms that would extract vasculature information, create a thermal facial signature and identify the individual. The proposed algorithm is fully integrated and consolidates the critical steps of feature extraction through the use of morphological operators, registration using the Linear Image Registration Tool and matching through unique similarity measures designed for this task. The novel approach at developing a thermal signature template using four images taken at various instants of time ensured that unforeseen changes in the vasculature over time did not affect the biometric matching process as the authentication process relied only on consistent thermal features. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using the similarity measures showed an average accuracy of 88.46% for skeletonized signatures and 90.39% for anisotropically diffused signatures. The highly accurate results obtained in the matching process clearly demonstrate the ability of the thermal infrared system to extend in application to other thermal imaging based systems. Empirical results applying this approach to an existing database of thermal images proves this assertion.

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

PubMed Central

Bayır, Şafak

2016-01-01

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

Characterization of Axial Inducer Cavitation Instabilities via High Speed Video Recordings

NASA Technical Reports Server (NTRS)

Arellano, Patrick; Peneda, Marinelle; Ferguson, Thomas; Zoladz, Thomas

2011-01-01

Sub-scale water tests were undertaken to assess the viability of utilizing high resolution, high frame-rate digital video recordings of a liquid rocket engine turbopump axial inducer to characterize cavitation instabilities. These high speed video (HSV) images of various cavitation phenomena, including higher order cavitation, rotating cavitation, alternating blade cavitation, and asymmetric cavitation, as well as non-cavitating flows for comparison, were recorded from various orientations through an acrylic tunnel using one and two cameras at digital recording rates ranging from 6,000 to 15,700 frames per second. The physical characteristics of these cavitation forms, including the mechanisms that define the cavitation frequency, were identified. Additionally, these images showed how the cavitation forms changed and transitioned from one type (tip vortex) to another (sheet cavitation) as the inducer boundary conditions (inlet pressures) were changed. Image processing techniques were developed which tracked the formation and collapse of cavitating fluid in a specified target area, both in the temporal and frequency domains, in order to characterize the cavitation instability frequency. The accuracy of the analysis techniques was found to be very dependent on target size for higher order cavitation, but much less so for the other phenomena. Tunnel-mounted piezoelectric, dynamic pressure transducers were present throughout these tests and were used as references in correlating the results obtained by image processing. Results showed good agreement between image processing and dynamic pressure spectral data. The test set-up, test program, and test results including H-Q and suction performance, dynamic environment and cavitation characterization, and image processing techniques and results will be discussed.

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Investigating the Role of Global Histogram Equalization Technique for 99mTechnetium-Methylene diphosphonate Bone Scan Image Enhancement

PubMed Central

Pandey, Anil Kumar; Sharma, Param Dev; Dheer, Pankaj; Parida, Girish Kumar; Goyal, Harish; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

Purpose of the Study: 99mTechnetium-methylene diphosphonate (99mTc-MDP) bone scan images have limited number of counts per pixel, and hence, they have inferior image quality compared to X-rays. Theoretically, global histogram equalization (GHE) technique can improve the contrast of a given image though practical benefits of doing so have only limited acceptance. In this study, we have investigated the effect of GHE technique for 99mTc-MDP-bone scan images. Materials and Methods: A set of 89 low contrast 99mTc-MDP whole-body bone scan images were included in this study. These images were acquired with parallel hole collimation on Symbia E gamma camera. The images were then processed with histogram equalization technique. The image quality of input and processed images were reviewed by two nuclear medicine physicians on a 5-point scale where score of 1 is for very poor and 5 is for the best image quality. A statistical test was applied to find the significance of difference between the mean scores assigned to input and processed images. Results: This technique improves the contrast of the images; however, oversaturation was noticed in the processed images. Student's t-test was applied, and a statistically significant difference in the input and processed image quality was found at P < 0.001 (with α = 0.05). However, further improvement in image quality is needed as per requirements of nuclear medicine physicians. Conclusion: GHE techniques can be used on low contrast bone scan images. In some of the cases, a histogram equalization technique in combination with some other postprocessing technique is useful. PMID:29142344

Use of ERTS data for a multidisciplinary analysis of Michigan resources. [forests, agriculture, soils, and landforms

NASA Technical Reports Server (NTRS)

Andersen, A. L.; Myers, W. L.; Safir, G.; Whiteside, E. P. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The results of this investigation of ratioing simulated ERTS spectral bands and several non-ERTS bands (all collected by an airborne multispectral scanner) indicate that significant terrain information is available from band-ratio images. Ratio images, which are based on the relative spectral changes which occur from one band to another, are useful for enhancing differences and aiding the image interpreter in identifying and mapping the distribution of such terrain elements as seedling crops, all bare soil, organic soil, mineral soil, forest and woodlots, and marsh areas. In addition, the ratio technique may be useful for computer processing to obtain recognition images of large areas at lower costs than with statistical decision rules. The results of this study of ratio processing of aircraft MSS data will be useful for future processing and evaluation of ERTS-1 data for soil and landform studies. Additionally, the results of ratioing spectral bands other than those currently collected by ERTS-1 suggests that some other bands (particularly a thermal band) would be useful in future satellites.

Digital watermarking algorithm research of color images based on quaternion Fourier transform

NASA Astrophysics Data System (ADS)

An, Mali; Wang, Weijiang; Zhao, Zhen

2013-10-01

A watermarking algorithm of color images based on the quaternion Fourier Transform (QFFT) and improved quantization index algorithm (QIM) is proposed in this paper. The original image is transformed by QFFT, the watermark image is processed by compression and quantization coding, and then the processed watermark image is embedded into the components of the transformed original image. It achieves embedding and blind extraction of the watermark image. The experimental results show that the watermarking algorithm based on the improved QIM algorithm with distortion compensation achieves a good tradeoff between invisibility and robustness, and better robustness for the attacks of Gaussian noises, salt and pepper noises, JPEG compression, cropping, filtering and image enhancement than the traditional QIM algorithm.

Nonlinear Optical Image Processing with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.; Deiss, Ron (Technical Monitor)

1994-01-01

The transmission properties of some bacteriorhodopsin film spatial light modulators are uniquely suited to allow nonlinear optical image processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude transmission feature of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. The bacteriorhodopsin film displays the logarithmic amplitude response for write beam intensities spanning a dynamic range greater than 2.0 orders of magnitude. We present experimental results demonstrating the principle and capability for several different image and noise situations, including deterministic noise and speckle. Using the bacteriorhodopsin film, we successfully filter out image noise from the transformed image that cannot be removed from the original image.

PICASSO: an end-to-end image simulation tool for space and airborne imaging systems

NASA Astrophysics Data System (ADS)

Cota, Steve A.; Bell, Jabin T.; Boucher, Richard H.; Dutton, Tracy E.; Florio, Chris J.; Franz, Geoffrey A.; Grycewicz, Thomas J.; Kalman, Linda S.; Keller, Robert A.; Lomheim, Terrence S.; Paulson, Diane B.; Willkinson, Timothy S.

2008-08-01

The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of image quality from fundamental design parameters - is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.

PICASSO: an end-to-end image simulation tool for space and airborne imaging systems

NASA Astrophysics Data System (ADS)

Cota, Stephen A.; Bell, Jabin T.; Boucher, Richard H.; Dutton, Tracy E.; Florio, Christopher J.; Franz, Geoffrey A.; Grycewicz, Thomas J.; Kalman, Linda S.; Keller, Robert A.; Lomheim, Terrence S.; Paulson, Diane B.; Wilkinson, Timothy S.

2010-06-01

The design of any modern imaging system is the end result of many trade studies, each seeking to optimize image quality within real world constraints such as cost, schedule and overall risk. Image chain analysis - the prediction of image quality from fundamental design parameters - is an important part of this design process. At The Aerospace Corporation we have been using a variety of image chain analysis tools for many years, the Parameterized Image Chain Analysis & Simulation SOftware (PICASSO) among them. In this paper we describe our PICASSO tool, showing how, starting with a high quality input image and hypothetical design descriptions representative of the current state of the art in commercial imaging satellites, PICASSO can generate standard metrics of image quality in support of the decision processes of designers and program managers alike.

Image processing on the image with pixel noise bits removed

NASA Astrophysics Data System (ADS)

Chuang, Keh-Shih; Wu, Christine

1992-06-01

Our previous studies used statistical methods to assess the noise level in digital images of various radiological modalities. We separated the pixel data into signal bits and noise bits and demonstrated visually that the removal of the noise bits does not affect the image quality. In this paper we apply image enhancement techniques on noise-bits-removed images and demonstrate that the removal of noise bits has no effect on the image property. The image processing techniques used are gray-level look up table transformation, Sobel edge detector, and 3-D surface display. Preliminary results show no noticeable difference between original image and noise bits removed image using look up table operation and Sobel edge enhancement. There is a slight enhancement of the slicing artifact in the 3-D surface display of the noise bits removed image.

MIA - A free and open source software for gray scale medical image analysis.

PubMed

Wollny, Gert; Kellman, Peter; Ledesma-Carbayo, María-Jesus; Skinner, Matthew M; Hublin, Jean-Jaques; Hierl, Thomas

2013-10-11

Gray scale images make the bulk of data in bio-medical image analysis, and hence, the main focus of many image processing tasks lies in the processing of these monochrome images. With ever improving acquisition devices, spatial and temporal image resolution increases, and data sets become very large.Various image processing frameworks exists that make the development of new algorithms easy by using high level programming languages or visual programming. These frameworks are also accessable to researchers that have no background or little in software development because they take care of otherwise complex tasks. Specifically, the management of working memory is taken care of automatically, usually at the price of requiring more it. As a result, processing large data sets with these tools becomes increasingly difficult on work station class computers.One alternative to using these high level processing tools is the development of new algorithms in a languages like C++, that gives the developer full control over how memory is handled, but the resulting workflow for the prototyping of new algorithms is rather time intensive, and also not appropriate for a researcher with little or no knowledge in software development.Another alternative is in using command line tools that run image processing tasks, use the hard disk to store intermediate results, and provide automation by using shell scripts. Although not as convenient as, e.g. visual programming, this approach is still accessable to researchers without a background in computer science. However, only few tools exist that provide this kind of processing interface, they are usually quite task specific, and don't provide an clear approach when one wants to shape a new command line tool from a prototype shell script. The proposed framework, MIA, provides a combination of command line tools, plug-ins, and libraries that make it possible to run image processing tasks interactively in a command shell and to prototype by using the according shell scripting language. Since the hard disk becomes the temporal storage memory management is usually a non-issue in the prototyping phase. By using string-based descriptions for filters, optimizers, and the likes, the transition from shell scripts to full fledged programs implemented in C++ is also made easy. In addition, its design based on atomic plug-ins and single tasks command line tools makes it easy to extend MIA, usually without the requirement to touch or recompile existing code. In this article, we describe the general design of MIA, a general purpouse framework for gray scale image processing. We demonstrated the applicability of the software with example applications from three different research scenarios, namely motion compensation in myocardial perfusion imaging, the processing of high resolution image data that arises in virtual anthropology, and retrospective analysis of treatment outcome in orthognathic surgery. With MIA prototyping algorithms by using shell scripts that combine small, single-task command line tools is a viable alternative to the use of high level languages, an approach that is especially useful when large data sets need to be processed.

On-demand server-side image processing for web-based DICOM image display

NASA Astrophysics Data System (ADS)

Sakusabe, Takaya; Kimura, Michio; Onogi, Yuzo

2000-04-01

Low cost image delivery is needed in modern networked hospitals. If a hospital has hundreds of clients, cost of client systems is a big problem. Naturally, a Web-based system is the most effective solution. But a Web browser could not display medical images with certain image processing such as a lookup table transformation. We developed a Web-based medical image display system using Web browser and on-demand server-side image processing. All images displayed on a Web page are generated from DICOM files on a server, delivered on-demand. User interaction on the Web page is handled by a client-side scripting technology such as JavaScript. This combination makes a look-and-feel of an imaging workstation not only for its functionality but also for its speed. Real time update of images with tracing mouse motion is achieved on Web browser without any client-side image processing which may be done by client-side plug-in technology such as Java Applets or ActiveX. We tested performance of the system in three cases. Single client, small number of clients in a fast speed network, and large number of clients in a normal speed network. The result shows that there are very slight overhead for communication and very scalable in number of clients.

Method and apparatus for optical encoding with compressible imaging

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

2006-01-01

The present invention presents an optical encoder with increased conversion rates. Improvement in the conversion rate is a result of combining changes in the pattern recognition encoder's scale pattern with an image sensor readout technique which takes full advantage of those changes, and lends itself to operation by modern, high-speed, ultra-compact microprocessors and digital signal processors (DSP) or field programmable gate array (FPGA) logic elements which can process encoder scale images at the highest speeds. Through these improvements, all three components of conversion time (reciprocal conversion rate)--namely exposure time, image readout time, and image processing time--are minimized.

Fluorescent screens and image processing for the APS linac test stand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, W.; Ko, K.

A fluorescent screen was used to monitor relative beam position and spot size of a 56-MeV electron beam in the linac test stand. A chromium doped alumina ceramic screen inserted into the beam was monitored by a video camera. The resulting image was captured using a frame grabber and stored into memory. Reconstruction and analysis of the stored image was performed using PV-WAVE. This paper will discuss the hardware and software implementation of the fluorescent screen and imaging system. Proposed improvements for the APS linac fluorescent screens and image processing will also be discussed.

Local wavelet transform: a cost-efficient custom processor for space image compression

NASA Astrophysics Data System (ADS)

Masschelein, Bart; Bormans, Jan G.; Lafruit, Gauthier

2002-11-01

Thanks to its intrinsic scalability features, the wavelet transform has become increasingly popular as decorrelator in image compression applications. Throuhgput, memory requirements and complexity are important parameters when developing hardware image compression modules. An implementation of the classical, global wavelet transform requires large memory sizes and implies a large latency between the availability of the input image and the production of minimal data entities for entropy coding. Image tiling methods, as proposed by JPEG2000, reduce the memory sizes and the latency, but inevitably introduce image artefacts. The Local Wavelet Transform (LWT), presented in this paper, is a low-complexity wavelet transform architecture using a block-based processing that results in the same transformed images as those obtained by the global wavelet transform. The architecture minimizes the processing latency with a limited amount of memory. Moreover, as the LWT is an instruction-based custom processor, it can be programmed for specific tasks, such as push-broom processing of infinite-length satelite images. The features of the LWT makes it appropriate for use in space image compression, where high throughput, low memory sizes, low complexity, low power and push-broom processing are important requirements.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Visual and visuomotor processing of hands and tools as a case study of cross talk between the dorsal and ventral streams.

PubMed

Almeida, Jorge; Amaral, Lénia; Garcea, Frank E; Aguiar de Sousa, Diana; Xu, Shan; Mahon, Bradford Z; Martins, Isabel Pavão

2018-05-24

A major principle of organization of the visual system is between a dorsal stream that processes visuomotor information and a ventral stream that supports object recognition. Most research has focused on dissociating processing across these two streams. Here we focus on how the two streams interact. We tested neurologically-intact and impaired participants in an object categorization task over two classes of objects that depend on processing within both streams-hands and tools. We measured how unconscious processing of images from one of these categories (e.g., tools) affects the recognition of images from the other category (i.e., hands). Our findings with neurologically-intact participants demonstrated that processing an image of a hand hampers the subsequent processing of an image of a tool, and vice versa. These results were not present in apraxic patients (N = 3). These findings suggest local and global inhibitory processes working in tandem to co-register information across the two streams.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

One-Step Real-Image Reflection Holograms

ERIC Educational Resources Information Center

Buah-Bassuah, Paul K.; Vannoni, Maurizio; Molesini, Giuseppe

2007-01-01

A holographic process is presented where the object is made of the real image produced by a two-mirror system. Single-step reflection hologram recording is achieved. Details of the process are given, optics concepts are outlined and demonstrative results are presented. (Contains 6 figures and 2 footnotes.)

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

Noise reduction and image enhancement using a hardware implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

David, Robert; Williams, Erin; de Tremiolles, Ghislain; Tannhof, Pascal

1999-03-01

In this paper, we present a neural based solution developed for noise reduction and image enhancement using the ZISC, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm and the K-Nearest Neighbor algorithm. Artificial neural networks present the advantages of processing time reduction in comparison with classical models, adaptability, and the weighted property of pattern learning. The goal of the developed application is image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). Image results show a quantitative improvement over the noisy image as well as the efficiency of this system. Further enhancements are being examined to improve the output of the system.

A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

An Interactive Procedure to Preserve the Desired Edges during the Image Processing of Noise Reduction

NASA Astrophysics Data System (ADS)

Hsu, Chih-Yu; Huang, Hsuan-Yu; Lee, Lin-Tsang

2010-12-01

The paper propose a new procedure including four stages in order to preserve the desired edges during the image processing of noise reduction. A denoised image can be obtained from a noisy image at the first stage of the procedure. At the second stage, an edge map can be obtained by the Canny edge detector to find the edges of the object contours. Manual modification of an edge map at the third stage is optional to capture all the desired edges of the object contours. At the final stage, a new method called Edge Preserved Inhomogeneous Diffusion Equation (EPIDE) is used to smooth the noisy images or the previously denoised image at the first stage for achieving the edge preservation. The Optical Character Recognition (OCR) results in the experiments show that the proposed procedure has the best recognition result because of the capability of edge preservation.

Assessment of body fat based on potential function clustering segmentation of computed tomography images

NASA Astrophysics Data System (ADS)

Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong

2005-01-01

In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.

Breadboard linear array scan imager using LSI solid-state technology

NASA Technical Reports Server (NTRS)

Tracy, R. A.; Brennan, J. A.; Frankel, D. G.; Noll, R. E.

