Caltech/JPL Conference on Image Processing Technology, Data Sources and Software for Commercial and Scientific Applications

NASA Technical Reports Server (NTRS)

Redmann, G. H.

1976-01-01

Recent advances in image processing and new applications are presented to the user community to stimulate the development and transfer of this technology to industrial and commercial applications. The Proceedings contains 37 papers and abstracts, including many illustrations (some in color) and provides a single reference source for the user community regarding the ordering and obtaining of NASA-developed image-processing software and science data.

scikit-image: image processing in Python

PubMed Central

Schönberger, Johannes L.; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D.; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

2014-01-01

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org. PMID:25024921

Processing, Cataloguing and Distribution of Uas Images in Near Real Time

NASA Astrophysics Data System (ADS)

Runkel, I.

2013-08-01

Why are UAS such a hype? UAS make the data capture flexible, fast and easy. For many applications this is more important than a perfect photogrammetric aerial image block. To ensure, that the advantage of a fast data capturing will be valid up to the end of the processing chain, all intermediate steps like data processing and data dissemination to the customer need to be flexible and fast as well. GEOSYSTEMS has established the whole processing workflow as server/client solution. This is the focus of the presentation. Depending on the image acquisition system the image data can be down linked during the flight to the data processing computer or it is stored on a mobile device and hooked up to the data processing computer after the flight campaign. The image project manager reads the data from the device and georeferences the images according to the position data. The meta data is converted into an ISO conform format and subsequently all georeferenced images are catalogued in the raster data management System ERDAS APOLLO. APOLLO provides the data, respectively the images as an OGC-conform services to the customer. Within seconds the UAV-images are ready to use for GIS application, image processing or direct interpretation via web applications - where ever you want. The whole processing chain is built in a generic manner. It can be adapted to a magnitude of applications. The UAV imageries can be processed and catalogued as single ortho imges or as image mosaic. Furthermore, image data of various cameras can be fusioned. By using WPS (web processing services) image enhancement, image analysis workflows like change detection layers can be calculated and provided to the image analysts. The processing of the WPS runs direct on the raster data management server. The image analyst has no data and no software on his local computer. This workflow is proven to be fast, stable and accurate. It is designed to support time critical applications for security demands - the images can be checked and interpreted in near real-time. For sensible areas it gives you the possibility to inform remote decision makers or interpretation experts in order to provide them situations awareness, wherever they are. For monitoring and inspection tasks it speeds up the process of data capture and data interpretation. The fully automated workflow of data pre-processing, data georeferencing, data cataloguing and data dissemination in near real time was developed based on the Intergraph products ERDAS IMAGINE, ERDAS APOLLO and GEOSYSTEMS METAmorph!IT. It is offered as adaptable solution by GEOSYSTEMS GmbH.

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.

Advanced processing for high-bandwidth sensor systems

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Blain, Phil C.; Bloch, Jeffrey J.; Brislawn, Christopher M.; Brumby, Steven P.; Cafferty, Maureen M.; Dunham, Mark E.; Frigo, Janette R.; Gokhale, Maya; Harvey, Neal R.; Kenyon, Garrett; Kim, Won-Ha; Layne, J.; Lavenier, Dominique D.; McCabe, Kevin P.; Mitchell, Melanie; Moore, Kurt R.; Perkins, Simon J.; Porter, Reid B.; Robinson, S.; Salazar, Alfonso; Theiler, James P.; Young, Aaron C.

2000-11-01

Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of spectral bands with millions of pixels. These data sets show great promise for remote sensing applications, but require new and computationally intensive processing. The goal of the Deployable Adaptive Processing Systems (DAPS) project at Los Alamos National Laboratory is to develop advanced processing hardware and algorithms for high-bandwidth sensor applications. The project has produced electronics for processing multi- and hyper-spectral sensor data, as well as LIDAR data, while employing processing elements using a variety of technologies. The project team is currently working on reconfigurable computing technology and advanced feature extraction techniques, with an emphasis on their application to image and RF signal processing. This paper presents reconfigurable computing technology and advanced feature extraction algorithm work and their application to multi- and hyperspectral image processing. Related projects on genetic algorithms as applied to image processing will be introduced, as will the collaboration between the DAPS project and the DARPA Adaptive Computing Systems program. Further details are presented in other talks during this conference and in other conferences taking place during this symposium.

Real-time hyperspectral imaging for food safety applications

USDA-ARS?s Scientific Manuscript database

Multispectral imaging systems with selected bands can commonly be used for real-time applications of food processing. Recent research has demonstrated several image processing methods including binning, noise removal filter, and appropriate morphological analysis in real-time mode can remove most fa...

The application of digital techniques to the analysis of metallurgical experiments

NASA Technical Reports Server (NTRS)

Rathz, T. J.

1977-01-01

The application of a specific digital computer system (known as the Image Data Processing System) to the analysis of three NASA-sponsored metallurgical experiments is discussed in some detail. The basic hardware and software components of the Image Data Processing System are presented. Many figures are presented in the discussion of each experimental analysis in an attempt to show the accuracy and speed that the Image Data Processing System affords in analyzing photographic images dealing with metallurgy, and in particular with material processing.

Managing Algorithmic Skeleton Nesting Requirements in Realistic Image Processing Applications: The Case of the SKiPPER-II Parallel Programming Environment's Operating Model

NASA Astrophysics Data System (ADS)

Coudarcher, Rémi; Duculty, Florent; Serot, Jocelyn; Jurie, Frédéric; Derutin, Jean-Pierre; Dhome, Michel

2005-12-01

SKiPPER is a SKeleton-based Parallel Programming EnviRonment being developed since 1996 and running at LASMEA Laboratory, the Blaise-Pascal University, France. The main goal of the project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This paper deals with the special features embedded in the latest version of the project: algorithmic skeleton nesting capabilities and a fully dynamic operating model. Throughout the case study of a complete and realistic image processing application, in which we have pointed out the requirement for skeleton nesting, we are presenting the operating model of this feature. The work described here is one of the few reported experiments showing the application of skeleton nesting facilities for the parallelisation of a realistic application, especially in the area of image processing. The image processing application we have chosen is a 3D face-tracking algorithm from appearance.