1976-01-01

The performance of large scale integration photodiode arrays in a linear array scan (pushbroom) breadboard was evaluated for application to multispectral remote sensing of the earth's resources. The technical approach, implementation, and test results of the program are described. Several self scanned linear array visible photodetector focal plane arrays were fabricated and evaluated in an optical bench configuration. A 1728-detector array operating in four bands (0.5 - 1.1 micrometer) was evaluated for noise, spectral response, dynamic range, crosstalk, MTF, noise equivalent irradiance, linearity, and image quality. Other results include image artifact data, temporal characteristics, radiometric accuracy, calibration experience, chip alignment, and array fabrication experience. Special studies and experimentation were included in long array fabrication and real-time image processing for low-cost ground stations, including the use of computer image processing. High quality images were produced and all objectives of the program were attained.

Improved Bat Algorithm Applied to Multilevel Image Thresholding

PubMed Central

2014-01-01

Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733

3CCD image segmentation and edge detection based on MATLAB

NASA Astrophysics Data System (ADS)

He, Yong; Pan, Jiazhi; Zhang, Yun

2006-09-01

This research aimed to identify weeds from crops in early stage in the field operation by using image-processing technology. As 3CCD images offer greater binary value difference between weed and crop section than ordinary digital images taken by common cameras. It has 3 channels (green, red, ifred) which takes a snap-photo of the same area, and the three images can be composed into one image, which facilitates the segmentation of different areas. By the application of image-processing toolkit on MATLAB, the different areas in the image can be segmented clearly. As edge detection technique is the first and very important step in image processing, The different result of different processing method was compared. Especially, by using the wavelet packet transform toolkit on MATLAB, An image was preprocessed and then the edge was extracted, and getting more clearly cut image of edge. The segmentation methods include operations as erosion, dilation and other algorithms to preprocess the images. It is of great importance to segment different areas in digital images in field real time, so as to be applied in precision farming, to saving energy and herbicide and many other materials. At present time Large scale software as MATLAB on PC was used, but the computation can be reduced and integrated into a small embed system, which means that the application of this technique in agricultural engineering is feasible and of great economical value.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

Three-dimensional analysis of alveolar bone resorption by image processing of 3-D dental CT images

NASA Astrophysics Data System (ADS)

Nagao, Jiro; Kitasaka, Takayuki; Mori, Kensaku; Suenaga, Yasuhito; Yamada, Shohzoh; Naitoh, Munetaka

2006-03-01

We have developed a novel system that provides total support for assessment of alveolar bone resorption, caused by periodontitis, based on three-dimensional (3-D) dental CT images. In spite of the difficulty in perceiving the complex 3-D shape of resorption, dentists assessing resorption location and severity have been relying on two-dimensional radiography and probing, which merely provides one-dimensional information (depth) about resorption shape. However, there has been little work on assisting assessment of the disease by 3-D image processing and visualization techniques. This work provides quantitative evaluation results and figures for our system that measures the three-dimensional shape and spread of resorption. It has the following functions: (1) measures the depth of resorption by virtually simulating probing in the 3-D CT images, taking advantage of image processing of not suffering obstruction by teeth on the inter-proximal sides and much smaller measurement intervals than the conventional examination; (2) visualizes the disposition of the depth by movies and graphs; (3) produces a quantitative index and intuitive visual representation of the spread of resorption in the inter-radicular region in terms of area; and (4) calculates the volume of resorption as another severity index in the inter-radicular region and the region outside it. Experimental results in two cases of 3-D dental CT images and a comparison of the results with the clinical examination results and experts' measurements of the corresponding patients confirmed that the proposed system gives satisfying results, including 0.1 to 0.6mm of resorption measurement (probing) error and fairly intuitive presentation of measurement and calculation results.

Real-time image dehazing using local adaptive neighborhoods and dark-channel-prior

NASA Astrophysics Data System (ADS)

Valderrama, Jesus A.; Díaz-Ramírez, Víctor H.; Kober, Vitaly; Hernandez, Enrique

2015-09-01

A real-time algorithm for single image dehazing is presented. The algorithm is based on calculation of local neighborhoods of a hazed image inside a moving window. The local neighborhoods are constructed by computing rank-order statistics. Next the dark-channel-prior approach is applied to the local neighborhoods to estimate the transmission function of the scene. By using the suggested approach there is no need for applying a refining algorithm to the estimated transmission such as the soft matting algorithm. To achieve high-rate signal processing the proposed algorithm is implemented exploiting massive parallelism on a graphics processing unit (GPU). Computer simulation results are carried out to test the performance of the proposed algorithm in terms of dehazing efficiency and speed of processing. These tests are performed using several synthetic and real images. The obtained results are analyzed and compared with those obtained with existing dehazing algorithms.

Planetary image conversion task

NASA Technical Reports Server (NTRS)

Martin, M. D.; Stanley, C. L.; Laughlin, G.

1985-01-01

The Planetary Image Conversion Task group processed 12,500 magnetic tapes containing raw imaging data from JPL planetary missions and produced an image data base in consistent format on 1200 fully packed 6250-bpi tapes. The output tapes will remain at JPL. A copy of the entire tape set was delivered to US Geological Survey, Flagstaff, Ariz. A secondary task converted computer datalogs, which had been stored in project specific MARK IV File Management System data types and structures, to flat-file, text format that is processable on any modern computer system. The conversion processing took place at JPL's Image Processing Laboratory on an IBM 370-158 with existing software modified slightly to meet the needs of the conversion task. More than 99% of the original digital image data was successfully recovered by the conversion task. However, processing data tapes recorded before 1975 was destructive. This discovery is of critical importance to facilities responsible for maintaining digital archives since normal periodic random sampling techniques would be unlikely to detect this phenomenon, and entire data sets could be wiped out in the act of generating seemingly positive sampling results. Reccomended follow-on activities are also included.

Processing infrared images of aircraft lapjoints

NASA Technical Reports Server (NTRS)

Syed, Hazari; Winfree, William P.; Cramer, K. E.

1992-01-01

Techniques for processing IR images of aging aircraft lapjoint data are discussed. Attention is given to a technique for detecting disbonds in aircraft lapjoints which clearly delineates the disbonded region from the bonded regions. The technique is weak on unpainted aircraft skin surfaces, but can be overridden by using a self-adhering contact sheet. Neural network analysis on raw temperature data has been shown to be an effective tool for visualization of images. Numerical simulation results show the above processing technique to be an effective tool in delineating the disbonds.

Fast and Accurate Cell Tracking by a Novel Optical-Digital Hybrid Method

NASA Astrophysics Data System (ADS)

Torres-Cisneros, M.; Aviña-Cervantes, J. G.; Pérez-Careta, E.; Ambriz-Colín, F.; Tinoco, Verónica; Ibarra-Manzano, O. G.; Plascencia-Mora, H.; Aguilera-Gómez, E.; Ibarra-Manzano, M. A.; Guzman-Cabrera, R.; Debeir, Olivier; Sánchez-Mondragón, J. J.

2013-09-01

An innovative methodology to detect and track cells using microscope images enhanced by optical cross-correlation techniques is proposed in this paper. In order to increase the tracking sensibility, image pre-processing has been implemented as a morphological operator on the microscope image. Results show that the pre-processing process allows for additional frames of cell tracking, therefore increasing its robustness. The proposed methodology can be used in analyzing different problems such as mitosis, cell collisions, and cell overlapping, ultimately designed to identify and treat illnesses and malignancies.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, G.P.; Skeate, M.F.

1996-10-15

An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.

Perceived visual speed constrained by image segmentation

NASA Technical Reports Server (NTRS)

Verghese, P.; Stone, L. S.

1996-01-01

Little is known about how or where the visual system parses the visual scene into objects or surfaces. However, it is generally assumed that the segmentation and grouping of pieces of the image into discrete entities is due to 'later' processing stages, after the 'early' processing of the visual image by local mechanisms selective for attributes such as colour, orientation, depth, and motion. Speed perception is also thought to be mediated by early mechanisms tuned for speed. Here we show that manipulating the way in which an image is parsed changes the way in which local speed information is processed. Manipulations that cause multiple stimuli to appear as parts of a single patch degrade speed discrimination, whereas manipulations that perceptually divide a single large stimulus into parts improve discrimination. These results indicate that processes as early as speed perception may be constrained by the parsing of the visual image into discrete entities.

Diffusion processes in tumors: A nuclear medicine approach

NASA Astrophysics Data System (ADS)

Amaya, Helman

2016-07-01

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and 18F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer software was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical 18F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical information processing with transformation of the spatial coherence of light

NASA Astrophysics Data System (ADS)

Bykovskii, Yurii A.; Markilov, A. A.; Rodin, V. G.; Starikov, S. N.

1995-10-01

A description is given of systems with spatially incoherent illumination, intended for spectral and correlation analysis, and for the recording of Fourier holograms. These systems make use of transformation of the degree of the spatial coherence of light. The results are given of the processing of images and signals, including those transmitted by a bundle of fibre-optic waveguides both as monochromatic light and as quasimonochromatic radiation from a cathode-ray tube. The feasibility of spatial frequency filtering and of correlation analysis of images with a bipolar impulse response is considered for systems with spatially incoherent illumination where these tasks are performed by double transformation of the spatial coherence of light. A description is given of experimental systems and the results of image processing are reported.

Automatic tissue image segmentation based on image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Reducing noise component on medical images

NASA Astrophysics Data System (ADS)

Semenishchev, Evgeny; Voronin, Viacheslav; Dub, Vladimir; Balabaeva, Oksana

2018-04-01

Medical visualization and analysis of medical data is an actual direction. Medical images are used in microbiology, genetics, roentgenology, oncology, surgery, ophthalmology, etc. Initial data processing is a major step towards obtaining a good diagnostic result. The paper considers the approach allows an image filtering with preservation of objects borders. The algorithm proposed in this paper is based on sequential data processing. At the first stage, local areas are determined, for this purpose the method of threshold processing, as well as the classical ICI algorithm, is applied. The second stage uses a method based on based on two criteria, namely, L2 norm and the first order square difference. To preserve the boundaries of objects, we will process the transition boundary and local neighborhood the filtering algorithm with a fixed-coefficient. For example, reconstructed images of CT, x-ray, and microbiological studies are shown. The test images show the effectiveness of the proposed algorithm. This shows the applicability of analysis many medical imaging applications.

Image processing of metal surface with structured light

NASA Astrophysics Data System (ADS)

Luo, Cong; Feng, Chang; Wang, Congzheng

2014-09-01

In structured light vision measurement system, the ideal image of structured light strip, in addition to black background , contains only the gray information of the position of the stripe. However, the actual image contains image noise, complex background and so on, which does not belong to the stripe, and it will cause interference to useful information. To extract the stripe center of mental surface accurately, a new processing method was presented. Through adaptive median filtering, the noise can be preliminary removed, and the noise which introduced by CCD camera and measured environment can be further removed with difference image method. To highlight fine details and enhance the blurred regions between the stripe and noise, the sharping algorithm is used which combine the best features of Laplacian operator and Sobel operator. Morphological opening operation and closing operation are used to compensate the loss of information.Experimental results show that this method is effective in the image processing, not only to restrain the information but also heighten contrast. It is beneficial for the following processing.

Optical coherence tomography imaging based on non-harmonic analysis

NASA Astrophysics Data System (ADS)

Cao, Xu; Hirobayashi, Shigeki; Chong, Changho; Morosawa, Atsushi; Totsuka, Koki; Suzuki, Takuya

2009-11-01

A new processing technique called Non-Harmonic Analysis (NHA) is proposed for OCT imaging. Conventional Fourier-Domain OCT relies on the FFT calculation which depends on the window function and length. Axial resolution is counter proportional to the frame length of FFT that is limited by the swept range of the swept source in SS-OCT, or the pixel counts of CCD in SD-OCT degraded in FD-OCT. However, NHA process is intrinsically free from this trade-offs; NHA can resolve high frequency without being influenced by window function or frame length of sampled data. In this study, NHA process is explained and applied to OCT imaging and compared with OCT images based on FFT. In order to validate the benefit of NHA in OCT, we carried out OCT imaging based on NHA with the three different sample of onion-skin,human-skin and pig-eye. The results show that NHA process can realize practical image resolution that is equivalent to 100nm swept range only with less than half-reduced wavelength range.

Iris recognition via plenoptic imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos-Villalobos, Hector J.; Boehnen, Chris Bensing; Bolme, David S.

Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios.

ASI aurora search: an attempt of intelligent image processing for circular fisheye lens.

PubMed

Yang, Xi; Gao, Xinbo; Song, Bin; Wang, Nannan; Yang, Dong

2018-04-02

The circular fisheye lens exhibits an approximately 180° angular field-of-view (FOV), which is much larger than that of an ordinary lens. Thus, images captured with a circular fisheye lens are distributed non-uniformly with spherical deformation. Along with the fast development of deep neural networks for normal images, how to apply it to achieve intelligent image processing for a circular fisheye lens is a new task of significant importance. In this paper, we take the aurora images captured with all-sky-imagers (ASI) as a typical example. By analyzing the imaging principle of ASI and the magnetic characteristics of the aurora, a deformed region division (DRD) scheme is proposed to replace the region proposals network (RPN) in the advanced mask regional convolutional neural network (Mask R-CNN) framework. Thus, each image can be regarded as a "bag" of deformed regions represented with CNN features. After clustering all CNN features to generate a vocabulary, each deformed region is quantified to its nearest center for indexing. On the stage of an online search, a similarity score is computed by measuring the distances between regions in the query image and all regions in the data set, and the image with the highest value is outputted as the top rank search result. Experimental results show that the proposed method greatly improves the search accuracy and efficiency, demonstrating that it is a valuable attempt of intelligent image processing for circular fisheye lenses.

SU-D-BRD-02: A Web-Based Image Processing and Plan Evaluation Platform (WIPPEP) for Future Cloud-Based Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, X; Liu, L; Xing, L

Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay informationmore » to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform through a web browser and exhibited potential for future cloud based radiotherapy.« less

Tchebichef moment transform on image dithering for mobile applications

NASA Astrophysics Data System (ADS)

Ernawan, Ferda; Abu, Nur Azman; Rahmalan, Hidayah

2012-04-01

Currently, mobile image applications spend a lot of computing process to display images. A true color raw image contains billions of colors and it consumes high computational power in most mobile image applications. At the same time, mobile devices are only expected to be equipped with lower computing process and minimum storage space. Image dithering is a popular technique to reduce the numbers of bit per pixel at the expense of lower quality image displays. This paper proposes a novel approach on image dithering using 2x2 Tchebichef moment transform (TMT). TMT integrates a simple mathematical framework technique using matrices. TMT coefficients consist of real rational numbers. An image dithering based on TMT has the potential to provide better efficiency and simplicity. The preliminary experiment shows a promising result in term of error reconstructions and image visual textures.

New Windows based Color Morphological Operators for Biomedical Image Processing

NASA Astrophysics Data System (ADS)

Pastore, Juan; Bouchet, Agustina; Brun, Marcel; Ballarin, Virginia

2016-04-01

Morphological image processing is well known as an efficient methodology for image processing and computer vision. With the wide use of color in many areas, the interest on the color perception and processing has been growing rapidly. Many models have been proposed to extend morphological operators to the field of color images, dealing with some new problems not present previously in the binary and gray level contexts. These solutions usually deal with the lattice structure of the color space, or provide it with total orders, to be able to define basic operators with required properties. In this work we propose a new locally defined ordering, in the context of window based morphological operators, for the definition of erosions-like and dilation-like operators, which provides the same desired properties expected from color morphology, avoiding some of the drawbacks of the prior approaches. Experimental results show that the proposed color operators can be efficiently used for color image processing.

Optronic System Imaging Simulator (OSIS): imager simulation tool of the ECOMOS project

NASA Astrophysics Data System (ADS)

Wegner, D.; Repasi, E.

2018-04-01

ECOMOS is a multinational effort within the framework of an EDA Project Arrangement. Its aim is to provide a generally accepted and harmonized European computer model for computing nominal Target Acquisition (TA) ranges of optronic imagers operating in the Visible or thermal Infrared (IR). The project involves close co-operation of defense and security industry and public research institutes from France, Germany, Italy, The Netherlands and Sweden. ECOMOS uses two approaches to calculate Target Acquisition (TA) ranges, the analytical TRM4 model and the image-based Triangle Orientation Discrimination model (TOD). In this paper the IR imager simulation tool, Optronic System Imaging Simulator (OSIS), is presented. It produces virtual camera imagery required by the TOD approach. Pristine imagery is degraded by various effects caused by atmospheric attenuation, optics, detector footprint, sampling, fixed pattern noise, temporal noise and digital signal processing. Resulting images might be presented to observers or could be further processed for automatic image quality calculations. For convenience OSIS incorporates camera descriptions and intermediate results provided by TRM4. For input OSIS uses pristine imagery tied with meta information about scene content, its physical dimensions, and gray level interpretation. These images represent planar targets placed at specified distances to the imager. Furthermore, OSIS is extended by a plugin functionality that enables integration of advanced digital signal processing techniques in ECOMOS such as compression, local contrast enhancement, digital turbulence mitiga- tion, to name but a few. By means of this image-based approach image degradations and image enhancements can be investigated, which goes beyond the scope of the analytical TRM4 model.

A Tentative Application Of Morphological Filters To Time-Varying Images

NASA Astrophysics Data System (ADS)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Current advances in molecular imaging: noninvasive in vivo bioluminescent and fluorescent optical imaging in cancer research.

PubMed

Choy, Garry; Choyke, Peter; Libutti, Steven K

2003-10-01

Recently, there has been tremendous interest in developing techniques such as MRI, micro-CT, micro-PET, and SPECT to image function and processes in small animals. These technologies offer deep tissue penetration and high spatial resolution, but compared with noninvasive small animal optical imaging, these techniques are very costly and time consuming to implement. Optical imaging is cost-effective, rapid, easy to use, and can be readily applied to studying disease processes and biology in vivo. In vivo optical imaging is the result of a coalescence of technologies from chemistry, physics, and biology. The development of highly sensitive light detection systems has allowed biologists to use imaging in studying physiological processes. Over the last few decades, biochemists have also worked to isolate and further develop optical reporters such as GFP, luciferase, and cyanine dyes. This article reviews the common types of fluorescent and bioluminescent optical imaging, the typical system platforms and configurations, and the applications in the investigation of cancer biology.

An advanced software suite for the processing and analysis of silicon luminescence images

NASA Astrophysics Data System (ADS)

Payne, D. N. R.; Vargas, C.; Hameiri, Z.; Wenham, S. R.; Bagnall, D. M.

2017-06-01

Luminescence imaging is a versatile characterisation technique used for a broad range of research and industrial applications, particularly for the field of photovoltaics where photoluminescence and electroluminescence imaging is routinely carried out for materials analysis and quality control. Luminescence imaging can reveal a wealth of material information, as detailed in extensive literature, yet these techniques are often only used qualitatively instead of being utilised to their full potential. Part of the reason for this is the time and effort required for image processing and analysis in order to convert image data to more meaningful results. In this work, a custom built, Matlab based software suite is presented which aims to dramatically simplify luminescence image processing and analysis. The suite includes four individual programs which can be used in isolation or in conjunction to achieve a broad array of functionality, including but not limited to, point spread function determination and deconvolution, automated sample extraction, image alignment and comparison, minority carrier lifetime calibration and iron impurity concentration mapping.

Roi-Orientated Sensor Correction Based on Virtual Steady Reimaging Model for Wide Swath High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Zhu, Y.; Jin, S.; Tian, Y.; Wang, M.

2017-09-01

To meet the requirement of high accuracy and high speed processing for wide swath high resolution optical satellite imagery under emergency situation in both ground processing system and on-board processing system. This paper proposed a ROI-orientated sensor correction algorithm based on virtual steady reimaging model for wide swath high resolution optical satellite imagery. Firstly, the imaging time and spatial window of the ROI is determined by a dynamic search method. Then, the dynamic ROI sensor correction model based on virtual steady reimaging model is constructed. Finally, the corrected image corresponding to the ROI is generated based on the coordinates mapping relationship which is established by the dynamic sensor correction model for corrected image and rigours imaging model for original image. Two experimental results show that the image registration between panchromatic and multispectral images can be well achieved and the image distortion caused by satellite jitter can be also corrected efficiently.

Automated aerial image based CD metrology initiated by pattern marking with photomask layout data

NASA Astrophysics Data System (ADS)

Davis, Grant; Choi, Sun Young; Jung, Eui Hee; Seyfarth, Arne; van Doornmalen, Hans; Poortinga, Eric

2007-05-01

The photomask is a critical element in the lithographic image transfer process from the drawn layout to the final structures on the wafer. The non-linearity of the imaging process and the related MEEF impose a tight control requirement on the photomask critical dimensions. Critical dimensions can be measured in aerial images with hardware emulation. This is a more recent complement to the standard scanning electron microscope measurement of wafers and photomasks. Aerial image measurement includes non-linear, 3-dimensional, and materials effects on imaging that cannot be observed directly by SEM measurement of the mask. Aerial image measurement excludes the processing effects of printing and etching on the wafer. This presents a unique contribution to the difficult process control and modeling tasks in mask making. In the past, aerial image measurements have been used mainly to characterize the printability of mask repair sites. Development of photomask CD characterization with the AIMS TM tool was motivated by the benefit of MEEF sensitivity and the shorter feedback loop compared to wafer exposures. This paper describes a new application that includes: an improved interface for the selection of meaningful locations using the photomask and design layout data with the Calibre TM Metrology Interface, an automated recipe generation process, an automated measurement process, and automated analysis and result reporting on a Carl Zeiss AIMS TM system.

Fission gas bubble identification using MATLAB's image processing toolbox

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

SU-G-IeP3-08: Image Reconstruction for Scanning Imaging System Based On Shape-Modulated Point Spreading Function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ruixing; Yang, LV; Xu, Kele

Purpose: Deconvolution is a widely used tool in the field of image reconstruction algorithm when the linear imaging system has been blurred by the imperfect system transfer function. However, due to the nature of Gaussian-liked distribution for point spread function (PSF), the components with coherent high frequency in the image are hard to restored in most of the previous scanning imaging system, even the relatively accurate PSF is acquired. We propose a novel method for deconvolution of images which are obtained by using shape-modulated PSF. Methods: We use two different types of PSF - Gaussian shape and donut shape -more » to convolute the original image in order to simulate the process of scanning imaging. By employing deconvolution of the two images with corresponding given priors, the image quality of the deblurred images are compared. Then we find the critical size of the donut shape compared with the Gaussian shape which has similar deconvolution results. Through calculation of tightened focusing process using radially polarized beam, such size of donut is achievable under same conditions. Results: The effects of different relative size of donut and Gaussian shapes are investigated. When the full width at half maximum (FWHM) ratio of donut and Gaussian shape is set about 1.83, similar resolution results are obtained through our deconvolution method. Decreasing the size of donut will favor the deconvolution method. A mask with both amplitude and phase modulation is used to create a donut-shaped PSF compared with the non-modulated Gaussian PSF. Donut with size smaller than our critical value is obtained. Conclusion: The utility of donutshaped PSF are proved useful and achievable in the imaging and deconvolution processing, which is expected to have potential practical applications in high resolution imaging for biological samples.« less

Assessment of visual communication by information theory

NASA Astrophysics Data System (ADS)

Huck, Friedrich O.; Fales, Carl L.

1994-01-01

This assessment of visual communication integrates the optical design of the image-gathering device with the digital processing for image coding and restoration. Results show that informationally optimized image gathering ordinarily can be relied upon to maximize the information efficiency of decorrelated data and the visual quality of optimally restored images.

a Critical Review of Automated Photogrammetric Processing of Large Datasets

NASA Astrophysics Data System (ADS)

Remondino, F.; Nocerino, E.; Toschi, I.; Menna, F.

2017-08-01

The paper reports some comparisons between commercial software able to automatically process image datasets for 3D reconstruction purposes. The main aspects investigated in the work are the capability to correctly orient large sets of image of complex environments, the metric quality of the results, replicability and redundancy. Different datasets are employed, each one featuring a diverse number of images, GSDs at cm and mm resolutions, and ground truth information to perform statistical analyses of the 3D results. A summary of (photogrammetric) terms is also provided, in order to provide rigorous terms of reference for comparisons and critical analyses.

Alternative techniques for high-resolution spectral estimation of spectrally encoded endoscopy

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Duan, Lian; Javidi, Tara; Ellerbee, Audrey K.

2015-09-01

Spectrally encoded endoscopy (SEE) is a minimally invasive optical imaging modality capable of fast confocal imaging of internal tissue structures. Modern SEE systems use coherent sources to image deep within the tissue and data are processed similar to optical coherence tomography (OCT); however, standard processing of SEE data via the Fast Fourier Transform (FFT) leads to degradation of the axial resolution as the bandwidth of the source shrinks, resulting in a well-known trade-off between speed and axial resolution. Recognizing the limitation of FFT as a general spectral estimation algorithm to only take into account samples collected by the detector, in this work we investigate alternative high-resolution spectral estimation algorithms that exploit information such as sparsity and the general region position of the bulk sample to improve the axial resolution of processed SEE data. We validate the performance of these algorithms using bothMATLAB simulations and analysis of experimental results generated from a home-built OCT system to simulate an SEE system with variable scan rates. Our results open a new door towards using non-FFT algorithms to generate higher quality (i.e., higher resolution) SEE images at correspondingly fast scan rates, resulting in systems that are more accurate and more comfortable for patients due to the reduced image time.

Activity in the fusiform face area supports expert perception in radiologists and does not depend upon holistic processing of images

NASA Astrophysics Data System (ADS)

Engel, Stephen A.; Harley, Erin M.; Pope, Whitney B.; Villablanca, J. Pablo; Mazziotta, John C.; Enzmann, Dieter

2009-02-01

Training in radiology dramatically changes observers' ability to process images, but the neural bases of this visual expertise remain unexplored. Prior imaging work has suggested that the fusiform face area (FFA), normally selectively responsive to faces, becomes responsive to images in observers' area of expertise. The FFA has been hypothesized to be important for "holistic" processing that integrates information across the entire image. Here, we report a cross-sectional study of radiologists that used functional magnetic resonance imaging to measure neural activity in first-year radiology residents, fourth-year radiology residents, and practicing radiologists as they detected abnormalities in chest radiographs. Across subjects, activity in the FFA correlated with visual expertise, measured as behavioral performance during scanning. To test whether processing in the FFA was holistic, we measured its responses both to intact radiographs and radiographs that had been divided into 25 square pieces whose locations were scrambled. Activity in the FFA was equal in magnitude for intact and scrambled images, and responses to both kinds of stimuli correlated reliably with expertise. These results suggest that the FFA is one of the cortical regions that provides the basis of expertise in radiology, but that its contribution is not holistic processing of images.

Localization of the transverse processes in ultrasound for spinal curvature measurement

NASA Astrophysics Data System (ADS)

Kamali, Shahrokh; Ungi, Tamas; Lasso, Andras; Yan, Christina; Lougheed, Matthew; Fichtinger, Gabor

2017-03-01

PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks such as transverse processes, but as bones have reduced visibility in ultrasound imaging, skeletal landmarks are typically segmented manually, which is an exceedingly laborious and long process. We propose an automatic algorithm to segment and localize the surface of bony areas in the transverse process for scoliosis in ultrasound. METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. / Image), including reading the original sequence file. CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.

Estimation of bladder wall location in ultrasound images.

PubMed

Topper, A K; Jernigan, M E

1991-05-01

A method of automatically estimating the location of the bladder wall in ultrasound images is proposed. Obtaining this estimate is intended to be the first stage in the development of an automatic bladder volume calculation system. The first step in the bladder wall estimation scheme involves globally processing the images using standard image processing techniques to highlight the bladder wall. Separate processing sequences are required to highlight the anterior bladder wall and the posterior bladder wall. The sequence to highlight the anterior bladder wall involves Gaussian smoothing and second differencing followed by zero-crossing detection. Median filtering followed by thresholding and gradient detection is used to highlight as much of the rest of the bladder wall as was visible in the original images. Then a 'bladder wall follower'--a line follower with rules based on the characteristics of ultrasound imaging and the anatomy involved--is applied to the processed images to estimate the bladder wall location by following the portions of the bladder wall which are highlighted and filling in the missing segments. The results achieved using this scheme are presented.

[Applicability of non-invasive imaging methods in forensic medicine and forensic anthropology in particular].

PubMed

Marcinková, Mária; Straka, Ľubomír; Novomeský, František; Janík, Martin; Štuller, František; Krajčovič, Jozef

2018-01-01

Massive progress in developing even more precise imaging modalities influenced all medical branches including the forensic medicine. In forensic anthropology, an inevitable part of forensic medicine itself, the use of all imaging modalities becomes even more important. Despite of acquiring more accurate informations about the deceased, all of them can be used in the process of identification and/or age estimation. X - ray imaging is most commonly used in detecting foreign bodies or various pathological changes of the deceased. Computed tomography, on the other hand, can be very helpful in the process of identification, whereas outcomes of this examination can be used for virtual reconstruction of living objects. Magnetic resonance imaging offers new opportunities in detecting cardiovascular pathological processes or develompental anomalies. Ultrasonography provides promising results in age estimation of living subjects without excessive doses of radiation. Processing the latest information sources available, authors introduce the application examples of X - ray imaging, computed tomography, magnetic resonance imaging and ultrasonography in everyday forensic medicine routine, with particular focusing on forensic anthropology.

SIproc: an open-source biomedical data processing platform for large hyperspectral images.

PubMed

Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

2017-04-10

There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

In-line agglomeration degree estimation in fluidized bed pellet coating processes using visual imaging.

PubMed

Mehle, Andraž; Kitak, Domen; Podrekar, Gregor; Likar, Boštjan; Tomaževič, Dejan

2018-05-09

Agglomeration of pellets in fluidized bed coating processes is an undesirable phenomenon that affects the yield and quality of the product. In scope of PAT guidance, we present a system that utilizes visual imaging for in-line monitoring of the agglomeration degree. Seven pilot-scale Wurster coating processes were executed under various process conditions, providing a wide spectrum of process outcomes. Images of pellets were acquired during the coating processes in a contactless manner through an observation window of the coating apparatus. Efficient image analysis methods were developed for automatic recognition of discrete pellets and agglomerates in the acquired images. In-line obtained agglomeration degree trends revealed the agglomeration dynamics in distinct phases of the coating processes. We compared the in-line estimated agglomeration degree in the end point of each process to the results obtained by the off-line sieve analysis reference method. A strong positive correlation was obtained (coefficient of determination R 2 =0.99), confirming the feasibility of the approach. The in-line estimated agglomeration degree enables early detection of agglomeration and provides means for timely interventions to retain it in an acceptable range. Copyright © 2018 Elsevier B.V. All rights reserved.

Digital Imaging

NASA Technical Reports Server (NTRS)

1986-01-01

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez, A; Little, K; Chung, J

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidencemore » of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.« less

Vision function testing for a suprachoroidal retinal prosthesis: effects of image filtering

NASA Astrophysics Data System (ADS)

Barnes, Nick; Scott, Adele F.; Lieby, Paulette; Petoe, Matthew A.; McCarthy, Chris; Stacey, Ashley; Ayton, Lauren N.; Sinclair, Nicholas C.; Shivdasani, Mohit N.; Lovell, Nigel H.; McDermott, Hugh J.; Walker, Janine G.; BVA Consortium,the

2016-06-01

Objective. One strategy to improve the effectiveness of prosthetic vision devices is to process incoming images to ensure that key information can be perceived by the user. This paper presents the first comprehensive results of vision function testing for a suprachoroidal retinal prosthetic device utilizing of 20 stimulating electrodes. Further, we investigate whether using image filtering can improve results on a light localization task for implanted participants compared to minimal vision processing. No controlled implanted participant studies have yet investigated whether vision processing methods that are not task-specific can lead to improved results. Approach. Three participants with profound vision loss from retinitis pigmentosa were implanted with a suprachoroidal retinal prosthesis. All three completed multiple trials of a light localization test, and one participant completed multiple trials of acuity tests. The visual representations used were: Lanczos2 (a high quality Nyquist bandlimited downsampling filter); minimal vision processing (MVP); wide view regional averaging filtering (WV); scrambled; and, system off. Main results. Using Lanczos2, all three participants successfully completed a light localization task and obtained a significantly higher percentage of correct responses than using MVP (p≤slant 0.025) or with system off (p\\lt 0.0001). Further, in a preliminary result using Lanczos2, one participant successfully completed grating acuity and Landolt C tasks, and showed significantly better performance (p=0.004) compared to WV, scrambled and system off on the grating acuity task. Significance. Participants successfully completed vision tasks using a 20 electrode suprachoroidal retinal prosthesis. Vision processing with a Nyquist bandlimited image filter has shown an advantage for a light localization task. This result suggests that this and targeted, more advanced vision processing schemes may become important components of retinal prostheses to enhance performance. ClinicalTrials.gov Identifier: NCT01603576.

AnimalFinder: A semi-automated system for animal detection in time-lapse camera trap images

USGS Publications Warehouse

Price Tack, Jennifer L.; West, Brian S.; McGowan, Conor P.; Ditchkoff, Stephen S.; Reeves, Stanley J.; Keever, Allison; Grand, James B.

2017-01-01

Although the use of camera traps in wildlife management is well established, technologies to automate image processing have been much slower in development, despite their potential to drastically reduce personnel time and cost required to review photos. We developed AnimalFinder in MATLAB® to identify animal presence in time-lapse camera trap images by comparing individual photos to all images contained within the subset of images (i.e. photos from the same survey and site), with some manual processing required to remove false positives and collect other relevant data (species, sex, etc.). We tested AnimalFinder on a set of camera trap images and compared the presence/absence results with manual-only review with white-tailed deer (Odocoileus virginianus), wild pigs (Sus scrofa), and raccoons (Procyon lotor). We compared abundance estimates, model rankings, and coefficient estimates of detection and abundance for white-tailed deer using N-mixture models. AnimalFinder performance varied depending on a threshold value that affects program sensitivity to frequently occurring pixels in a series of images. Higher threshold values led to fewer false negatives (missed deer images) but increased manual processing time, but even at the highest threshold value, the program reduced the images requiring manual review by ~40% and correctly identified >90% of deer, raccoon, and wild pig images. Estimates of white-tailed deer were similar between AnimalFinder and the manual-only method (~1–2 deer difference, depending on the model), as were model rankings and coefficient estimates. Our results show that the program significantly reduced data processing time and may increase efficiency of camera trapping surveys.

A Computer-Aided Diagnosis System for Measuring Carotid Artery Intima-Media Thickness (IMT) Using Quaternion Vectors.

PubMed

Kutbay, Uğurhan; Hardalaç, Fırat; Akbulut, Mehmet; Akaslan, Ünsal; Serhatlıoğlu, Selami

2016-06-01

This study aims investigating adjustable distant fuzzy c-means segmentation on carotid Doppler images, as well as quaternion-based convolution filters and saliency mapping procedures. We developed imaging software that will simplify the measurement of carotid artery intima-media thickness (IMT) on saliency mapping images. Additionally, specialists evaluated the present images and compared them with saliency mapping images. In the present research, we conducted imaging studies of 25 carotid Doppler images obtained by the Department of Cardiology at Fırat University. After implementing fuzzy c-means segmentation and quaternion-based convolution on all Doppler images, we obtained a model that can be analyzed easily by the doctors using a bottom-up saliency model. These methods were applied to 25 carotid Doppler images and then interpreted by specialists. In the present study, we used color-filtering methods to obtain carotid color images. Saliency mapping was performed on the obtained images, and the carotid artery IMT was detected and interpreted on the obtained images from both methods and the raw images are shown in Results. Also these results were investigated by using Mean Square Error (MSE) for the raw IMT images and the method which gives the best performance is the Quaternion Based Saliency Mapping (QBSM). 0,0014 and 0,000191 mm(2) MSEs were obtained for artery lumen diameters and plaque diameters in carotid arteries respectively. We found that computer-based image processing methods used on carotid Doppler could aid doctors' in their decision-making process. We developed software that could ease the process of measuring carotid IMT for cardiologists and help them to evaluate their findings.