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.

Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop

NASA Astrophysics Data System (ADS)

Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.

2018-04-01

The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

Display management subsystem, version 1: A user's eye view

NASA Technical Reports Server (NTRS)

Parker, Dolores

1986-01-01

The structure and application functions of the Display Management Subsystem (DMS) are described. The DMS, a subsystem of the Transportable Applications Executive (TAE), was designed to provide a device-independent interface for an image processing and display environment. The system is callable by C and FORTRAN applications, portable to accommodate different image analysis terminals, and easily expandable to meet local needs. Generic applications are also available for performing many image processing tasks.

PCIPS 2.0: Powerful multiprofile image processing implemented on PCs

NASA Technical Reports Server (NTRS)

Smirnov, O. M.; Piskunov, N. E.

1992-01-01

Over the years, the processing power of personal computers has steadily increased. Now, 386- and 486-based PC's are fast enough for many image processing applications, and inexpensive enough even for amateur astronomers. PCIPS is an image processing system based on these platforms that was designed to satisfy a broad range of data analysis needs, while requiring minimum hardware and providing maximum expandability. It will run (albeit at a slow pace) even on a 80286 with 640K memory, but will take full advantage of bigger memory and faster CPU's. Because the actual image processing is performed by external modules, the system can be easily upgraded by the user for all sorts of scientific data analysis. PCIPS supports large format lD and 2D images in any numeric type from 8-bit integer to 64-bit floating point. The images can be displayed, overlaid, printed and any part of the data examined via an intuitive graphical user interface that employs buttons, pop-up menus, and a mouse. PCIPS automatically converts images between different types and sizes to satisfy the requirements of various applications. PCIPS features an API that lets users develop custom applications in C or FORTRAN. While doing so, a programmer can concentrate on the actual data processing, because PCIPS assumes responsibility for accessing images and interacting with the user. This also ensures that all applications, even custom ones, have a consistent and user-friendly interface. The API is compatible with factory programming, a metaphor for constructing image processing procedures that will be implemented in future versions of the system. Several application packages were created under PCIPS. The basic package includes elementary arithmetics and statistics, geometric transformations and import/export in various formats (FITS, binary, ASCII, and GIF). The CCD processing package and the spectral analysis package were successfully used to reduce spectra from the Nordic Telescope at La Palma. A photometry package is also available, and other packages are being developed. A multitasking version of PCIPS that utilizes the factory programming concept is currently under development. This version will remain compatible (on the source code level) with existing application packages and custom applications.

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

Development of a Simple Image Processing Application that Makes Abdominopelvic Tumor Visible on Positron Emission Tomography/Computed Tomography Image.

PubMed

Pandey, Anil Kumar; Saroha, Kartik; Sharma, Param Dev; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images. A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b. The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest. The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.

Photo-reconnaissance applications of computer processing of images.

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1972-01-01

Discussion of imaging processing techniques for enhancement and calibration of Jet Propulsion Laboratory imaging experiment pictures returned from NASA space vehicles such as Ranger, Mariner and Surveyor. Particular attention is given to data transmission, resolution vs recognition, and color aspects of digital data processing. The effectiveness of these techniques in applications to images from a wide variety of sources is noted. It is anticipated that the use of computer processing for enhancement of imagery will increase with the improvement and cost reduction of these techniques in the future.

AOIPS - An interactive image processing system. [Atmospheric and Oceanic Information Processing System

NASA Technical Reports Server (NTRS)

Bracken, P. A.; Dalton, J. T.; Quann, J. J.; Billingsley, J. B.

1978-01-01

The Atmospheric and Oceanographic Information Processing System (AOIPS) was developed to help applications investigators perform required interactive image data analysis rapidly and to eliminate the inefficiencies and problems associated with batch operation. This paper describes the configuration and processing capabilities of AOIPS and presents unique subsystems for displaying, analyzing, storing, and manipulating digital image data. Applications of AOIPS to research investigations in meteorology and earth resources are featured.

Methods in Astronomical Image Processing

NASA Astrophysics Data System (ADS)

Jörsäter, S.

A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

Wood industrial application for quality control using image processing

NASA Astrophysics Data System (ADS)

Ferreira, M. J. O.; Neves, J. A. C.

1994-11-01

This paper describes an application of image processing for the furniture industry. It uses an input data, images acquired directly from wood planks where defects were previously marked by an operator. A set of image processing algorithms separates and codes each defect and detects a polygonal approach of the line representing them. For such a purpose we developed a pattern classification algorithm and a new technique of segmenting defects by carving the convex hull of the binary shape representing each isolated defect.

User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

NASA Technical Reports Server (NTRS)

Huh, Oscar Karl; Leibowitz, Scott G.; Dirosa, Donald; Hill, John M.

1986-01-01

The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

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.

Synthetic Aperture Radar (SAR) data processing

NASA Technical Reports Server (NTRS)

Beckner, F. L.; Ahr, H. A.; Ausherman, D. A.; Cutrona, L. J.; Francisco, S.; Harrison, R. E.; Heuser, J. S.; Jordan, R. L.; Justus, J.; Manning, B.

1978-01-01

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.

Fundamental Concepts of Digital Image Processing

DOE R&D Accomplishments Database

Twogood, R. E.

1983-03-01

The field of a digital-image processing has experienced dramatic growth and increasingly widespread applicability in recent years. Fortunately, advances in computer technology have kept pace with the rapid growth in volume of image data in these and other applications. Digital image processing has become economical in many fields of research and in industrial and military applications. While each application has requirements unique from the others, all are concerned with faster, cheaper, more accurate, and more extensive computation. The trend is toward real-time and interactive operations, where the user of the system obtains preliminary results within a short enough time that the next decision can be made by the human processor without loss of concentration on the task at hand. An example of this is the obtaining of two-dimensional (2-D) computer-aided tomography (CAT) images. A medical decision might be made while the patient is still under observation rather than days later.

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

Hardware accelerator of convolution with exponential function for image processing applications

NASA Astrophysics Data System (ADS)

Panchenko, Ivan; Bucha, Victor

2015-12-01

In this paper we describe a Hardware Accelerator (HWA) for fast recursive approximation of separable convolution with exponential function. This filter can be used in many Image Processing (IP) applications, e.g. depth-dependent image blur, image enhancement and disparity estimation. We have adopted this filter RTL implementation to provide maximum throughput in constrains of required memory bandwidth and hardware resources to provide a power-efficient VLSI implementation.

Document Image Processing: Going beyond the Black-and-White Barrier. Progress, Issues and Options with Greyscale and Colour Image Processing.

ERIC Educational Resources Information Center

Hendley, Tom

1995-01-01

Discussion of digital document image processing focuses on issues and options associated with greyscale and color image processing. Topics include speed; size of original document; scanning resolution; markets for different categories of scanners, including photographic libraries, publishing, and office applications; hybrid systems; data…

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.

Dedicated computer system AOTK for image processing and analysis of horse navicular bone

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Fojud, A.; Koszela, K.; Mueller, W.; Górna, K.; Okoń, P.; Piekarska-Boniecka, H.

2017-07-01

The aim of the research was made the dedicated application AOTK (pol. Analiza Obrazu Trzeszczki Kopytowej) for image processing and analysis of horse navicular bone. The application was produced by using specialized software like Visual Studio 2013 and the .NET platform. To implement algorithms of image processing and analysis were used libraries of Aforge.NET. Implemented algorithms enabling accurate extraction of the characteristics of navicular bones and saving data to external files. Implemented in AOTK modules allowing the calculations of distance selected by user, preliminary assessment of conservation of structure of the examined objects. The application interface is designed in a way that ensures user the best possible view of the analyzed images.

Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

PubMed

Prescott, Jeffrey William

2013-02-01

The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

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.

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.

ImagingSIMS

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

2017-11-06

ImagingSIMS is an open source application for loading, processing, manipulating and visualizing secondary ion mass spectrometry (SIMS) data. At PNNL, a separate branch has been further developed to incorporate application specific features for dynamic SIMS data sets. These include loading CAMECA IMS-1280, NanoSIMS and modified IMS-4f raw data, creating isotopic ratio images and stitching together images from adjacent interrogation regions. In addition to other modifications of the parent open source version, this version is equipped with a point-by-point image registration tool to assist with streamlining the image fusion process.

Near-infrared spectroscopic tissue imaging for medical applications

DOEpatents

Demos,; Stavros, Staggs [Livermore, CA; Michael, C [Tracy, CA

2006-03-21

Near infrared imaging using elastic light scattering and tissue autofluorescence are explored for medical applications. The approach involves imaging using cross-polarized elastic light scattering and tissue autofluorescence in the Near Infra-Red (NIR) coupled with image processing and inter-image operations to differentiate human tissue components.

Near-infrared spectroscopic tissue imaging for medical applications

DOEpatents

Demos, Stavros [Livermore, CA; Staggs, Michael C [Tracy, CA

2006-12-12

Near infrared imaging using elastic light scattering and tissue autofluorescence are explored for medical applications. The approach involves imaging using cross-polarized elastic light scattering and tissue autofluorescence in the Near Infra-Red (NIR) coupled with image processing and inter-image operations to differentiate human tissue components.

A Web simulation of medical image reconstruction and processing as an educational tool.

PubMed

Papamichail, Dimitrios; Pantelis, Evaggelos; Papagiannis, Panagiotis; Karaiskos, Pantelis; Georgiou, Evangelos

2015-02-01

Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre- and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre- and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution.

Advantages and Disadvantages in Image Processing with Free Software in Radiology.

PubMed

Mujika, Katrin Muradas; Méndez, Juan Antonio Juanes; de Miguel, Andrés Framiñan

2018-01-15

Currently, there are sophisticated applications that make it possible to visualize medical images and even to manipulate them. These software applications are of great interest, both from a teaching and a radiological perspective. In addition, some of these applications are known as Free Open Source Software because they are free and the source code is freely available, and therefore it can be easily obtained even on personal computers. Two examples of free open source software are Osirix Lite® and 3D Slicer®. However, this last group of free applications have limitations in its use. For the radiological field, manipulating and post-processing images is increasingly important. Consequently, sophisticated computing tools that combine software and hardware to process medical images are needed. In radiology, graphic workstations allow their users to process, review, analyse, communicate and exchange multidimensional digital images acquired with different image-capturing radiological devices. These radiological devices are basically CT (Computerised Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), etc. Nevertheless, the programs included in these workstations have a high cost which always depends on the software provider and is always subject to its norms and requirements. With this study, we aim to present the advantages and disadvantages of these radiological image visualization systems in the advanced management of radiological studies. We will compare the features of the VITREA2® and AW VolumeShare 5® radiology workstation with free open source software applications like OsiriX® and 3D Slicer®, with examples from specific studies.

ImSyn: photonic image synthesis applied to synthetic aperture radar, microscopy, and ultrasound imaging

NASA Astrophysics Data System (ADS)

Turpin, Terry M.; Lafuse, James L.