Improved cancer diagnostics by different image processing techniques on OCT images

NASA Astrophysics Data System (ADS)

Kanawade, Rajesh; Lengenfelder, Benjamin; Marini Menezes, Tassiana; Hohmann, Martin; Kopfinger, Stefan; Hohmann, Tim; Grabiec, Urszula; Klämpfl, Florian; Gonzales Menezes, Jean; Waldner, Maximilian; Schmidt, Michael

2015-07-01

Optical-coherence tomography (OCT) is a promising non-invasive, high-resolution imaging modality which can be used for cancer diagnosis and its therapeutic assessment. However, speckle noise makes detection of cancer boundaries and image segmentation problematic and unreliable. Therefore, to improve the image analysis for a precise cancer border detection, the performance of different image processing algorithms such as mean, median, hybrid median filter and rotational kernel transformation (RKT) for this task is investigated. This is done on OCT images acquired from an ex-vivo human cancerous mucosa and in vitro by using cultivated tumour applied on organotypical hippocampal slice cultures. The preliminary results confirm that the border between the healthy and the cancer lesions can be identified precisely. The obtained results are verified with fluorescence microscopy. This research can improve cancer diagnosis and the detection of borders between healthy and cancerous tissue. Thus, it could also reduce the number of biopsies required during screening endoscopy by providing better guidance to the physician.

A mobile ferromagnetic shape detection sensor using a Hall sensor array and magnetic imaging.

PubMed

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a mobile Hall sensor array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the mobile Hall sensor array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of mobile Hall sensor array system for actual shape detection. The results prove that the mobile Hall sensor array system is able to perform magnetic imaging in identifying various ferromagnetic materials.

A Mobile Ferromagnetic Shape Detection Sensor Using a Hall Sensor Array and Magnetic Imaging

PubMed Central

Misron, Norhisam; Shin, Ng Wei; Shafie, Suhaidi; Marhaban, Mohd Hamiruce; Mailah, Nashiren Farzilah

2011-01-01

This paper presents a Mobile Hall Sensor Array system for the shape detection of ferromagnetic materials that are embedded in walls or floors. The operation of the Mobile Hall Sensor Array system is based on the principle of magnetic flux leakage to describe the shape of the ferromagnetic material. Two permanent magnets are used to generate the magnetic flux flow. The distribution of magnetic flux is perturbed as the ferromagnetic material is brought near the permanent magnets and the changes in magnetic flux distribution are detected by the 1-D array of the Hall sensor array setup. The process for magnetic imaging of the magnetic flux distribution is done by a signal processing unit before it displays the real time images using a netbook. A signal processing application software is developed for the 1-D Hall sensor array signal acquisition and processing to construct a 2-D array matrix. The processed 1-D Hall sensor array signals are later used to construct the magnetic image of ferromagnetic material based on the voltage signal and the magnetic flux distribution. The experimental results illustrate how the shape of specimens such as square, round and triangle shapes is determined through magnetic images based on the voltage signal and magnetic flux distribution of the specimen. In addition, the magnetic images of actual ferromagnetic objects are also illustrated to prove the functionality of Mobile Hall Sensor Array system for actual shape detection. The results prove that the Mobile Hall Sensor Array system is able to perform magnetic imaging in identifying various ferromagnetic materials. PMID:22346653

Highway 3D model from image and lidar data

NASA Astrophysics Data System (ADS)

Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

2014-05-01

We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

NASA Technical Reports Server (NTRS)

Houchin, Scott; Porter, Brian; Graybill, Justin; Slingerland, Philip

2017-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. This paper describes the software design and implementation of IPATS and provides preliminary test results.

Reducing Speckle In One-Look SAR Images

NASA Technical Reports Server (NTRS)

Nathan, K. S.; Curlander, J. C.

1990-01-01

Local-adaptive-filter algorithm incorporated into digital processing of synthetic-aperture-radar (SAR) echo data to reduce speckle in resulting imagery. Involves use of image statistics in vicinity of each picture element, in conjunction with original intensity of element, to estimate brightness more nearly proportional to true radar reflectance of corresponding target. Increases ratio of signal to speckle noise without substantial degradation of resolution common to multilook SAR images. Adapts to local variations of statistics within scene, preserving subtle details. Computationally simple. Lends itself to parallel processing of different segments of image, making possible increased throughput.

A simplified and powerful image processing methods to separate Thai jasmine rice and sticky rice varieties

NASA Astrophysics Data System (ADS)

Khondok, Piyoros; Sakulkalavek, Aparporn; Suwansukho, Kajpanya

2018-03-01

A simplified and powerful image processing procedures to separate the paddy of KHAW DOK MALI 105 or Thai jasmine rice and the paddy of sticky rice RD6 varieties were proposed. The procedures consist of image thresholding, image chain coding and curve fitting using polynomial function. From the fitting, three parameters of each variety, perimeters, area, and eccentricity, were calculated. Finally, the overall parameters were determined by using principal component analysis. The result shown that these procedures can be significantly separate both varieties.

Research of flaw image collecting and processing technology based on multi-baseline stereo imaging

NASA Astrophysics Data System (ADS)

Yao, Yong; Zhao, Jiguang; Pang, Xiaoyan

2008-03-01

Aiming at the practical situations such as accurate optimal design, complex algorithms and precise technical demands of gun bore flaw image collecting, the design frame of a 3-D image collecting and processing system based on multi-baseline stereo imaging was presented in this paper. This system mainly including computer, electrical control box, stepping motor and CCD camera and it can realize function of image collection, stereo matching, 3-D information reconstruction and after-treatments etc. Proved by theoretical analysis and experiment results, images collected by this system were precise and it can slake efficiently the uncertainty problem produced by universally veins or repeated veins. In the same time, this system has faster measure speed and upper measure precision.

Adaptive marginal median filter for colour images.

PubMed

Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

2011-01-01

This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

Novel Algorithm for Classification of Medical Images

NASA Astrophysics Data System (ADS)

Bhushan, Bharat; Juneja, Monika

2010-11-01

Content-based image retrieval (CBIR) methods in medical image databases have been designed to support specific tasks, such as retrieval of medical images. These methods cannot be transferred to other medical applications since different imaging modalities require different types of processing. To enable content-based queries in diverse collections of medical images, the retrieval system must be familiar with the current Image class prior to the query processing. Further, almost all of them deal with the DICOM imaging format. In this paper a novel algorithm based on energy information obtained from wavelet transform for the classification of medical images according to their modalities is described. For this two types of wavelets have been used and have been shown that energy obtained in either case is quite distinct for each of the body part. This technique can be successfully applied to different image formats. The results are shown for JPEG imaging format.

Classification of Acute Myelogenous Leukemia (AML M2 and AML M3) using Momentum Back Propagation from Watershed Distance Transform Segmented Images

NASA Astrophysics Data System (ADS)

Suryani, Esti; Wiharto; Palgunadi, Sarngadi; Nurcahya Pradana, TP

2017-01-01

This study uses image processing to analyze white blood cell with leukemia indicated that includes the identification, analysis of shapes and sizes, as well as white blood cell count indicated the symptoms of leukemia. A case study in this research was blood cells, from the type of leukemia Acute Myelogenous Leukemia (AML), M2 and M3 in particular. Image processing operations used for segmentation by utilizing the color conversion from RGB (Red, Green dab Blue) to obtain white blood cell candidates. Furthermore, the white blood cells candidates are separated by other cells with active contour without edge. WBC (White Blood Cell) results still have intersected or overlap condition. Watershed distance transform method can separate overlap of WBC. Furthermore, the separation of the nucleus from the cytoplasm using the HSI (Hue Saturation Intensity). The further characteristic extraction process is done by calculating the area WBC, WBC edge, roundness, the ratio of the nucleus, the mean and standard deviation of pixel intensities. The feature extraction results are used for training and testing in determining the classification of AML: M2 and M3 by using the momentum backpropagation algorithm. The classification process is done by testing the numeric data input from the feature extraction results that have been entered in the database. K-Fold validation is used to divide the amount of training data and to test the classification of AML M2 and M3. The experiment results of eight images trials, the result, was 94.285% per cell accuracy and 75% per image accuracy

Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit.

PubMed

Yi, Faliu; Lee, Jieun; Moon, Inkyu

2014-05-01

The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.

High-throughput image analysis of tumor spheroids: a user-friendly software application to measure the size of spheroids automatically and accurately.

PubMed

Chen, Wenjin; Wong, Chung; Vosburgh, Evan; Levine, Arnold J; Foran, David J; Xu, Eugenia Y

2014-07-08

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application - SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary "Manual Initialize" and "Hand Draw" tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.

Image Analysis and Modeling

DTIC Science & Technology

1976-03-01

This report summarizes the results of the research program on Image Analysis and Modeling supported by the Defense Advanced Research Projects Agency...The objective is to achieve a better understanding of image structure and to use this knowledge to develop improved image models for use in image ... analysis and processing tasks such as information extraction, image enhancement and restoration, and coding. The ultimate objective of this research is

The Effects of Visual Degradation on Attended Objects and the Ability to Process Unattended Objects within the Visual Array

DTIC Science & Technology

2010-09-01

field at once (e.g., Biederman , Blickle, Teitelbaum, & Klatsky, 1988), and objects of interest typically receive the attention required to recognize them...field ( Biederman & Cooper, 1991) and image size changes ( Biederman & Cooper, 1992). Yet, only attended objects are recognized when mirror images...left-right reversals) occur ( Biederman & Cooper, 1991). Due to these results, Hummel (2001) proposed that attended images are processed by both

Image processing system performance prediction and product quality evaluation

NASA Technical Reports Server (NTRS)

Stein, E. K.; Hammill, H. B. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

PubMed Central

Lu, Zhaolin

2017-01-01

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. PMID:28298925

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

Rahim, Mohd Shafry Mohd; Saba, Tanzila; Nayer, Fatima; Syed, Afraz Zahra

2014-03-01

Medical image segmentation is a process to extract region of interest and to divide an image into its individual meaningful, homogeneous components. Actually, these components will have a strong relationship with the objects of interest in an image. For computer-aided diagnosis and therapy process, medical image segmentation is an initial mandatory step. Medical image segmentation is a sophisticated and challenging task because of the sophisticated nature of the medical images. Indeed, successful medical image analysis heavily dependent on the segmentation accuracy. Texture is one of the major features to identify region of interests in an image or to classify an object. 2D textures features yields poor classification results. Hence, this paper represents 3D features extraction using texture analysis and SVM as segmentation technique in the testing methodologies.

A back-illuminated megapixel CMOS image sensor

NASA Technical Reports Server (NTRS)

Pain, Bedabrata; Cunningham, Thomas; Nikzad, Shouleh; Hoenk, Michael; Jones, Todd; Wrigley, Chris; Hancock, Bruce

2005-01-01

In this paper, we present the test and characterization results for a back-illuminated megapixel CMOS imager. The imager pixel consists of a standard junction photodiode coupled to a three transistor-per-pixel switched source-follower readout [1]. The imager also consists of integrated timing and control and bias generation circuits, and provides analog output. The analog column-scan circuits were implemented in such a way that the imager could be configured to run in off-chip correlated double-sampling (CDS) mode. The imager was originally designed for normal front-illuminated operation, and was fabricated in a commercially available 0.5 pn triple-metal CMOS-imager compatible process. For backside illumination, the imager was thinned by etching away the substrate was etched away in a post-fabrication processing step.

The Radon cumulative distribution transform and its application to image classification

PubMed Central

Kolouri, Soheil; Park, Se Rim; Rohde, Gustavo K.

2016-01-01

Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g. Fourier, Wavelet, etc.) are linear transforms, and, by themselves, are unable to substantially simplify the representation of image classes for classification. Here we describe a nonlinear, invertible, low-level image processing transform based on combining the well known Radon transform for image data, and the 1D Cumulative Distribution Transform proposed earlier. We describe a few of the properties of this new transform, and with both theoretical and experimental results show that it can often render certain problems linearly separable in transform space. PMID:26685245

A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

PubMed

Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

2014-03-21

This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

Remote Sensing Image Quality Assessment Experiment with Post-Processing

NASA Astrophysics Data System (ADS)

Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.

2018-04-01

This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

Application on-line imagery for photogrammetry comparison of natural hazards events

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Jaboyedoff, Michel; Derron, Marc-Henri

2015-04-01

The airborne (ALS) and terrestrial laser scanner (TLS) technologies are well known and actually one of the most common technics to obtain 3D terrain models. However those technologies are expensive and logistically demanding. Another way to obtain DEM without those inconveniences is photogrammetry, in particular the structure from motion (SfM) technic that allows high quality 3D model extraction from common digital camera images without need of a expensive material. If the usual way to get images for SfM 3D modelling is to take pictures on-site, on-line imagery offer the possibility to get images from many roads and other places. The most common on-line street view resource is Google Street View. Since April 2014, this service proposes a back-in-time function on a certain number of locations. Google Street View images are composed from many pictures taken with a set of panoramic cameras mounted on a platform like a car roof. Those images are affected by strong deformations, which are not recommended for photogrammetry. At first sight, using street view images to make photogrammetry may bring some processing problems. The aim of this project is to study the possibility to made SfM 3D model from Google Street View images with open source processing software (Visual SFM) and low-cost software (Agisoft). The main interest of this method is to evaluate at low cost changes without terrain visit. Study areas are landslides (such those of Séchilienne in France) and cliffs near or far away from roads. Human-made terrain changes like stone wall collapse by high rain precipitations near of Monaco are also studied. For each case, 50 to 200 pictures have been used. The mains conditions to obtain 3D model results are: to have a street view image of the area of interest. Some countries like USA or France are well documented. Other countries like Switzerland are only partially or not at all like Germany. The second constraint is to have two or more sets of images at different time. Third condition is to have enough quality images. Over- or underexposed images, bad meteorological conditions (fog, rain, etc.) or bad images resolution compromise the SfM process. In our case studies, distances from the road to the object of interest range from 1 to 500 m. First results show that SfM processing with on-line images is not obvious. Poor-resolution and deformed images with unknown camera features make the process often difficult and not predictive. The use of Agisoft software give bad results because of the abovementioned features while Visual SFM give interesting results for about two thirds of cases. It is also demonstrated that 3D photogrammetry is possible with on-line images under certain restrictive conditions. Under these conditions of images quality, this technique can then be used to estimate volumes changes.

Concrete Slump Classification using GLCM Feature Extraction

NASA Astrophysics Data System (ADS)

Andayani, Relly; Madenda, Syarifudin

2016-05-01

Digital image processing technologies have been widely applies in analyzing concrete structure because the accuracy and real time result. The aim of this study is to classify concrete slump by using image processing technique. For this purpose, concrete mix design of 30 MPa compression strength designed with slump of 0-10 mm, 10-30 mm, 30-60 mm, and 60-180 mm were analysed. Image acquired by Nikon Camera D-7000 using high resolution was set up. In the first step RGB converted to greyimage than cropped to 1024 x 1024 pixel. With open-source program, cropped images to be analysed to extract GLCM feature. The result shows for the higher slump contrast getting lower, but higher correlation, energy, and homogeneity.

Image Processing Strategies Based on a Visual Saliency Model for Object Recognition Under Simulated Prosthetic Vision.

PubMed

Wang, Jing; Li, Heng; Fu, Weizhen; Chen, Yao; Li, Liming; Lyu, Qing; Han, Tingting; Chai, Xinyu

2016-01-01

Retinal prostheses have the potential to restore partial vision. Object recognition in scenes of daily life is one of the essential tasks for implant wearers. Still limited by the low-resolution visual percepts provided by retinal prostheses, it is important to investigate and apply image processing methods to convey more useful visual information to the wearers. We proposed two image processing strategies based on Itti's visual saliency map, region of interest (ROI) extraction, and image segmentation. Itti's saliency model generated a saliency map from the original image, in which salient regions were grouped into ROI by the fuzzy c-means clustering. Then Grabcut generated a proto-object from the ROI labeled image which was recombined with background and enhanced in two ways--8-4 separated pixelization (8-4 SP) and background edge extraction (BEE). Results showed that both 8-4 SP and BEE had significantly higher recognition accuracy in comparison with direct pixelization (DP). Each saliency-based image processing strategy was subject to the performance of image segmentation. Under good and perfect segmentation conditions, BEE and 8-4 SP obtained noticeably higher recognition accuracy than DP, and under bad segmentation condition, only BEE boosted the performance. The application of saliency-based image processing strategies was verified to be beneficial to object recognition in daily scenes under simulated prosthetic vision. They are hoped to help the development of the image processing module for future retinal prostheses, and thus provide more benefit for the patients. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

VIP: Vortex Image Processing Package for High-contrast Direct Imaging

NASA Astrophysics Data System (ADS)

Gomez Gonzalez, Carlos Alberto; Wertz, Olivier; Absil, Olivier; Christiaens, Valentin; Defrère, Denis; Mawet, Dimitri; Milli, Julien; Absil, Pierre-Antoine; Van Droogenbroeck, Marc; Cantalloube, Faustine; Hinz, Philip M.; Skemer, Andrew J.; Karlsson, Mikael; Surdej, Jean

2017-07-01

We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source position and flux estimation, and sensitivity curve generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at http://github.com/vortex-exoplanet/VIP and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

Client-side Medical Image Colorization in a Collaborative Environment.

PubMed

Virag, Ioan; Stoicu-Tivadar, Lăcrămioara; Crişan-Vida, Mihaela

2015-01-01

The paper presents an application related to collaborative medicine using a browser based medical visualization system with focus on the medical image colorization process and the underlying open source web development technologies involved. Browser based systems allow physicians to share medical data with their remotely located counterparts or medical students, assisting them during patient diagnosis, treatment monitoring, surgery planning or for educational purposes. This approach brings forth the advantage of ubiquity. The system can be accessed from a any device, in order to process the images, assuring the independence towards having a specific proprietary operating system. The current work starts with processing of DICOM (Digital Imaging and Communications in Medicine) files and ends with the rendering of the resulting bitmap images on a HTML5 (fifth revision of the HyperText Markup Language) canvas element. The application improves the image visualization emphasizing different tissue densities.

Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

PubMed Central

Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

2015-01-01

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

Geocoding uncertainty analysis for the automated processing of Sentinel-1 data using Sentinel-1 Toolbox software

NASA Astrophysics Data System (ADS)

Dostálová, Alena; Naeimi, Vahid; Wagner, Wolfgang; Elefante, Stefano; Cao, Senmao; Persson, Henrik

2016-10-01

One of the major advantages of the Sentinel-1 data is its capability to provide very high spatio-temporal coverage allowing the mapping of large areas as well as creation of dense time-series of the Sentinel-1 acquisitions. The SGRT software developed at TU Wien aims at automated processing of Sentinel-1 data for global and regional products. The first step of the processing consists of the Sentinel-1 data geocoding with the help of S1TBX software and their resampling to a common grid. These resampled images serve as an input for the product derivation. Thus, it is very important to select the most reliable processing settings and assess the geocoding uncertainty for both backscatter and projected local incidence angle images. Within this study, selection of Sentinel-1 acquisitions over 3 test areas in Europe were processed manually in the S1TBX software, testing multiple software versions, processing settings and digital elevation models (DEM) and the accuracy of the resulting geocoded images were assessed. Secondly, all available Sentinel-1 data over the areas were processed using selected settings and detailed quality check was performed. Overall, strong influence of the used DEM on the geocoding quality was confirmed with differences up to 80 meters in areas with higher terrain variations. In flat areas, the geocoding accuracy of backscatter images was overall good, with observed shifts between 0 and 30m. Larger systematic shifts were identified in case of projected local incidence angle images. These results encourage the automated processing of large volumes of Sentinel-1 data.

Automatic detection of blurred images in UAV image sets

NASA Astrophysics Data System (ADS)

Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

2016-12-01

Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur. Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of additional images. However, the calculated blur value named SIEDS (saturation image edge difference standard-deviation) on its own does not provide an absolute number to judge if an image is blurred or not. To achieve a reliable judgement of image sharpness the SIEDS value has to be compared to other SIEDS values from the same dataset. The speed and reliability of the method was tested using a range of different UAV datasets. Two datasets will be presented in this paper to demonstrate the effectiveness of the algorithm. The algorithm proves to be fast and the returned values are optically correct, making the algorithm applicable for UAV datasets. Additionally, a close range dataset was processed to determine whether the method is also useful for close range applications. The results show that the method is also reliable for close range images, which significantly extends the field of application for the algorithm.

Combined Acquisition/Processing For Data Reduction

NASA Astrophysics Data System (ADS)

Kruger, Robert A.

1982-01-01

Digital image processing systems necessarily consist of three components: acquisition, storage/retrieval and processing. The acquisition component requires the greatest data handling rates. By coupling together the acquisition witn some online hardwired processing, data rates and capacities for short term storage can be reduced. Furthermore, long term storage requirements can be reduced further by appropriate processing and editing of image data contained in short term memory. The net result could be reduced performance requirements for mass storage, processing and communication systems. Reduced amounts of data also snouid speed later data analysis and diagnostic decision making.

Multifocus watermarking approach based on discrete cosine transform.

PubMed

Waheed, Safa Riyadh; Alkawaz, Mohammed Hazim; Rehman, Amjad; Almazyad, Abdulaziz S; Saba, Tanzila

2016-05-01

Image fusion process consolidates data and information from various images of same sight into a solitary image. Each of the source images might speak to a fractional perspective of the scene, and contains both "pertinent" and "immaterial" information. In this study, a new image fusion method is proposed utilizing the Discrete Cosine Transform (DCT) to join the source image into a solitary minimized image containing more exact depiction of the sight than any of the individual source images. In addition, the fused image comes out with most ideal quality image without bending appearance or loss of data. DCT algorithm is considered efficient in image fusion. The proposed scheme is performed in five steps: (1) RGB colour image (input image) is split into three channels R, G, and B for source images. (2) DCT algorithm is applied to each channel (R, G, and B). (3) The variance values are computed for the corresponding 8 × 8 blocks of each channel. (4) Each block of R of source images is compared with each other based on the variance value and then the block with maximum variance value is selected to be the block in the new image. This process is repeated for all channels of source images. (5) Inverse discrete cosine transform is applied on each fused channel to convert coefficient values to pixel values, and then combined all the channels to generate the fused image. The proposed technique can potentially solve the problem of unwanted side effects such as blurring or blocking artifacts by reducing the quality of the subsequent image in image fusion process. The proposed approach is evaluated using three measurement units: the average of Q(abf), standard deviation, and peak Signal Noise Rate. The experimental results of this proposed technique have shown good results as compared with older techniques. © 2016 Wiley Periodicals, Inc.

Imaging systems and algorithms to analyze biological samples in real-time using mobile phone microscopy.

PubMed

Shanmugam, Akshaya; Usmani, Mohammad; Mayberry, Addison; Perkins, David L; Holcomb, Daniel E

2018-01-01

Miniaturized imaging devices have pushed the boundaries of point-of-care imaging, but existing mobile-phone-based imaging systems do not exploit the full potential of smart phones. This work demonstrates the use of simple imaging configurations to deliver superior image quality and the ability to handle a wide range of biological samples. Results presented in this work are from analysis of fluorescent beads under fluorescence imaging, as well as helminth eggs and freshwater mussel larvae under white light imaging. To demonstrate versatility of the systems, real time analysis and post-processing results of the sample count and sample size are presented in both still images and videos of flowing samples.

Nonlinear coherent optical image processing using logarithmic transmittance of bacteriorhodopsin films

NASA Astrophysics Data System (ADS)

Downie, John D.

1995-08-01

The transmission properties of some bacteriorhodopsin-film spatial light modulators are uniquely suited to allow nonlinear optical image-processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude-transmission characteristic of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. I present experimental results demonstrating the principle and the capability for several different image and noise situations, including deterministic noise and speckle. The bacteriorhodopsin film studied here displays the logarithmic transmission response for write intensities spanning a dynamic range greater than 2 orders of magnitude.

Nonlinear Coherent Optical Image Processing Using Logarithmic Transmittance of Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

The transmission properties of some bacteriorhodopsin-film spatial light modulators are uniquely suited to allow nonlinear optical image-processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude-transmission characteristic of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. I present experimental results demonstrating the principle and the capability for several different image and noise situations, including deterministic noise and speckle. The bacteriorhodopsin film studied here displays the logarithmic transmission response for write intensities spanning a dynamic range greater than 2 orders of magnitude.

An architecture for a brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.

2000-01-01

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Image fusion via nonlocal sparse K-SVD dictionary learning.

PubMed

Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang

2016-03-01

Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.

Classifying magnetic resonance image modalities with convolutional neural networks

NASA Astrophysics Data System (ADS)

Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

2018-02-01

Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

Single-Scale Fusion: An Effective Approach to Merging Images.

PubMed

Ancuti, Codruta O; Ancuti, Cosmin; De Vleeschouwer, Christophe; Bovik, Alan C

2017-01-01

Due to its robustness and effectiveness, multi-scale fusion (MSF) based on the Laplacian pyramid decomposition has emerged as a popular technique that has shown utility in many applications. Guided by several intuitive measures (weight maps) the MSF process is versatile and straightforward to be implemented. However, the number of pyramid levels increases with the image size, which implies sophisticated data management and memory accesses, as well as additional computations. Here, we introduce a simplified formulation that reduces MSF to only a single level process. Starting from the MSF decomposition, we explain both mathematically and intuitively (visually) a way to simplify the classical MSF approach with minimal loss of information. The resulting single-scale fusion (SSF) solution is a close approximation of the MSF process that eliminates important redundant computations. It also provides insights regarding why MSF is so effective. While our simplified expression is derived in the context of high dynamic range imaging, we show its generality on several well-known fusion-based applications, such as image compositing, extended depth of field, medical imaging, and blending thermal (infrared) images with visible light. Besides visual validation, quantitative evaluations demonstrate that our SSF strategy is able to yield results that are highly competitive with traditional MSF approaches.

Muscle segmentation in time series images of Drosophila metamorphosis.

PubMed

Yadav, Kuleesha; Lin, Feng; Wasser, Martin

2015-01-01

In order to study genes associated with muscular disorders, we characterize the phenotypic changes in Drosophila muscle cells during metamorphosis caused by genetic perturbations. We collect in vivo images of muscle fibers during remodeling of larval to adult muscles. In this paper, we focus on the new image processing pipeline designed to quantify the changes in shape and size of muscles. We propose a new two-step approach to muscle segmentation in time series images. First, we implement a watershed algorithm to divide the image into edge-preserving regions, and then, we classify these regions into muscle and non-muscle classes on the basis of shape and intensity. The advantage of our method is two-fold: First, better results are obtained because classification of regions is constrained by the shape of muscle cell from previous time point; and secondly, minimal user intervention results in faster processing time. The segmentation results are used to compare the changes in cell size between controls and reduction of the autophagy related gene Atg 9 during Drosophila metamorphosis.

Techniques of Photometry and Astrometry with APASS, Gaia, and Pan-STARRs Results (Abstract)

NASA Astrophysics Data System (ADS)

Green, W.

2017-12-01

(Abstract only) The databases with the APASS DR9, Gaia DR1, and the Pan-STARRs 3pi DR1 data releases are publicly available for use. There is a bit of data-mining involved to download and manage these reference stars. This paper discusses the use of these databases to acquire accurate photometric references as well as techniques for improving results. Images are prepared in the usual way: zero, dark, flat-fields, and WCS solutions with Astrometry.net. Images are then processed with Sextractor to produce an ASCII table of identifying photometric features. The database manages photometics catalogs and images converted to ASCII tables. Scripts convert the files into SQL and assimilate them into database tables. Using SQL techniques, each image star is merged with reference data to produce publishable results. The VYSOS has over 13,000 images of the ONC5 field to process with roughly 100 total fields in the campaign. This paper provides the overview for this daunting task.

Establishment of Imaging Spectroscopy of Nuclear Gamma-Rays based on Geometrical Optics

PubMed Central

Tanimori, Toru; Mizumura, Yoshitaka; Takada, Atsushi; Miyamoto, Shohei; Takemura, Taito; Kishimoto, Tetsuro; Komura, Shotaro; Kubo, Hidetoshi; Kurosawa, Shunsuke; Matsuoka, Yoshihiro; Miuchi, Kentaro; Mizumoto, Tetsuya; Nakamasu, Yuma; Nakamura, Kiseki; Parker, Joseph D.; Sawano, Tatsuya; Sonoda, Shinya; Tomono, Dai; Yoshikawa, Kei

2017-01-01

Since the discovery of nuclear gamma-rays, its imaging has been limited to pseudo imaging, such as Compton Camera (CC) and coded mask. Pseudo imaging does not keep physical information (intensity, or brightness in Optics) along a ray, and thus is capable of no more than qualitative imaging of bright objects. To attain quantitative imaging, cameras that realize geometrical optics is essential, which would be, for nuclear MeV gammas, only possible via complete reconstruction of the Compton process. Recently we have revealed that “Electron Tracking Compton Camera” (ETCC) provides a well-defined Point Spread Function (PSF). The information of an incoming gamma is kept along a ray with the PSF and that is equivalent to geometrical optics. Here we present an imaging-spectroscopic measurement with the ETCC. Our results highlight the intrinsic difficulty with CCs in performing accurate imaging, and show that the ETCC surmounts this problem. The imaging capability also helps the ETCC suppress the noise level dramatically by ~3 orders of magnitude without a shielding structure. Furthermore, full reconstruction of Compton process with the ETCC provides spectra free of Compton edges. These results mark the first proper imaging of nuclear gammas based on the genuine geometrical optics. PMID:28155870

Establishment of Imaging Spectroscopy of Nuclear Gamma-Rays based on Geometrical Optics.

PubMed

Tanimori, Toru; Mizumura, Yoshitaka; Takada, Atsushi; Miyamoto, Shohei; Takemura, Taito; Kishimoto, Tetsuro; Komura, Shotaro; Kubo, Hidetoshi; Kurosawa, Shunsuke; Matsuoka, Yoshihiro; Miuchi, Kentaro; Mizumoto, Tetsuya; Nakamasu, Yuma; Nakamura, Kiseki; Parker, Joseph D; Sawano, Tatsuya; Sonoda, Shinya; Tomono, Dai; Yoshikawa, Kei

2017-02-03

Since the discovery of nuclear gamma-rays, its imaging has been limited to pseudo imaging, such as Compton Camera (CC) and coded mask. Pseudo imaging does not keep physical information (intensity, or brightness in Optics) along a ray, and thus is capable of no more than qualitative imaging of bright objects. To attain quantitative imaging, cameras that realize geometrical optics is essential, which would be, for nuclear MeV gammas, only possible via complete reconstruction of the Compton process. Recently we have revealed that "Electron Tracking Compton Camera" (ETCC) provides a well-defined Point Spread Function (PSF). The information of an incoming gamma is kept along a ray with the PSF and that is equivalent to geometrical optics. Here we present an imaging-spectroscopic measurement with the ETCC. Our results highlight the intrinsic difficulty with CCs in performing accurate imaging, and show that the ETCC surmounts this problem. The imaging capability also helps the ETCC suppress the noise level dramatically by ~3 orders of magnitude without a shielding structure. Furthermore, full reconstruction of Compton process with the ETCC provides spectra free of Compton edges. These results mark the first proper imaging of nuclear gammas based on the genuine geometrical optics.

On the assessment of visual communication by information theory

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Fales, Carl L.

1993-01-01

This assessment of visual communication integrates the optical design of the image-gathering device with the digital processing for image coding and restoration. Results show that informationally optimized image gathering ordinarily can be relied upon to maximize the information efficiency of decorrelated data and the visual quality of optimally restored images.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

IMAGE 100: The interactive multispectral image processing system

NASA Technical Reports Server (NTRS)

Schaller, E. S.; Towles, R. W.

1975-01-01

The need for rapid, cost-effective extraction of useful information from vast quantities of multispectral imagery available from aircraft or spacecraft has resulted in the design, implementation and application of a state-of-the-art processing system known as IMAGE 100. Operating on the general principle that all objects or materials possess unique spectral characteristics or signatures, the system uses this signature uniqueness to identify similar features in an image by simultaneously analyzing signatures in multiple frequency bands. Pseudo-colors, or themes, are assigned to features having identical spectral characteristics. These themes are displayed on a color CRT, and may be recorded on tape, film, or other media. The system was designed to incorporate key features such as interactive operation, user-oriented displays and controls, and rapid-response machine processing. Owing to these features, the user can readily control and/or modify the analysis process based on his knowledge of the input imagery. Effective use can be made of conventional photographic interpretation skills and state-of-the-art machine analysis techniques in the extraction of useful information from multispectral imagery. This approach results in highly accurate multitheme classification of imagery in seconds or minutes rather than the hours often involved in processing using other means.

Lipase production in solid-state fermentation monitoring biomass growth of aspergillus niger using digital image processing.

PubMed

Dutra, Júlio C V; da C Terzi, Selma; Bevilaqua, Juliana Vaz; Damaso, Mônica C T; Couri, Sônia; Langone, Marta A P; Senna, Lilian F

2008-03-01

The aim of this study was to monitor the biomass growth of Aspergillus niger in solid-state fermentation (SSF) for lipase production using digital image processing technique. The strain A. niger 11T53A14 was cultivated in SSF using wheat bran as support, which was enriched with 0.91% (m/v) of ammonium sulfate. The addition of several vegetable oils (castor, soybean, olive, corn, and palm oils) was investigated to enhance lipase production. The maximum lipase activity was obtained using 2% (m/m) castor oil. In these conditions, the growth was evaluated each 24 h for 5 days by the glycosamine content analysis and digital image processing. Lipase activity was also determined. The results indicated that the digital image process technique can be used to monitor biomass growth in a SSF process and to correlate biomass growth and enzyme activity. In addition, the immobilized esterification lipase activity was determined for the butyl oleate synthesis, with and without 50% v/v hexane, resulting in 650 and 120 U/g, respectively. The enzyme was also used for transesterification of soybean oil and ethanol with maximum yield of 2.4%, after 30 min of reaction.

Exploiting range imagery: techniques and applications

NASA Astrophysics Data System (ADS)

Armbruster, Walter

2009-07-01

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.

Lipase Production in Solid-State Fermentation Monitoring Biomass Growth of Aspergillus niger Using Digital Image Processing

NASA Astrophysics Data System (ADS)

Dutra, Julio C. V.; da Terzi, Selma C.; Bevilaqua, Juliana Vaz; Damaso, Mônica C. T.; Couri, Sônia; Langone, Marta A. P.; Senna, Lilian F.

The aim of this study was to monitor the biomass growth of Aspergillus niger in solid-state fermentation (SSF) for lipase production using digital image processing technique. The strain A. niger 11T53A14 was cultivated in SSF using wheat bran as support, which was enriched with 0.91% (m/v) of ammonium sulfate. The addition of several vegetable oils (castor, soybean, olive, corn, and palm oils) was investigated to enhance lipase production. The maximum lipase activity was obtained using 2% (m/m) castor oil. In these conditions, the growth was evaluated each 24 h for 5 days by the glycosamine content analysis and digital image processing. Lipase activity was also determined. The results indicated that the digital image process technique can be used to monitor biomass growth in a SSF process and to correlate biomass growth and enzyme activity. In addition, the immobilized esterification lipase activity was determined for the butyl oleate synthesis, with and without 50% v/v hexane, resulting in 650 and 120 U/g, respectively. The enzyme was also used for transesterification of soybean oil and ethanol with maximum yield of 2.4%, after 30 min of reaction.

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

2017-03-01

The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

High speed imaging of dynamic processes with a switched source x-ray CT system

NASA Astrophysics Data System (ADS)

Thompson, William M.; Lionheart, William R. B.; Morton, Edward J.; Cunningham, Mike; Luggar, Russell D.