1993-02-01

ImSynTM is an image synthesis technology, developed and patented by Essex Corporation. ImSynTM can provide compact, low cost, and low power solutions to some of the most difficult image synthesis problems existing today. The inherent simplicity of ImSynTM enables the manufacture of low cost and reliable photonic systems for imaging applications ranging from airborne reconnaissance to doctor's office ultrasound. The initial application of ImSynTM technology has been to SAR processing; however, it has a wide range of applications such as: image correlation, image compression, acoustic imaging, x-ray tomographic (CAT, PET, SPECT), magnetic resonance imaging (MRI), microscopy, range- doppler mapping (extended TDOA/FDOA). This paper describes ImSynTM in terms of synthetic aperture microscopy and then shows how the technology can be extended to ultrasound and synthetic aperture radar. The synthetic aperture microscope (SAM) enables high resolution three dimensional microscopy with greater dynamic range than real aperture microscopes. SAM produces complex image data, enabling the use of coherent image processing techniques. Most importantly SAM produces the image data in a form that is easily manipulated by a digital image processing workstation.

Spectral imaging applications: Remote sensing, environmental monitoring, medicine, military operations, factory automation and manufacturing

NASA Technical Reports Server (NTRS)

Gat, N.; Subramanian, S.; Barhen, J.; Toomarian, N.

1996-01-01

This paper reviews the activities at OKSI related to imaging spectroscopy presenting current and future applications of the technology. The authors discuss the development of several systems including hardware, signal processing, data classification algorithms and benchmarking techniques to determine algorithm performance. Signal processing for each application is tailored by incorporating the phenomenology appropriate to the process, into the algorithms. Pixel signatures are classified using techniques such as principal component analyses, generalized eigenvalue analysis and novel very fast neural network methods. The major hyperspectral imaging systems developed at OKSI include the Intelligent Missile Seeker (IMS) demonstration project for real-time target/decoy discrimination, and the Thermal InfraRed Imaging Spectrometer (TIRIS) for detection and tracking of toxic plumes and gases. In addition, systems for applications in medical photodiagnosis, manufacturing technology, and for crop monitoring are also under development.

Applications of digital image processing techniques to problems of data registration and correlation

NASA Technical Reports Server (NTRS)

Green, W. B.

1978-01-01

An overview is presented of the evolution of the computer configuration at JPL's Image Processing Laboratory (IPL). The development of techniques for the geometric transformation of digital imagery is discussed and consideration is given to automated and semiautomated image registration, and the registration of imaging and nonimaging data. The increasing complexity of image processing tasks at IPL is illustrated with examples of various applications from the planetary program and earth resources activities. It is noted that the registration of existing geocoded data bases with Landsat imagery will continue to be important if the Landsat data is to be of genuine use to the user community.

Transplant Image Processing Technology under Windows into the Platform Based on MiniGUI

NASA Astrophysics Data System (ADS)

Gan, Lan; Zhang, Xu; Lv, Wenya; Yu, Jia

MFC has a large number of digital image processing-related API functions, object-oriented and class mechanisms which provides image processing technology strong support in Windows. But in embedded systems, image processing technology dues to the restrictions of hardware and software do not have the environment of MFC in Windows. Therefore, this paper draws on the experience of image processing technology of Windows and transplants it into MiniGUI embedded systems. The results show that MiniGUI/Embedded graphical user interface applications about image processing which used in embedded image processing system can be good results.

Rapid 3D bioprinting from medical images: an application to bone scaffolding

NASA Astrophysics Data System (ADS)

Lee, Daniel Z.; Peng, Matthew W.; Shinde, Rohit; Khalid, Arbab; Hong, Abigail; Pennacchi, Sara; Dawit, Abel; Sipzner, Daniel; Udupa, Jayaram K.; Rajapakse, Chamith S.

2018-03-01

Bioprinting of tissue has its applications throughout medicine. Recent advances in medical imaging allows the generation of 3-dimensional models that can then be 3D printed. However, the conventional method of converting medical images to 3D printable G-Code instructions has several limitations, namely significant processing time for large, high resolution images, and the loss of microstructural surface information from surface resolution and subsequent reslicing. We have overcome these issues by creating a JAVA program that skips the intermediate triangularization and reslicing steps and directly converts binary dicom images into G-Code. In this study, we tested the two methods of G-Code generation on the application of synthetic bone graft scaffold generation. We imaged human cadaveric proximal femurs at an isotropic resolution of 0.03mm using a high resolution peripheral quantitative computed tomography (HR-pQCT) scanner. These images, of the Digital Imaging and Communications in Medicine (DICOM) format, were then processed through two methods. In each method, slices and regions of print were selected, filtered to generate a smoothed image, and thresholded. In the conventional method, these processed images are converted to the STereoLithography (STL) format and then resliced to generate G-Code. In the new, direct method, these processed images are run through our JAVA program and directly converted to G-Code. File size, processing time, and print time were measured for each. We found that this new method produced a significant reduction in G-Code file size as well as processing time (92.23% reduction). This allows for more rapid 3D printing from medical images.

Extending Single-Molecule Microscopy Using Optical Fourier Processing

PubMed Central

2015-01-01

This article surveys the recent application of optical Fourier processing to the long-established but still expanding field of single-molecule imaging and microscopy. A variety of single-molecule studies can benefit from the additional image information that can be obtained by modulating the Fourier, or pupil, plane of a widefield microscope. After briefly reviewing several current applications, we present a comprehensive and computationally efficient theoretical model for simulating single-molecule fluorescence as it propagates through an imaging system. Furthermore, we describe how phase/amplitude-modulating optics inserted in the imaging pathway may be modeled, especially at the Fourier plane. Finally, we discuss selected recent applications of Fourier processing methods to measure the orientation, depth, and rotational mobility of single fluorescent molecules. PMID:24745862

Extending single-molecule microscopy using optical Fourier processing.