2015-05-01

Conventional x-ray computed tomography (CT) scanners are limited in their scanning speed by the mechanical constraints of their rotating gantries and as such do not provide the necessary temporal resolution for imaging of fast-moving dynamic processes, such as moving fluid flows. The Real Time Tomography (RTT) system is a family of fast cone beam CT scanners which instead use multiple fixed discrete sources and complete rings of detectors in an offset geometry. We demonstrate the potential of this system for use in the imaging of such high speed dynamic processes and give results using simulated and real experimental data. The unusual scanning geometry results in some challenges in image reconstruction, which are overcome using algebraic iterative reconstruction techniques and explicit regularisation. Through the use of a simple temporal regularisation term and by optimising the source firing pattern, we show that temporal resolution of the system may be increased at the expense of spatial resolution, which may be advantageous in some situations. Results are given showing temporal resolution of approximately 500 µs with simulated data and 3 ms with real experimental data.

Automatic x-ray image contrast enhancement based on parameter auto-optimization.

PubMed

Qiu, Jianfeng; Harold Li, H; Zhang, Tiezhi; Ma, Fangfang; Yang, Deshan

2017-11-01

Insufficient image contrast associated with radiation therapy daily setup x-ray images could negatively affect accurate patient treatment setup. We developed a method to perform automatic and user-independent contrast enhancement on 2D kilo voltage (kV) and megavoltage (MV) x-ray images. The goal was to provide tissue contrast optimized for each treatment site in order to support accurate patient daily treatment setup and the subsequent offline review. The proposed method processes the 2D x-ray images with an optimized image processing filter chain, which consists of a noise reduction filter and a high-pass filter followed by a contrast limited adaptive histogram equalization (CLAHE) filter. The most important innovation is to optimize the image processing parameters automatically to determine the required image contrast settings per disease site and imaging modality. Three major parameters controlling the image processing chain, i.e., the Gaussian smoothing weighting factor for the high-pass filter, the block size, and the clip limiting parameter for the CLAHE filter, were determined automatically using an interior-point constrained optimization algorithm. Fifty-two kV and MV x-ray images were included in this study. The results were manually evaluated and ranked with scores from 1 (worst, unacceptable) to 5 (significantly better than adequate and visually praise worthy) by physicians and physicists. The average scores for the images processed by the proposed method, the CLAHE, and the best window-level adjustment were 3.92, 2.83, and 2.27, respectively. The percentage of the processed images received a score of 5 were 48, 29, and 18%, respectively. The proposed method is able to outperform the standard image contrast adjustment procedures that are currently used in the commercial clinical systems. When the proposed method is implemented in the clinical systems as an automatic image processing filter, it could be useful for allowing quicker and potentially more accurate treatment setup and facilitating the subsequent offline review and verification. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

[Research on spatially modulated Fourier transform imaging spectrometer data processing method].

PubMed

Huang, Min; Xiangli, Bin; Lü, Qun-Bo; Zhou, Jin-Song; Jing, Juan-Juan; Cui, Yan

2010-03-01

Fourier transform imaging spectrometer is a new technic, and has been developed very rapidly in nearly ten years. The data catched by Fourier transform imaging spectrometer is indirect data, can not be used by user, and need to be processed by various approaches, including data pretreatment, apodization, phase correction, FFT, and spectral radicalization calibration. No paper so far has been found roundly to introduce this method. In the present paper, the author will give an effective method to process the interfering data to spectral data, and with this method we can obtain good result.

High-resolution imaging of the supercritical antisolvent process

NASA Astrophysics Data System (ADS)

Bell, Philip W.; Stephens, Amendi P.; Roberts, Christopher B.; Duke, Steve R.

2005-06-01

A high-magnification and high-resolution imaging technique was developed for the supercritical fluid antisolvent (SAS) precipitation process. Visualizations of the jet injection, flow patterns, droplets, and particles were obtained in a high-pressure vessel for polylactic acid and budesonide precipitation in supercritical CO2. The results show two regimes for particle production: one where turbulent mixing occurs in gas-like plumes, and another where distinct droplets were observed in the injection. Images are presented to demonstrate the capabilities of the method for examining particle formation theories and for understanding the underlying fluid mechanics, thermodynamics, and mass transport in the SAS process.

Managing Institutional Image.

ERIC Educational Resources Information Center

Melchiori, Gerlinda S.

1990-01-01

A managerial process for enhancing the image and public reputation of a higher education institution is outlined. It consists of five stages: market research; data analysis and market positioning; communication of results and recommendations to the administration; development of a global image program; and impact evaluation. (MSE)

Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

PubMed

Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

2012-01-01

Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. Copyright © 2011 Elsevier Ltd. All rights reserved.

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

The possibilities of improvement in the sensitivity of cancer fluorescence diagnostics by computer image processing

NASA Astrophysics Data System (ADS)

Ledwon, Aleksandra; Bieda, Robert; Kawczyk-Krupka, Aleksandra; Polanski, Andrzej; Wojciechowski, Konrad; Latos, Wojciech; Sieron-Stoltny, Karolina; Sieron, Aleksander

2008-02-01

Background: Fluorescence diagnostics uses the ability of tissues to fluoresce after exposition to a specific wavelength of light. The change in fluorescence between normal and progression to cancer allows to see early cancer and precancerous lesions often missed by white light. Aim: To improve by computer image processing the sensitivity of fluorescence images obtained during examination of skin, oral cavity, vulva and cervix lesions, during endoscopy, cystoscopy and bronchoscopy using Xillix ONCOLIFE. Methods: Function of image f(x,y):R2 --> R 3 was transformed from original color space RGB to space in which vector of 46 values refers to every point labeled by defined xy-coordinates- f(x,y):R2 --> R 46. By means of Fisher discriminator vector of attributes of concrete point analalyzed in the image was reduced according to two defined classes defined as pathologic areas (foreground) and healthy areas (background). As a result the highest four fisher's coefficients allowing the greatest separation between points of pathologic (foreground) and healthy (background) areas were chosen. In this way new function f(x,y):R2 --> R 4 was created in which point x,y corresponds with vector Y, H, a*, c II. In the second step using Gaussian Mixtures and Expectation-Maximisation appropriate classificator was constructed. This classificator enables determination of probability that the selected pixel of analyzed image is a pathologically changed point (foreground) or healthy one (background). Obtained map of probability distribution was presented by means of pseudocolors. Results: Image processing techniques improve the sensitivity, quality and sharpness of original fluorescence images. Conclusion: Computer image processing enables better visualization of suspected areas examined by means of fluorescence diagnostics.

Robust feature estimation by non-rigid hierarchical image registration and its application in disparity measurement

NASA Astrophysics Data System (ADS)

Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan

2017-03-01

Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.

Processing digital images and calculation of beam emittance (pepper-pot method for the Krion source)

NASA Astrophysics Data System (ADS)

Alexandrov, V. S.; Donets, E. E.; Nyukhalova, E. V.; Kaminsky, A. K.; Sedykh, S. N.; Tuzikov, A. V.; Philippov, A. V.

2016-12-01

Programs for the pre-processing of photographs of beam images on the mask based on Wolfram Mathematica and Origin software are described. Angles of rotation around the axis and in the vertical plane are taken into account in the generation of the file with image coordinates. Results of the emittance calculation by the Pep_emit program written in Visual Basic using the generated file in the test mode are presented.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Hoenk, Michael; Monacos, Steve; Nikzad, Shouleh

2009-01-01

Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151.

PubMed

Jones, A Kyle; Heintz, Philip; Geiser, William; Goldman, Lee; Jerjian, Khachig; Martin, Melissa; Peck, Donald; Pfeiffer, Douglas; Ranger, Nicole; Yorkston, John

2015-11-01

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist is responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

PubMed Central

Huang, Xiwei; Jiang, Yu; Liu, Xu; Xu, Hang; Han, Zhi; Rong, Hailong; Yang, Haiping; Yan, Mei; Yu, Hao

2016-01-01

A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR) processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR) and Convolutional Neural Network based SR (CNNSR). Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications. PMID:27827837

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, A. Kyle, E-mail: kyle.jones@mdanderson.org; Geiser, William; Heintz, Philip

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist ismore » responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.« less

Content-based quality evaluation of color images: overview and proposals

NASA Astrophysics Data System (ADS)

Tremeau, Alain; Richard, Noel; Colantoni, Philippe; Fernandez-Maloigne, Christine

2003-12-01

The automatic prediction of perceived quality from image data in general, and the assessment of particular image characteristics or attributes that may need improvement in particular, becomes an increasingly important part of intelligent imaging systems. The purpose of this paper is to propose to the color imaging community in general to develop a software package available on internet to help the user to select among all these approaches which is better appropriated to a given application. The ultimate goal of this project is to propose, next to implement, an open and unified color imaging system to set up a favourable context for the evaluation and analysis of color imaging processes. Many different methods for measuring the performance of a process have been proposed by different researchers. In this paper, we will discuss the advantages and shortcomings of most of main analysis criteria and performance measures currently used. The aim is not to establish a harsh competition between algorithms or processes, but rather to test and compare the efficiency of methodologies firstly to highlight strengths and weaknesses of a given algorithm or methodology on a given image type and secondly to have these results publicly available. This paper is focused on two important unsolved problems. Why it is so difficult to select a color space which gives better results than another one? Why it is so difficult to select an image quality metric which gives better results than another one, with respect to the judgment of the Human Visual System? Several methods used either in color imaging or in image quality will be thus discussed. Proposals for content-based image measures and means of developing a standard test suite for will be then presented. The above reference advocates for an evaluation protocol based on an automated procedure. This is the ultimate goal of our proposal.

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

Do High Dynamic Range threatments improve the results of Structure from Motion approaches in Geomorphology?

NASA Astrophysics Data System (ADS)

Gómez-Gutiérrez, Álvaro; Juan de Sanjosé-Blasco, José; Schnabel, Susanne; de Matías-Bejarano, Javier; Pulido-Fernández, Manuel; Berenguer-Sempere, Fernando

2015-04-01

In this work, the hypothesis of improving 3D models obtained with Structure from Motion (SfM) approaches using images pre-processed by High Dynamic Range (HDR) techniques is tested. Photographs of the Veleta Rock Glacier in Spain were captured with different exposure values (EV0, EV+1 and EV-1), two focal lengths (35 and 100 mm) and under different weather conditions for the years 2008, 2009, 2011, 2012 and 2014. HDR images were produced using the different EV steps within Fusion F.1 software. Point clouds were generated using commercial and free available SfM software: Agisoft Photoscan and 123D Catch. Models Obtained using pre-processed images and non-preprocessed images were compared in a 3D environment with a benchmark 3D model obtained by means of a Terrestrial Laser Scanner (TLS). A total of 40 point clouds were produced, georeferenced and compared. Results indicated that for Agisoft Photoscan software differences in the accuracy between models obtained with pre-processed and non-preprocessed images were not significant from a statistical viewpoint. However, in the case of the free available software 123D Catch, models obtained using images pre-processed by HDR techniques presented a higher point density and were more accurate. This tendency was observed along the 5 studied years and under different capture conditions. More work should be done in the near future to corroborate whether the results of similar software packages can be improved by HDR techniques (e.g. ARC3D, Bundler and PMVS2, CMP SfM, Photosynth and VisualSFM).

Real-time processing of interferograms for monitoring protein crystal growth on the Space Station

NASA Technical Reports Server (NTRS)

Choudry, A.; Dupuis, N.

1988-01-01

The possibility of using microscopic interferometric techniques to monitor the growth of protein crystals on the Space Station is studied. Digital image processing techniques are used to develop a system for the real-time analysis of microscopic interferograms of nucleation sites during protein crystal growth. Features of the optical setup and the image processing system are discussed and experimental results are presented.

Image segmentation by iterative parallel region growing with application to data compression and image analysis

NASA Technical Reports Server (NTRS)

Tilton, James C.

1988-01-01

Image segmentation can be a key step in data compression and image analysis. However, the segmentation results produced by most previous approaches to region growing are suspect because they depend on the order in which portions of the image are processed. An iterative parallel segmentation algorithm avoids this problem by performing globally best merges first. Such a segmentation approach, and two implementations of the approach on NASA's Massively Parallel Processor (MPP) are described. Application of the segmentation approach to data compression and image analysis is then described, and results of such application are given for a LANDSAT Thematic Mapper image.

Development of real-time extensometer based on image processing

NASA Astrophysics Data System (ADS)

Adinanta, H.; Puranto, P.; Suryadi

2017-04-01

An extensometer system was developed by using high definition web camera as main sensor to track object position. The developed system applied digital image processing techniques. The image processing was used to measure the change of object position. The position measurement was done in real-time so that the system can directly showed the actual position in both x and y-axis. In this research, the relation between pixel and object position changes had been characterized. The system was tested by moving the target in a range of 20 cm in interval of 1 mm. To verify the long run performance, the stability and linearity of continuous measurements on both x and y-axis, this measurement had been conducted for 83 hours. The results show that this image processing-based extensometer had both good stability and linearity.

Fault detection and isolation in the challenging Tennessee Eastman process by using image processing techniques.

PubMed

Hajihosseini, Payman; Anzehaee, Mohammad Mousavi; Behnam, Behzad

2018-05-22

The early fault detection and isolation in industrial systems is a critical factor in preventing equipment damage. In the proposed method, instead of using the time signals of sensors, the 2D image obtained by placing these signals next to each other in a matrix has been used; and then a novel fault detection and isolation procedure has been carried out based on image processing techniques. Different features including texture, wavelet transform, mean and standard deviation of the image accompanied with MLP and RBF neural networks based classifiers have been used for this purpose. Obtained results indicate the notable efficacy and success of the proposed method in detecting and isolating faults of the Tennessee Eastman benchmark process and its superiority over previous techniques. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A platform for European CMOS image sensors for space applications

NASA Astrophysics Data System (ADS)

Minoglou, K.; San Segundo Bello, D.; Sabuncuoglu Tezcan, D.; Haspeslagh, L.; Van Olmen, J.; Merry, B.; Cavaco, C.; Mazzamuto, F.; Toqué-Trésonne, I.; Moirin, R.; Brouwer, M.; Toccafondi, M.; Preti, G.; Rosmeulen, M.; De Moor, P.

2017-11-01

Both ESA and the EC have identified the need for a supply chain of CMOS imagers for space applications which uses solely European sources. An essential requirement on this supply chain is the platformization of the process modules, in particular when it comes to very specific processing steps, such as those required for the manufacturing of backside illuminated image sensors. This is the goal of the European (EC/FP7/SPACE) funded project EUROCIS. All EUROCIS partners have excellent know-how and track record in the expertise fields required. Imec has been leading the imager chip design and the front side and backside processing. LASSE, as a major player in the laser annealing supplier sector, has been focusing on the optimization of the process related to the backside passivation of the image sensors. TNO, known worldwide as a top developer of instruments for scientific research, including space research and sensors for satellites, has contributed in the domain of optical layers for space instruments and optimized antireflective coatings. Finally, Selex ES, as a world-wide leader for manufacturing instruments with expertise in various space missions and programs, has defined the image sensor specifications and is taking care of the final device characterization. In this paper, an overview of the process flow, the results on test structures and imagers processed using this platform will be presented.

Persistent recruitment of somatosensory cortex during active maintenance of hand images in working memory.

PubMed

Galvez-Pol, A; Calvo-Merino, B; Capilla, A; Forster, B

2018-07-01

Working memory (WM) supports temporary maintenance of task-relevant information. This process is associated with persistent activity in the sensory cortex processing the information (e.g., visual stimuli activate visual cortex). However, we argue here that more multifaceted stimuli moderate this sensory-locked activity and recruit distinctive cortices. Specifically, perception of bodies recruits somatosensory cortex (SCx) beyond early visual areas (suggesting embodiment processes). Here we explore persistent activation in processing areas beyond the sensory cortex initially relevant to the modality of the stimuli. Using visual and somatosensory evoked-potentials in a visual WM task, we isolated different levels of visual and somatosensory involvement during encoding of body and non-body-related images. Persistent activity increased in SCx only when maintaining body images in WM, whereas visual/posterior regions' activity increased significantly when maintaining non-body images. Our results bridge WM and embodiment frameworks, supporting a dynamic WM process where the nature of the information summons specific processing resources. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting cotton yield of small field plots in a cotton breeding program using UAV imagery data

NASA Astrophysics Data System (ADS)

Maja, Joe Mari J.; Campbell, Todd; Camargo Neto, Joao; Astillo, Philip

2016-05-01

One of the major criteria used for advancing experimental lines in a breeding program is yield performance. Obtaining yield performance data requires machine picking each plot with a cotton picker, modified to weigh individual plots. Harvesting thousands of small field plots requires a great deal of time and resources. The efficiency of cotton breeding could be increased significantly while the cost could be decreased with the availability of accurate methods to predict yield performance. This work is investigating the feasibility of using an image processing technique using a commercial off-the-shelf (COTS) camera mounted on a small Unmanned Aerial Vehicle (sUAV) to collect normal RGB images in predicting cotton yield on small plot. An orthonormal image was generated from multiple images and used to process multiple, segmented plots. A Gaussian blur was used to eliminate the high frequency component of the images, which corresponds to the cotton pixels, and used image subtraction technique to generate high frequency pixel images. The cotton pixels were then separated using k-means cluster with 5 classes. Based on the current work, the calculated percentage cotton area was computed using the generated high frequency image (cotton pixels) divided by the total area of the plot. Preliminary results showed (five flights, 3 altitudes) that cotton cover on multiple pre-selected 227 sq. m. plots produce an average of 8% which translate to approximately 22.3 kgs. of cotton. The yield prediction equation generated from the test site was then use on a separate validation site and produced a prediction error of less than 10%. In summary, the results indicate that a COTS camera with an appropriate image processing technique can produce results that are comparable to expensive sensors.

Recognition of Roasted Coffee Bean Levels using Image Processing and Neural Network

NASA Astrophysics Data System (ADS)

Nasution, T. H.; Andayani, U.

2017-03-01

The coffee beans roast levels have some characteristics. However, some people cannot recognize the coffee beans roast level. In this research, we propose to design a method to recognize the coffee beans roast level of images digital by processing the image and classifying with backpropagation neural network. The steps consist of how to collect the images data with image acquisition, pre-processing, feature extraction using Gray Level Co-occurrence Matrix (GLCM) method and finally normalization of data extraction using decimal scaling features. The values of decimal scaling features become an input of classifying in backpropagation neural network. We use the method of backpropagation to recognize the coffee beans roast levels. The results showed that the proposed method is able to identify the coffee roasts beans level with an accuracy of 97.5%.