PubMed

Backer, Adam S; Moerner, W E

2014-07-17

This article surveys the recent application of optical Fourier processing to the long-established but still expanding field of single-molecule imaging and microscopy. A variety of single-molecule studies can benefit from the additional image information that can be obtained by modulating the Fourier, or pupil, plane of a widefield microscope. After briefly reviewing several current applications, we present a comprehensive and computationally efficient theoretical model for simulating single-molecule fluorescence as it propagates through an imaging system. Furthermore, we describe how phase/amplitude-modulating optics inserted in the imaging pathway may be modeled, especially at the Fourier plane. Finally, we discuss selected recent applications of Fourier processing methods to measure the orientation, depth, and rotational mobility of single fluorescent molecules.

Interactive data-processing system for metallurgy

NASA Technical Reports Server (NTRS)

Rathz, T. J.

1978-01-01

Equipment indicates that system can rapidly and accurately process metallurgical and materials-processing data for wide range of applications. Advantages include increase in contract between areas on image, ability to analyze images via operator-written programs, and space available for storing images.

Image processing in forensic pathology.

PubMed

Oliver, W R

1998-03-01

Image processing applications in forensic pathology are becoming increasingly important. This article introduces basic concepts in image processing as applied to problems in forensic pathology in a non-mathematical context. Discussions of contrast enhancement, digital encoding, compression, deblurring, and other topics are presented.

Basic research planning in mathematical pattern recognition and image analysis

NASA Technical Reports Server (NTRS)

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

Pc-Based Floating Point Imaging Workstation

NASA Astrophysics Data System (ADS)

Guzak, Chris J.; Pier, Richard M.; Chinn, Patty; Kim, Yongmin

1989-07-01

The medical, military, scientific and industrial communities have come to rely on imaging and computer graphics for solutions to many types of problems. Systems based on imaging technology are used to acquire and process images, and analyze and extract data from images that would otherwise be of little use. Images can be transformed and enhanced to reveal detail and meaning that would go undetected without imaging techniques. The success of imaging has increased the demand for faster and less expensive imaging systems and as these systems become available, more and more applications are discovered and more demands are made. From the designer's perspective the challenge to meet these demands forces him to attack the problem of imaging from a different perspective. The computing demands of imaging algorithms must be balanced against the desire for affordability and flexibility. Systems must be flexible and easy to use, ready for current applications but at the same time anticipating new, unthought of uses. Here at the University of Washington Image Processing Systems Lab (IPSL) we are focusing our attention on imaging and graphics systems that implement imaging algorithms for use in an interactive environment. We have developed a PC-based imaging workstation with the goal to provide powerful and flexible, floating point processing capabilities, along with graphics functions in an affordable package suitable for diverse environments and many applications.

Pattern recognition and expert image analysis systems in biomedical image processing (Invited Paper)

NASA Astrophysics Data System (ADS)

Oosterlinck, A.; Suetens, P.; Wu, Q.; Baird, M.; F. M., C.

1987-09-01

This paper gives an overview of pattern recoanition techniques (P.R.) used in biomedical image processing and problems related to the different P.R. solutions. Also the use of knowledge based systems to overcome P.R. difficulties, is described. This is illustrated by a common example ofabiomedical image processing application.

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.

Feature evaluation of complex hysteresis smoothing and its practical applications to noisy SEM images.

PubMed

Suzuki, Kazuhiko; Oho, Eisaku

2013-01-01

Quality of a scanning electron microscopy (SEM) image is strongly influenced by noise. This is a fundamental drawback of the SEM instrument. Complex hysteresis smoothing (CHS) has been previously developed for noise removal of SEM images. This noise removal is performed by monitoring and processing properly the amplitude of the SEM signal. As it stands now, CHS may not be so utilized, though it has several advantages for SEM. For example, the resolution of image processed by CHS is basically equal to that of the original image. In order to find wide application of the CHS method in microscopy, the feature of CHS, which has not been so clarified until now is evaluated correctly. As the application of the result obtained by the feature evaluation, cursor width (CW), which is the sole processing parameter of CHS, is determined more properly using standard deviation of noise Nσ. In addition, disadvantage that CHS cannot remove the noise with excessively large amplitude is improved by a certain postprocessing. CHS is successfully applicable to SEM images with various noise amplitudes. © Wiley Periodicals, Inc.

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

Crawford, R. A.; Smith, L. M.

1994-01-01

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Techniques for Microwave Imaging.

DTIC Science & Technology

1981-01-18

reduce cross-range sidelobes in tht subsequent -’ FT and the array was padd ,,d with 64 additional r,wis containing zeros . The configuration of the array is...of microwave imagery obtained by synthetic aperture processing described in reference 1-2. This type of image. generated by processing radar data...1,000 wavelengths. Althouigh these are the intended applications, the imaging methods con- sidered have general applicability to environments outside

Image Processing Software

NASA Technical Reports Server (NTRS)

1990-01-01

The Ames digital image velocimetry technology has been incorporated in a commercially available image processing software package that allows motion measurement of images on a PC alone. The software, manufactured by Werner Frei Associates, is IMAGELAB FFT. IMAGELAB FFT is a general purpose image processing system with a variety of other applications, among them image enhancement of fingerprints and use by banks and law enforcement agencies for analysis of videos run during robberies.

Imaging techniques in digital forensic investigation: a study using neural networks

NASA Astrophysics Data System (ADS)

Williams, Godfried

2006-09-01

Imaging techniques have been applied to a number of applications, such as translation and classification problems in medicine and defence. This paper examines the application of imaging techniques in digital forensics investigation using neural networks. A review of applications of digital image processing is presented, whiles a Pedagogical analysis of computer forensics is also highlighted. A data set describing selected images in different forms are used in the simulation and experimentation.

1984 European Conference on Optics, Optical Systems and Applications, Amsterdam, Netherlands, October 9-12, 1984, Proceedings

NASA Astrophysics Data System (ADS)

Boelger, B.; Ferwerda, H. A.

Various papers on optics, optical systems, and their applications are presented. The general topics addressed include: laser systems, optical and electrooptical materials and devices; novel spectroscopic techniques and applications; inspection, remote sensing, velocimetry, and gauging; optical design and image formation; holography, image processing, and storage; and integrated and fiber optics. Also discussed are: nonlinear optics; nonlinear photorefractive materials; scattering and diffractions applications in materials processing, deposition, and machining; medical and biological applications; and focus on industry.

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

Process for guidance, containment, treatment, and imaging in a subsurface environment utilizing ferro-fluids

DOEpatents

Moridis, George J.; Oldenburg, Curtis M.

2001-01-01

Disclosed are processes for monitoring and control of underground contamination, which involve the application of ferrofluids. Two broad uses of ferrofluids are described: (1) to control liquid movement by the application of strong external magnetic fields; and (2) to image liquids by standard geophysical methods.

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.

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

NASA Astrophysics Data System (ADS)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

GreenView and GreenLand Applications Development on SEE-GRID Infrastructure

NASA Astrophysics Data System (ADS)

Mihon, Danut; Bacu, Victor; Gorgan, Dorian; Mészáros, Róbert; Gelybó, Györgyi; Stefanut, Teodor

2010-05-01

The GreenView and GreenLand applications [1] have been developed through the SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) FP7 project co-funded by the European Commission [2]. The development of environment applications is a challenge for Grid technologies and software development methodologies. This presentation exemplifies the development of the GreenView and GreenLand applications over the SEE-GRID infrastructure by the Grid Application Development Methodology [3]. Today's environmental applications are used in vary domains of Earth Science such as meteorology, ground and atmospheric pollution, ground metal detection or weather prediction. These applications run on satellite images (e.g. Landsat, MERIS, MODIS, etc.) and the accuracy of output results depends mostly of the quality of these images. The main drawback of such environmental applications regards the need of computation power and storage power (some images are almost 1GB in size), in order to process such a large data volume. Actually, almost applications requiring high computation resources have approached the migration onto the Grid infrastructure. This infrastructure offers the computing power by running the atomic application components on different Grid nodes in sequential or parallel mode. The middleware used between the Grid infrastructure and client applications is ESIP (Environment Oriented Satellite Image Processing Platform), which is based on gProcess platform [4]. In its current format, gProcess is used for launching new processes on the Grid nodes, but also for monitoring the execution status of these processes. This presentation highlights two case studies of Grid based environmental applications, GreenView and GreenLand [5]. GreenView is used in correlation with MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images and meteorological datasets, in order to produce pseudo colored temperature and vegetation maps for different geographical CEE (Central Eastern Europe) regions. On the other hand, GreenLand is used for generating maps for different vegetation indexes (e.g. NDVI, EVI, SAVI, GEMI) based on Landsat satellite images. Both applications are using interpolation and random value generation algorithms, but also specific formulas for computing vegetation index values. The GreenView and GreenLand applications have been experimented over the SEE-GRID infrastructure and the performance evaluation is reported in [6]. The improvement of the execution time (obtained through a better parallelization of jobs), the extension of geographical areas to other parts of the Earth, and new user interaction techniques on spatial data and large set of satellite images are the goals of the future work. References [1] GreenView application on Wiki, http://wiki.egee-see.org/index.php/GreenView [2] SEE-GRID-SCI Project, http://www.see-grid-sci.eu/ [3] Gorgan D., Stefanut T., Bâcu V., Mihon D., Grid based Environment Application Development Methodology, SCICOM, 7th International Conference on "Large-Scale Scientific Computations", 4-8 June, 2009, Sozopol, Bulgaria, (To be published by Springer), (2009). [4] Gorgan D., Bacu V., Stefanut T., Rodila D., Mihon D., Grid based Satellite Image Processing Platform for Earth Observation Applications Development. IDAACS'2009 - IEEE Fifth International Workshop on "Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications", 21-23 September, Cosenza, Italy, IEEE Published in Computer Press, 247-252 (2009). [5] Mihon D., Bacu V., Stefanut T., Gorgan D., "Grid Based Environment Application Development - GreenView Application". ICCP2009 - IEEE 5th International Conference on Intelligent Computer Communication and Processing, 27 Aug, 2009 Cluj-Napoca. Published by IEEE Computer Press, pp. 275-282 (2009). [6] Danut Mihon, Victor Bacu, Dorian Gorgan, Róbert Mészáros, Györgyi Gelybó, Teodor Stefanut, Practical Considerations on the GreenView Application Development and Execution over SEE-GRID. SEE-GRID-SCI User Forum, 9-10 Dec 2009, Bogazici University, Istanbul, Turkey, ISBN: 978-975-403-510-0, pp. 167-175 (2009).

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.

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Use of discrete chromatic space to tune the image tone in a color image mosaic

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Zheng, Li

2003-09-01

Color image process is a very important problem. However, the main approach presently of them is to transfer RGB colour space into another colour space, such as HIS (Hue, Intensity and Saturation). YIQ, LUV and so on. Virutally, it may not be a valid way to process colour airborne image just in one colour space. Because the electromagnetic wave is physically altered in every wave band, while the color image is perceived based on psychology vision. Therefore, it's necessary to propose an approach accord with physical transformation and psychological perception. Then, an analysis on how to use relative colour spaces to process colour airborne photo is discussed and an application on how to tune the image tone in colour airborne image mosaic is introduced. As a practice, a complete approach to perform the mosaic on color airborne images via taking full advantage of relative color spaces is discussed in the application.