The near real time image navigation of pictures returned by Voyager 2 at Neptune

NASA Technical Reports Server (NTRS)

Underwood, Ian M.; Bachman, Nathaniel J.; Taber, William L.; Wang, Tseng-Chan; Acton, Charles H.

1990-01-01

The development of a process for performing image navigation in near real time is described. The process was used to accurately determine the camera pointing for pictures returned by the Voyager 2 spacecraft at Neptune Encounter. Image navigation improves knowledge of the pointing of an imaging instrument at a particular epoch by correlating the spacecraft-relative locations of target bodies in inertial space with the locations of their images in a picture taken at that epoch. More than 8,500 pictures returned by Voyager 2 at Neptune were processed in near real time. The results were used in several applications, including improving pointing knowledge for nonimaging instruments ('C-smithing'), making 'Neptune, the Movie', and providing immediate access to geometrical quantities similar to those traditionally supplied in the Supplementary Experiment Data Record.

Acquiring skill at medical image inspection: learning localized in early visual processes

NASA Astrophysics Data System (ADS)

Sowden, Paul T.; Davies, Ian R. L.; Roling, Penny; Watt, Simon J.

1997-04-01

Acquisition of the skill of medical image inspection could be due to changes in visual search processes, 'low-level' sensory learning, and higher level 'conceptual learning.' Here, we report two studies that investigate the extent to which learning in medical image inspection involves low- level learning. Early in the visual processing pathway cells are selective for direction of luminance contrast. We exploit this in the present studies by using transfer across direction of contrast as a 'marker' to indicate the level of processing at which learning occurs. In both studies twelve observers trained for four days at detecting features in x- ray images (experiment one equals discs in the Nijmegen phantom, experiment two equals micro-calcification clusters in digitized mammograms). Half the observers examined negative luminance contrast versions of the images and the remainder examined positive contrast versions. On the fifth day, observers swapped to inspect their respective opposite contrast images. In both experiments leaning occurred across sessions. In experiment one, learning did not transfer across direction of luminance contrast, while in experiment two there was only partial transfer. These findings are consistent with the contention that some of the leaning was localized early in the visual processing pathway. The implications of these results for current medical image inspection training schedules are discussed.

Objective Measurement of Erythema in Psoriasis using Digital Color Photography with Color Calibration

PubMed Central

Raina, Abhay; Hennessy, Ricky; Rains, Michael; Allred, James; Hirshburg, Jason M; Diven, Dayna; Markey, Mia K.

2016-01-01

Background Traditional metrics for evaluating the severity of psoriasis are subjective, which complicates efforts to measure effective treatments in clinical trials. Methods We collected images of psoriasis plaques and calibrated the coloration of the images according to an included color card. Features were extracted from the images and used to train a linear discriminant analysis classifier with cross-validation to automatically classify the degree of erythema. The results were tested against numerical scores obtained by a panel of dermatologists using a standard rating system. Results Quantitative measures of erythema based on the digital color images showed good agreement with subjective assessment of erythema severity (κ = 0.4203). The color calibration process improved the agreement from κ = 0.2364 to κ = 0.4203. Conclusions We propose a method for the objective measurement of the psoriasis severity parameter of erythema and show that the calibration process improved the results. PMID:26517973

Application of imaging and ultrasound to the quality grading of beef

NASA Astrophysics Data System (ADS)

Anselmo, V. J.; Gammell, P. M.

1980-04-01

The results of a study conducted to assist the Department of Agriculture in the task of considering innovative methods for the grading of carcass beef for human consumption is presented. The processing of photographic, television and ultrasound images of the longissimus dorsi muscle at the 12/13th rib cut was undertaken. The results showed that a correlation could be developed between the quality grade of the carcass as determined by a professional grader, and the fat to area ratio of the muscle as determined by image processing techniques. In addition, the use of ultrasound shows the potential for grading of an unsliced carcass or a live animal.

Application of imaging and ultrasound to the quality grading of beef

NASA Technical Reports Server (NTRS)

Anselmo, V. J.; Gammell, P. M.

1980-01-01

The results of a study conducted to assist the Department of Agriculture in the task of considering innovative methods for the grading of carcass beef for human consumption is presented. The processing of photographic, television and ultrasound images of the longissimus dorsi muscle at the 12/13th rib cut was undertaken. The results showed that a correlation could be developed between the quality grade of the carcass as determined by a professional grader, and the fat to area ratio of the muscle as determined by image processing techniques. In addition, the use of ultrasound shows the potential for grading of an unsliced carcass or a live animal.

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis.

PubMed

Yagahara, Ayako; Yokooka, Yuki; Jiang, Guoqian; Tsuji, Shintarou; Fukuda, Akihisa; Nishimoto, Naoki; Kurowarabi, Kunio; Ogasawara, Katsuhiko

2018-03-01

Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and intuition. In our previous study, we analyzed the process using a new bottom-up hierarchical task analysis and identified key components of the process. Leveraging the results of the previous study, the purpose of this study was to construct a mammographic examination process ontology to formally describe the relationships between the process and image evaluation criteria to improve the quality of mammograms. First, we identified and created root classes: task, plan, and clinical image evaluation (CIE). Second, we described an "is-a" relation referring to the result of the previous study and the structure of the CIE. Third, the procedural steps in the ontology were described using the new properties: "isPerformedBefore," "isPerformedAfter," and "isPerformedAfterIfNecessary." Finally, the relationships between tasks and CIEs were described using the "isAffectedBy" property to represent the influence of the process on image quality. In total, there were 219 classes in the ontology. By introducing new properties related to the process flow, a sophisticated mammography examination process could be visualized. In relationships between tasks and CIEs, it became clear that the tasks affecting the evaluation criteria related to positioning were greater in number than those for image quality. We developed a mammographic examination process ontology that makes knowledge explicit for a comprehensive mammography process. Our research will support education and help promote knowledge sharing about mammography examination expertise.

An interactive medical image segmentation framework using iterative refinement.

PubMed

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

IOTA: integration optimization, triage and analysis tool for the processing of XFEL diffraction images.

PubMed

Lyubimov, Artem Y; Uervirojnangkoorn, Monarin; Zeldin, Oliver B; Brewster, Aaron S; Murray, Thomas D; Sauter, Nicholas K; Berger, James M; Weis, William I; Brunger, Axel T

2016-06-01

Serial femtosecond crystallography (SFX) uses an X-ray free-electron laser to extract diffraction data from crystals not amenable to conventional X-ray light sources owing to their small size or radiation sensitivity. However, a limitation of SFX is the high variability of the diffraction images that are obtained. As a result, it is often difficult to determine optimal indexing and integration parameters for the individual diffraction images. Presented here is a software package, called IOTA , which uses a grid-search technique to determine optimal spot-finding parameters that can in turn affect the success of indexing and the quality of integration on an image-by-image basis. Integration results can be filtered using a priori information about the Bravais lattice and unit-cell dimensions and analyzed for unit-cell isomorphism, facilitating an improvement in subsequent data-processing steps.

Image processing for x-ray inspection of pistachio nuts

NASA Astrophysics Data System (ADS)

Casasent, David P.

2001-03-01

A review is provided of image processing techniques that have been applied to the inspection of pistachio nuts using X-ray images. X-ray sensors provide non-destructive internal product detail not available from other sensors. The primary concern in this data is detecting the presence of worm infestations in nuts, since they have been linked to the presence of aflatoxin. We describe new techniques for segmentation, feature selection, selection of product categories (clusters), classifier design, etc. Specific novel results include: a new segmentation algorithm to produce images of isolated product items; preferable classifier operation (the classifier with the best probability of correct recognition Pc is not best); higher-order discrimination information is present in standard features (thus, high-order features appear useful); classifiers that use new cluster categories of samples achieve improved performance. Results are presented for X-ray images of pistachio nuts; however, all techniques have use in other product inspection applications.

Single Anisotropic 3-D MR Image Upsampling via Overcomplete Dictionary Trained From In-Plane High Resolution Slices.

PubMed

Jia, Yuanyuan; He, Zhongshi; Gholipour, Ali; Warfield, Simon K

2016-11-01

In magnetic resonance (MR), hardware limitation, scanning time, and patient comfort often result in the acquisition of anisotropic 3-D MR images. Enhancing image resolution is desired but has been very challenging in medical image processing. Super resolution reconstruction based on sparse representation and overcomplete dictionary has been lately employed to address this problem; however, these methods require extra training sets, which may not be always available. This paper proposes a novel single anisotropic 3-D MR image upsampling method via sparse representation and overcomplete dictionary that is trained from in-plane high resolution slices to upsample in the out-of-plane dimensions. The proposed method, therefore, does not require extra training sets. Abundant experiments, conducted on simulated and clinical brain MR images, show that the proposed method is more accurate than classical interpolation. When compared to a recent upsampling method based on the nonlocal means approach, the proposed method did not show improved results at low upsampling factors with simulated images, but generated comparable results with much better computational efficiency in clinical cases. Therefore, the proposed approach can be efficiently implemented and routinely used to upsample MR images in the out-of-planes views for radiologic assessment and postacquisition processing.

SU-E-T-497: Semi-Automated in Vivo Radiochromic Film Dosimetry Using a Novel Image Processing Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reyhan, M; Yue, N

Purpose: To validate an automated image processing algorithm designed to detect the center of radiochromic film used for in vivo film dosimetry against the current gold standard of manual selection. Methods: An image processing algorithm was developed to automatically select the region of interest (ROI) in *.tiff images that contain multiple pieces of radiochromic film (0.5x1.3cm{sup 2}). After a user has linked a calibration file to the processing algorithm and selected a *.tiff file for processing, an ROI is automatically detected for all films by a combination of thresholding and erosion, which removes edges and any additional markings for orientation.more » Calibration is applied to the mean pixel values from the ROIs and a *.tiff image is output displaying the original image with an overlay of the ROIs and the measured doses. Validation of the algorithm was determined by comparing in vivo dose determined using the current gold standard (manually drawn ROIs) versus automated ROIs for n=420 scanned films. Bland-Altman analysis, paired t-test, and linear regression were performed to demonstrate agreement between the processes. Results: The measured doses ranged from 0.2-886.6cGy. Bland-Altman analysis of the two techniques (automatic minus manual) revealed a bias of -0.28cGy and a 95% confidence interval of (5.5cGy,-6.1cGy). These values demonstrate excellent agreement between the two techniques. Paired t-test results showed no statistical differences between the two techniques, p=0.98. Linear regression with a forced zero intercept demonstrated that Automatic=0.997*Manual, with a Pearson correlation coefficient of 0.999. The minimal differences between the two techniques may be explained by the fact that the hand drawn ROIs were not identical to the automatically selected ones. The average processing time was 6.7seconds in Matlab on an IntelCore2Duo processor. Conclusion: An automated image processing algorithm has been developed and validated, which will help minimize user interaction and processing time of radiochromic film used for in vivo dosimetry.« less

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

NASA Astrophysics Data System (ADS)

Duncan, R. B.; Sabol, C.; Borelli, K.; Spetka, S.; Addison, J.; Mallo, A.; Farnsworth, B.; Viloria, R.

2012-09-01

This paper describes image enhancement software applications engineering development work that has been performed in support of Maui Space Surveillance System (MSSS) Modernization. It also includes R&D and transition activity that has been performed over the past few years with the objective of providing increased space situational awareness (SSA) capabilities. This includes Air Force Research Laboratory (AFRL) use of an FY10 Dedicated High Performance Investment (DHPI) cluster award -- and our selection and planned use for an FY12 DHPI award. We provide an introduction to image processing of electro optical (EO) telescope sensors data; and a high resolution image enhancement and near real time processing and summary status overview. We then describe recent image enhancement applications development and support for MSSS Modernization, results to date, and end with a discussion of desired future development work and conclusions. Significant improvements to image processing enhancement have been realized over the past several years, including a key application that has realized more than a 10,000-times speedup compared to the original R&D code -- and a greater than 72-times speedup over the past few years. The latest version of this code maintains software efficiency for post-mission processing while providing optimization for image processing of data from a new EO sensor at MSSS. Additional work has also been performed to develop low latency, near real time processing of data that is collected by the ground-based sensor during overhead passes of space objects.

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery

NASA Astrophysics Data System (ADS)

Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L.

2016-12-01

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques.

Web-based platform for collaborative medical imaging research

NASA Astrophysics Data System (ADS)

Rittner, Leticia; Bento, Mariana P.; Costa, André L.; Souza, Roberto M.; Machado, Rubens C.; Lotufo, Roberto A.

2015-03-01

Medical imaging research depends basically on the availability of large image collections, image processing and analysis algorithms, hardware and a multidisciplinary research team. It has to be reproducible, free of errors, fast, accessible through a large variety of devices spread around research centers and conducted simultaneously by a multidisciplinary team. Therefore, we propose a collaborative research environment, named Adessowiki, where tools and datasets are integrated and readily available in the Internet through a web browser. Moreover, processing history and all intermediate results are stored and displayed in automatic generated web pages for each object in the research project or clinical study. It requires no installation or configuration from the client side and offers centralized tools and specialized hardware resources, since processing takes place in the cloud.

Space-based optical image encryption.

PubMed

Chen, Wen; Chen, Xudong

2010-12-20

In this paper, we propose a new method based on a three-dimensional (3D) space-based strategy for the optical image encryption. The two-dimensional (2D) processing of a plaintext in the conventional optical encryption methods is extended to a 3D space-based processing. Each pixel of the plaintext is considered as one particle in the proposed space-based optical image encryption, and the diffraction of all particles forms an object wave in the phase-shifting digital holography. The effectiveness and advantages of the proposed method are demonstrated by numerical results. The proposed method can provide a new optical encryption strategy instead of the conventional 2D processing, and may open up a new research perspective for the optical image encryption.

Within-subject template estimation for unbiased longitudinal image analysis.

PubMed

Reuter, Martin; Schmansky, Nicholas J; Rosas, H Diana; Fischl, Bruce

2012-07-16

Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

A self-teaching image processing and voice-recognition-based, intelligent and interactive system to educate visually impaired children

NASA Astrophysics Data System (ADS)

Iqbal, Asim; Farooq, Umar; Mahmood, Hassan; Asad, Muhammad Usman; Khan, Akrama; Atiq, Hafiz Muhammad

2010-02-01

A self teaching image processing and voice recognition based system is developed to educate visually impaired children, chiefly in their primary education. System comprises of a computer, a vision camera, an ear speaker and a microphone. Camera, attached with the computer system is mounted on the ceiling opposite (on the required angle) to the desk on which the book is placed. Sample images and voices in the form of instructions and commands of English, Urdu alphabets, Numeric Digits, Operators and Shapes are already stored in the database. A blind child first reads the embossed character (object) with the help of fingers than he speaks the answer, name of the character, shape etc into the microphone. With the voice command of a blind child received by the microphone, image is taken by the camera which is processed by MATLAB® program developed with the help of Image Acquisition and Image processing toolbox and generates a response or required set of instructions to child via ear speaker, resulting in self education of a visually impaired child. Speech recognition program is also developed in MATLAB® with the help of Data Acquisition and Signal Processing toolbox which records and process the command of the blind child.

Oil Spill Detection in Terma-Side-Looking Airborne Radar Images Using Image Features and Region Segmentation

PubMed Central

Alacid, Beatriz

2018-01-01

This work presents a method for oil-spill detection on Spanish coasts using aerial Side-Looking Airborne Radar (SLAR) images, which are captured using a Terma sensor. The proposed method uses grayscale image processing techniques to identify the dark spots that represent oil slicks on the sea. The approach is based on two steps. First, the noise regions caused by aircraft movements are detected and labeled in order to avoid the detection of false-positives. Second, a segmentation process guided by a map saliency technique is used to detect image regions that represent oil slicks. The results show that the proposed method is an improvement on the previous approaches for this task when employing SLAR images. PMID:29316716

Enhancing facial features by using clear facial features

NASA Astrophysics Data System (ADS)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

Applications of process improvement techniques to improve workflow in abdominal imaging.

PubMed

Tamm, Eric Peter

2016-03-01

Major changes in the management and funding of healthcare are underway that will markedly change the way radiology studies will be reimbursed. The result will be the need to deliver radiology services in a highly efficient manner while maintaining quality. The science of process improvement provides a practical approach to improve the processes utilized in radiology. This article will address in a step-by-step manner how to implement process improvement techniques to improve workflow in abdominal imaging.

[Dry view laser imager--a new economical photothermal imaging method].

PubMed

Weberling, R

1996-11-01

The production of hard copies is currently achieved by means of laser imagers and wet film processing in systems attached either directly in or to the laser imager or in a darkroom. Variations in image quality resulting from a not always optimal wet film development are frequent. A newly developed thermographic film developer for laser films without liquid powdered chemicals, on the other hand, is environmentally preferable and reducing operating costs. The completely dry developing process provides permanent image documentation meeting the quality and safety requirements of RöV and BAK. One of the currently available systems of this type, the DryView Laser Imager is inexpensive and easy to install. The selective connection principle of the DryView Laser Imager can be expanded as required and accepts digital and/or analog interfaces with all imaging systems (CT, MR, DR, US, NM) from the various manufactures.

EOS mapping accuracy study

NASA Technical Reports Server (NTRS)

Forrest, R. B.; Eppes, T. A.; Ouellette, R. J.

1973-01-01

Studies were performed to evaluate various image positioning methods for possible use in the earth observatory satellite (EOS) program and other earth resource imaging satellite programs. The primary goal is the generation of geometrically corrected and registered images, positioned with respect to the earth's surface. The EOS sensors which were considered were the thematic mapper, the return beam vidicon camera, and the high resolution pointable imager. The image positioning methods evaluated consisted of various combinations of satellite data and ground control points. It was concluded that EOS attitude control system design must be considered as a part of the image positioning problem for EOS, along with image sensor design and ground image processing system design. Study results show that, with suitable efficiency for ground control point selection and matching activities during data processing, extensive reliance should be placed on use of ground control points for positioning the images obtained from EOS and similar programs.