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

Robust crop and weed segmentation under uncontrolled outdoor illumination.

PubMed

Jeon, Hong Y; Tian, Lei F; Zhu, Heping

2011-01-01

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA).

Status report: Data management program algorithm evaluation activity at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Jayroe, R. R., Jr.

1977-01-01

An algorithm evaluation activity was initiated to study the problems associated with image processing by assessing the independent and interdependent effects of registration, compression, and classification techniques on LANDSAT data for several discipline applications. The objective of the activity was to make recommendations on selected applicable image processing algorithms in terms of accuracy, cost, and timeliness or to propose alternative ways of processing the data. As a means of accomplishing this objective, an Image Coding Panel was established. The conduct of the algorithm evaluation is described.

Industrial application of thermal image processing and thermal control

NASA Astrophysics Data System (ADS)

Kong, Lingxue

2001-09-01

Industrial application of infrared thermography is virtually boundless as it can be used in any situations where there are temperature differences. This technology has particularly been widely used in automotive industry for process evaluation and system design. In this work, thermal image processing technique will be introduced to quantitatively calculate the heat stored in a warm/hot object and consequently, a thermal control system will be proposed to accurately and actively manage the thermal distribution within the object in accordance with the heat calculated from the thermal images.

Image Processing Software

NASA Technical Reports Server (NTRS)

1992-01-01

To convert raw data into environmental products, the National Weather Service and other organizations use the Global 9000 image processing system marketed by Global Imaging, Inc. The company's GAE software package is an enhanced version of the TAE, developed by Goddard Space Flight Center to support remote sensing and image processing applications. The system can be operated in three modes and is combined with HP Apollo workstation hardware.

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.

A smartphone application for psoriasis segmentation and classification (Conference Presentation)

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; MacKinnon, Nicholas B.; Horita, Timothy; Shi, Kevin; Khan Munia, Tamanna Tabassum; Tavakolian, Kouhyar; Alhashim, Minhal; Fazel-Rezai, Reza

2017-02-01

Psoriasis is a chronic skin disease affecting approximately 125 million people worldwide. Currently, dermatologists monitor changes of psoriasis by clinical evaluation or by measuring psoriasis severity scores over time which lead to Subjective management of this condition. The goal of this paper is to develop a reliable assessment system to quantitatively assess the changes of erythema and intensity of scaling of psoriatic lesions. A smartphone deployable mobile application is presented that uses the smartphone camera and cloud-based image processing to analyze physiological characteristics of psoriasis lesions, identify the type and stage of the scaling and erythema. The application targets to automatically evaluate Psoriasis Area Severity Index (PASI) by measuring the severity and extent of psoriasis. The mobile application performs the following core functions: 1) it captures text information from user input to create a profile in a HIPAA compliant database. 2) It captures an image of the skin with psoriasis as well as image-related information entered by the user. 3) The application color correct the image based on environmental lighting condition using calibration process including calibration procedure by capturing Macbeth ColorChecker image. 4) The color-corrected image will be transmitted to a cloud-based engine for image processing. In cloud, first, the algorithm removes the non-skin background to ensure the psoriasis segmentation is only applied to the skin regions. Then, the psoriasis segmentation algorithm estimates the erythema and scaling boundary regions of lesion. We analyzed 10 images of psoriasis images captured by cellphone, determined PASI score for each subject during our pilot study, and correlated it with changes in severity scores given by dermatologists. The success of this work allows smartphone application for psoriasis severity assessment in a long-term treatment.

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.

High-performance floating-point image computing workstation for medical applications

NASA Astrophysics Data System (ADS)

Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

1990-07-01

The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e.g., three 1280 x 1024 monitors, each with a 16-Mbyte frame buffer). Each add-in board provides an expansion connector to which an optional image computing coprocessor board may be added. Each coprocessor board supports up to four processors for a peak performance of 160 MFLOPS. The coprocessors can execute programs from external high-speed microcode memory as well as built-in internal microcode routines. The internal microcode routines provide support for 2-D and 3-D graphics operations, matrix and vector arithmetic, and image processing in integer, IEEE single-precision floating point, or IEEE double-precision floating point. In addition to providing a library of C functions which links the NeXT computer to the add-in board and supports its various operational modes, algorithms and medical imaging application programs are being developed and implemented for image display and enhancement. As an extension to the built-in algorithms of the coprocessors, 2-D Fast Fourier Transform (FF1), 2-D Inverse FFF, convolution, warping and other algorithms (e.g., Discrete Cosine Transform) which exploit the parallel architecture of the coprocessor board are being implemented.

Electromagnetic Imaging Methods for Nondestructive Evaluation Applications

PubMed Central

Deng, Yiming; Liu, Xin

2011-01-01

Electromagnetic nondestructive tests are important and widely used within the field of nondestructive evaluation (NDE). The recent advances in sensing technology, hardware and software development dedicated to imaging and image processing, and material sciences have greatly expanded the application fields, sophisticated the systems design and made the potential of electromagnetic NDE imaging seemingly unlimited. This review provides a comprehensive summary of research works on electromagnetic imaging methods for NDE applications, followed by the summary and discussions on future directions. PMID:22247693

From Wheatstone to Cameron and beyond: overview in 3-D and 4-D imaging technology

NASA Astrophysics Data System (ADS)

Gilbreath, G. Charmaine

2012-02-01

This paper reviews three-dimensional (3-D) and four-dimensional (4-D) imaging technology, from Wheatstone through today, with some prognostications for near future applications. This field is rich in variety, subject specialty, and applications. A major trend, multi-view stereoscopy, is moving the field forward to real-time wide-angle 3-D reconstruction as breakthroughs in parallel processing and multi-processor computers enable very fast processing. Real-time holography meets 4-D imaging reconstruction at the goal of achieving real-time, interactive, 3-D imaging. Applications to telesurgery and telemedicine as well as to the needs of the defense and intelligence communities are also discussed.