A Method to Measure and Estimate Normalized Contrast in Infrared Flash Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

A Q-Ising model application for linear-time image segmentation

NASA Astrophysics Data System (ADS)

Bentrem, Frank W.

2010-10-01

A computational method is presented which efficiently segments digital grayscale images by directly applying the Q-state Ising (or Potts) model. Since the Potts model was first proposed in 1952, physicists have studied lattice models to gain deep insights into magnetism and other disordered systems. For some time, researchers have realized that digital images may be modeled in much the same way as these physical systems ( i.e., as a square lattice of numerical values). A major drawback in using Potts model methods for image segmentation is that, with conventional methods, it processes in exponential time. Advances have been made via certain approximations to reduce the segmentation process to power-law time. However, in many applications (such as for sonar imagery), real-time processing requires much greater efficiency. This article contains a description of an energy minimization technique that applies four Potts (Q-Ising) models directly to the image and processes in linear time. The result is analogous to partitioning the system into regions of four classes of magnetism. This direct Potts segmentation technique is demonstrated on photographic, medical, and acoustic images.

Astronomical Image Processing with Hadoop

NASA Astrophysics Data System (ADS)

Wiley, K.; Connolly, A.; Krughoff, S.; Gardner, J.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-07-01

In the coming decade astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. With a requirement that these images be analyzed in real time to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. In the commercial world, new techniques that utilize cloud computing have been developed to handle massive data streams. In this paper we describe how cloud computing, and in particular the map-reduce paradigm, can be used in astronomical data processing. We will focus on our experience implementing a scalable image-processing pipeline for the SDSS database using Hadoop (http://hadoop.apache.org). This multi-terabyte imaging dataset approximates future surveys such as those which will be conducted with the LSST. Our pipeline performs image coaddition in which multiple partially overlapping images are registered, integrated and stitched into a single overarching image. We will first present our initial implementation, then describe several critical optimizations that have enabled us to achieve high performance, and finally describe how we are incorporating a large in-house existing image processing library into our Hadoop system. The optimizations involve prefiltering of the input to remove irrelevant images from consideration, grouping individual FITS files into larger, more efficient indexed files, and a hybrid system in which a relational database is used to determine the input images relevant to the task. The incorporation of an existing image processing library, written in C++, presented difficult challenges since Hadoop is programmed primarily in Java. We will describe how we achieved this integration and the sophisticated image processing routines that were made feasible as a result. We will end by briefly describing the longer term goals of our work, namely detection and classification of transient objects and automated object classification.

A Review on Medical Image Registration as an Optimization Problem

PubMed Central

Song, Guoli; Han, Jianda; Zhao, Yiwen; Wang, Zheng; Du, Huibin

2017-01-01

Objective: In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem. Methods: The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images. Result: The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process. Conclusion: The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration. PMID:28845149

Medical image integrity control and forensics based on watermarking--approximating local modifications and identifying global image alterations.

PubMed

Huang, H; Coatrieux, G; Shu, H Z; Luo, L M; Roux, Ch

2011-01-01

In this paper we present a medical image integrity verification system that not only allows detecting and approximating malevolent local image alterations (e.g. removal or addition of findings) but is also capable to identify the nature of global image processing applied to the image (e.g. lossy compression, filtering …). For that purpose, we propose an image signature derived from the geometric moments of pixel blocks. Such a signature is computed over regions of interest of the image and then watermarked in regions of non interest. Image integrity analysis is conducted by comparing embedded and recomputed signatures. If any, local modifications are approximated through the determination of the parameters of the nearest generalized 2D Gaussian. Image moments are taken as image features and serve as inputs to one classifier we learned to discriminate the type of global image processing. Experimental results with both local and global modifications illustrate the overall performances of our approach.

Modeling human faces with multi-image photogrammetry

NASA Astrophysics Data System (ADS)

D'Apuzzo, Nicola

2002-03-01

Modeling and measurement of the human face have been increasing by importance for various purposes. Laser scanning, coded light range digitizers, image-based approaches and digital stereo photogrammetry are the used methods currently employed in medical applications, computer animation, video surveillance, teleconferencing and virtual reality to produce three dimensional computer models of the human face. Depending on the application, different are the requirements. Ours are primarily high accuracy of the measurement and automation in the process. The method presented in this paper is based on multi-image photogrammetry. The equipment, the method and results achieved with this technique are here depicted. The process is composed of five steps: acquisition of multi-images, calibration of the system, establishment of corresponding points in the images, computation of their 3-D coordinates and generation of a surface model. The images captured by five CCD cameras arranged in front of the subject are digitized by a frame grabber. The complete system is calibrated using a reference object with coded target points, which can be measured fully automatically. To facilitate the establishment of correspondences in the images, texture in the form of random patterns can be projected from two directions onto the face. The multi-image matching process, based on a geometrical constrained least squares matching algorithm, produces a dense set of corresponding points in the five images. Neighborhood filters are then applied on the matching results to remove the errors. After filtering the data, the three-dimensional coordinates of the matched points are computed by forward intersection using the results of the calibration process; the achieved mean accuracy is about 0.2 mm in the sagittal direction and about 0.1 mm in the lateral direction. The last step of data processing is the generation of a surface model from the point cloud and the application of smooth filters. Moreover, a color texture image can be draped over the model to achieve a photorealistic visualization. The advantage of the presented method over laser scanning and coded light range digitizers is the acquisition of the source data in a fraction of a second, allowing the measurement of human faces with higher accuracy and the possibility to measure dynamic events like the speech of a person.

Evaluation of a Noise Reduction Procedure for Chest Radiography

PubMed Central

Fukui, Ryohei; Ishii, Rie; Kodani, Kazuhiko; Kanasaki, Yoshiko; Suyama, Hisashi; Watanabe, Masanari; Nakamoto, Masaki; Fukuoka, Yasushi

2013-01-01

Background The aim of this study was to evaluate the usefulness of noise reduction procedure (NRP), a function in the new image processing for chest radiography. Methods A CXDI-50G Portable Digital Radiography System (Canon) was used for X-ray detection. Image noise was analyzed with a noise power spectrum (NPS) and a burger phantom was used for evaluation of density resolution. The usefulness of NRP was evaluated by chest phantom images and clinical chest radiography. We employed the Bureau of Radiological Health Method for scoring chest images while carrying out our observations. Results NPS through the use of NRP was improved compared with conventional image processing (CIP). The results in image quality showed high-density resolution through the use of NRP, so that chest radiography examination can be performed with a low dose of radiation. Scores were significantly higher than for CIP. Conclusion In this study, use of NRP led to a high evaluation in these so we are able to confirm the usefulness of NRP for clinical chest radiography. PMID:24574577

Measurement of thermally ablated lesions in sonoelastographic images using level set methods

NASA Astrophysics Data System (ADS)

Castaneda, Benjamin; Tamez-Pena, Jose Gerardo; Zhang, Man; Hoyt, Kenneth; Bylund, Kevin; Christensen, Jared; Saad, Wael; Strang, John; Rubens, Deborah J.; Parker, Kevin J.

2008-03-01

The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.

Statistical lamb wave localization based on extreme value theory

NASA Astrophysics Data System (ADS)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

Normative Databases for Imaging Instrumentation

PubMed Central

Realini, Tony; Zangwill, Linda; Flanagan, John; Garway-Heath, David; Patella, Vincent Michael; Johnson, Chris; Artes, Paul; Ben Gaddie, I.; Fingeret, Murray

2015-01-01

Purpose To describe the process by which imaging devices undergo reference database development and regulatory clearance. The limitations and potential improvements of reference (normative) data sets for ophthalmic imaging devices will be discussed. Methods A symposium was held in July 2013 in which a series of speakers discussed issues related to the development of reference databases for imaging devices. Results Automated imaging has become widely accepted and used in glaucoma management. The ability of such instruments to discriminate healthy from glaucomatous optic nerves, and to detect glaucomatous progression over time is limited by the quality of reference databases associated with the available commercial devices. In the absence of standardized rules governing the development of reference databases, each manufacturer’s database differs in size, eligibility criteria, and ethnic make-up, among other key features. Conclusions The process for development of imaging reference databases may be improved by standardizing eligibility requirements and data collection protocols. Such standardization may also improve the degree to which results may be compared between commercial instruments. PMID:25265003

Visual grading analysis of digital neonatal chest phantom X-ray images: Impact of detector type, dose and image processing on image quality.

PubMed

Smet, M H; Breysem, L; Mussen, E; Bosmans, H; Marshall, N W; Cockmartin, L

2018-07-01

To evaluate the impact of digital detector, dose level and post-processing on neonatal chest phantom X-ray image quality (IQ). A neonatal phantom was imaged using four different detectors: a CR powder phosphor (PIP), a CR needle phosphor (NIP) and two wireless CsI DR detectors (DXD and DRX). Five different dose levels were studied for each detector and two post-processing algorithms evaluated for each vendor. Three paediatric radiologists scored the images using European quality criteria plus additional questions on vascular lines, noise and disease simulation. Visual grading characteristics and ordinal regression statistics were used to evaluate the effect of detector type, post-processing and dose on VGA score (VGAS). No significant differences were found between the NIP, DXD and CRX detectors (p>0.05) whereas the PIP detector had significantly lower VGAS (p< 0.0001). Processing did not influence VGAS (p=0.819). Increasing dose resulted in significantly higher VGAS (p<0.0001). Visual grading analysis (VGA) identified a detector air kerma/image (DAK/image) of ~2.4 μGy as an ideal working point for NIP, DXD and DRX detectors. VGAS tracked IQ differences between detectors and dose levels but not image post-processing changes. VGA showed a DAK/image value above which perceived IQ did not improve, potentially useful for commissioning. • A VGA study detects IQ differences between detectors and dose levels. • The NIP detector matched the VGAS of the CsI DR detectors. • VGA data are useful in setting initial detector air kerma level. • Differences in NNPS were consistent with changes in VGAS.

Acousto-optic time- and space-integrating spotlight-mode SAR processor

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.

1993-09-01

The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.

Combined neutron and x-ray imaging at the National Ignition Facility (invited)

DOE PAGES

Danly, C. R.; Christensen, K.; Fatherley, Valerie E.; ...

2016-10-11

X-ray and neutrons are commonly used to image Inertial Confinement Fusion implosions, providing key diagnostic information on the fuel assembly of burning DT fuel. The x-ray and neutron data provided are complementary as the production of neutrons and x-rays occur from different physical processes, but typically these two images are collected from different views with no opportunity for co-registration of the two images. Neutrons are produced where the DT fusion fuel is burning; X-rays are produced in regions corresponding to high temperatures. Processes such as mix of ablator material into the hotspot can result in increased x-ray production and decreasedmore » neutron production but can only be confidently observed if the two images are collected along the same line of sight and co-registered. To allow direct comparison of x-ray and neutron data, a Combined Neutron X-ray Imaging system has been tested at Omega and installed at the National Ignition Facility to collect an x-ray image along the currently installed neutron imaging line-of-sight. Here, this system is described, and initial results are presented along with prospects for definitive coregistration of the images.« less

Using hyperspectral imaging technology to identify diseased tomato leaves

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Zhao, Xueguan; Meng, Zhijun; Zou, Wei

2016-11-01

In the process of tomato plants growth, due to the effect of plants genetic factors, poor environment factors, or disoperation of parasites, there will generate a series of unusual symptoms on tomato plants from physiology, organization structure and external form, as a result, they cannot grow normally, and further to influence the tomato yield and economic benefits. Hyperspectral image usually has high spectral resolution, not only contains spectral information, but also contains the image information, so this study adopted hyperspectral imaging technology to identify diseased tomato leaves, and developed a simple hyperspectral imaging system, including a halogen lamp light source unit, a hyperspectral image acquisition unit and a data processing unit. Spectrometer detection wavelength ranged from 400nm to 1000nm. After hyperspectral images of tomato leaves being captured, it was needed to calibrate hyperspectral images. This research used spectrum angle matching method and spectral red edge parameters discriminant method respectively to identify diseased tomato leaves. Using spectral red edge parameters discriminant method produced higher recognition accuracy, the accuracy was higher than 90%. Research results have shown that using hyperspectral imaging technology to identify diseased tomato leaves is feasible, and provides the discriminant basis for subsequent disease control of tomato plants.

Combined neutron and x-ray imaging at the National Ignition Facility (invited).

PubMed

Danly, C R; Christensen, K; Fatherley, V E; Fittinghoff, D N; Grim, G P; Hibbard, R; Izumi, N; Jedlovec, D; Merrill, F E; Schmidt, D W; Simpson, R A; Skulina, K; Volegov, P L; Wilde, C H

2016-11-01

X-ray and neutrons are commonly used to image inertial confinement fusion implosions, providing key diagnostic information on the fuel assembly of burning deuterium-tritium (DT) fuel. The x-ray and neutron data provided are complementary as the production of neutrons and x-rays occurs from different physical processes, but typically these two images are collected from different views with no opportunity for co-registration of the two images. Neutrons are produced where the DT fusion fuel is burning; X-rays are produced in regions corresponding to high temperatures. Processes such as mix of ablator material into the hotspot can result in increased x-ray production and decreased neutron production but can only be confidently observed if the two images are collected along the same line of sight and co-registered. To allow direct comparison of x-ray and neutron data, a combined neutron x-ray imaging system has been tested at Omega and installed at the National Ignition Facility to collect an x-ray image along the currently installed neutron imaging line of sight. This system is described, and initial results are presented along with prospects for definitive coregistration of the images.

Novel optical scanning cryptography using Fresnel telescope imaging.

PubMed

Yan, Aimin; Sun, Jianfeng; Hu, Zhijuan; Zhang, Jingtao; Liu, Liren

2015-07-13

We propose a new method called modified optical scanning cryptography using Fresnel telescope imaging technique for encryption and decryption of remote objects. An image or object can be optically encrypted on the fly by Fresnel telescope scanning system together with an encryption key. For image decryption, the encrypted signals are received and processed with an optical coherent heterodyne detection system. The proposed method has strong performance through use of secure Fresnel telescope scanning with orthogonal polarized beams and efficient all-optical information processing. The validity of the proposed method is demonstrated by numerical simulations and experimental results.

Adaptive platform for fluorescence microscopy-based high-content screening

NASA Astrophysics Data System (ADS)

Geisbauer, Matthias; Röder, Thorsten; Chen, Yang; Knoll, Alois; Uhl, Rainer

2010-04-01

Fluorescence microscopy has become a widely used tool for the study of medically relevant intra- and intercellular processes. Extracting meaningful information out of a bulk of acquired images is usually performed during a separate post-processing task. Thus capturing raw data results in an unnecessary huge number of images, whereas usually only a few images really show the particular information that is searched for. Here we propose a novel automated high-content microscope system, which enables experiments to be carried out with only a minimum of human interaction. It facilitates a huge speed-increase for cell biology research and its applications compared to the widely performed workflows. Our fluorescence microscopy system can automatically execute application-dependent data processing algorithms during the actual experiment. They are used for image contrast enhancement, cell segmentation and/or cell property evaluation. On-the-fly retrieved information is used to reduce data and concomitantly control the experiment process in real-time. Resulting in a closed loop of perception and action the system can greatly decrease the amount of stored data on one hand and increases the relative valuable data content on the other hand. We demonstrate our approach by addressing the problem of automatically finding cells with a particular combination of labeled receptors and then selectively stimulate them with antagonists or agonists. The results are then compared against the results of traditional, static systems.

Vision based tunnel inspection using non-rigid registration

NASA Astrophysics Data System (ADS)

Badshah, Amir; Ullah, Shan; Shahzad, Danish

2015-04-01

Growing numbers of long tunnels across the globe has increased the need for safety measurements and inspections of tunnels in these days. To avoid serious damages, tunnel inspection is highly recommended at regular intervals of time to find any deformations or cracks at the right time. While following the stringent safety and tunnel accessibility standards, conventional geodetic surveying using techniques of civil engineering and other manual and mechanical methods are time consuming and results in troublesome of routine life. An automatic tunnel inspection by image processing techniques using non rigid registration has been proposed. There are many other image processing methods used for image registration purposes. Most of the processes are operation of images in its spatial domain like finding edges and corners by Harris edge detection method. These methods are quite time consuming and fail for some or other reasons like for blurred or images with noise. Due to use of image features directly by these methods in the process, are known by the group, correlation by image features. The other method is featureless correlation, in which the images are converted into its frequency domain and then correlated with each other. The shift in spatial domain is the same as in frequency domain, but the processing is order faster than in spatial domain. In the proposed method modified normalized phase correlation has been used to find any shift between two images. As pre pre-processing the tunnel images i.e. reference and template are divided into small patches. All these relative patches are registered by the proposed modified normalized phase correlation. By the application of the proposed algorithm we get the pixel movement of the images. And then these pixels shifts are converted to measuring units like mm, cm etc. After the complete process if there is any shift in the tunnel at described points are located.

Multispectral and geomorphic studies of processed Voyager 2 images of Europa

NASA Technical Reports Server (NTRS)

Meier, T. A.

1984-01-01

High resolution images of Europa taken by the Voyager 2 spacecraft were used to study a portion of Europa's dark lineations and the major white line feature Agenor Linea. Initial image processing of images 1195J2-001 (violet filter), 1198J2-001 (blue filter), 1201J2-001 (orange filter), and 1204J2-001 (ultraviolet filter) was performed at the U.S.G.S. Branch of Astrogeology in Flagstaff, Arizona. Processing was completed through the stages of image registration and color ratio image construction. Pixel printouts were used in a new technique of linear feature profiling to compensate for image misregistration through the mapping of features on the printouts. In all, 193 dark lineation segments were mapped and profiled. The more accurate multispectral data derived by this method was plotted using a new application of the ternary diagram, with orange, blue, and violet relative spectral reflectances serving as end members. Statistical techniques were then applied to the ternary diagram plots. The image products generated at LPI were used mainly to cross-check and verify the results of the ternary diagram analysis.