Image processing and products for the Magellan mission to Venus

NASA Technical Reports Server (NTRS)

Clark, Jerry; Alexander, Doug; Andres, Paul; Lewicki, Scott; Mcauley, Myche

1992-01-01

The Magellan mission to Venus is providing planetary scientists with massive amounts of new data about the surface geology of Venus. Digital image processing is an integral part of the ground data system that provides data products to the investigators. The mosaicking of synthetic aperture radar (SAR) image data from the spacecraft is being performed at JPL's Multimission Image Processing Laboratory (MIPL). MIPL hosts and supports the Image Data Processing Subsystem (IDPS), which was developed in a VAXcluster environment of hardware and software that includes optical disk jukeboxes and the TAE-VICAR (Transportable Applications Executive-Video Image Communication and Retrieval) system. The IDPS is being used by processing analysts of the Image Data Processing Team to produce the Magellan image data products. Various aspects of the image processing procedure are discussed.

Image-Processing Software For A Hypercube Computer

NASA Technical Reports Server (NTRS)

Lee, Meemong; Mazer, Alan S.; Groom, Steven L.; Williams, Winifred I.

1992-01-01

Concurrent Image Processing Executive (CIPE) is software system intended to develop and use image-processing application programs on concurrent computing environment. Designed to shield programmer from complexities of concurrent-system architecture, it provides interactive image-processing environment for end user. CIPE utilizes architectural characteristics of particular concurrent system to maximize efficiency while preserving architectural independence from user and programmer. CIPE runs on Mark-IIIfp 8-node hypercube computer and associated SUN-4 host computer.

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.

Digital Light Processing update: status and future applications

NASA Astrophysics Data System (ADS)

Hornbeck, Larry J.

1999-05-01

Digital Light Processing (DLP) projection displays based on the Digital Micromirror Device (DMD) were introduced to the market in 1996. Less than 3 years later, DLP-based projectors are found in such diverse applications as mobile, conference room, video wall, home theater, and large-venue. They provide high-quality, seamless, all-digital images that have exceptional stability as well as freedom from both flicker and image lag. Marked improvements have been made in the image quality of DLP-based projection display, including brightness, resolution, contrast ratio, and border image. DLP-based mobile projectors that weighted about 27 pounds in 1996 now weight only about 7 pounds. This weight reduction has been responsible for the definition of an entirely new projector class, the ultraportable. New applications are being developed for this important new projection display technology; these include digital photofinishing for high process speed minilab and maxilab applications and DLP Cinema for the digital delivery of films to audiences around the world. This paper describes the status of DLP-based projection display technology, including its manufacturing, performance improvements, and new applications, with emphasis on DLP Cinema.

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

Web-based interactive 2D/3D medical image processing and visualization software.

PubMed

Mahmoudi, Seyyed Ehsan; Akhondi-Asl, Alireza; Rahmani, Roohollah; Faghih-Roohi, Shahrooz; Taimouri, Vahid; Sabouri, Ahmad; Soltanian-Zadeh, Hamid

2010-05-01

There are many medical image processing software tools available for research and diagnosis purposes. However, most of these tools are available only as local applications. This limits the accessibility of the software to a specific machine, and thus the data and processing power of that application are not available to other workstations. Further, there are operating system and processing power limitations which prevent such applications from running on every type of workstation. By developing web-based tools, it is possible for users to access the medical image processing functionalities wherever the internet is available. In this paper, we introduce a pure web-based, interactive, extendable, 2D and 3D medical image processing and visualization application that requires no client installation. Our software uses a four-layered design consisting of an algorithm layer, web-user-interface layer, server communication layer, and wrapper layer. To compete with extendibility of the current local medical image processing software, each layer is highly independent of other layers. A wide range of medical image preprocessing, registration, and segmentation methods are implemented using open source libraries. Desktop-like user interaction is provided by using AJAX technology in the web-user-interface. For the visualization functionality of the software, the VRML standard is used to provide 3D features over the web. Integration of these technologies has allowed implementation of our purely web-based software with high functionality without requiring powerful computational resources in the client side. The user-interface is designed such that the users can select appropriate parameters for practical research and clinical studies. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.

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.

Potential medical applications of TAE

NASA Technical Reports Server (NTRS)

Fahy, J. Ben; Kaucic, Robert; Kim, Yongmin

1986-01-01

In cooperation with scientists in the University of Washington Medical School, a microcomputer-based image processing system for quantitative microscopy, called DMD1 (Digital Microdensitometer 1) was constructed. In order to make DMD1 transportable to different hosts and image processors, we have been investigating the possibility of rewriting the lower level portions of DMD1 software using Transportable Applications Executive (TAE) libraries and subsystems. If successful, we hope to produce a newer version of DMD1, called DMD2, running on an IBM PC/AT under the SCO XENIX System 5 operating system, using any of seven target image processors available in our laboratory. Following this implementation, copies of the system will be transferred to other laboratories with biomedical imaging applications. By integrating those applications into DMD2, we hope to eventually expand our system into a low-cost general purpose biomedical imaging workstation. This workstation will be useful not only as a self-contained instrument for clinical or research applications, but also as part of a large scale Digital Imaging Network and Picture Archiving and Communication System, (DIN/PACS). Widespread application of these TAE-based image processing and analysis systems should facilitate software exchange and scientific cooperation not only within the medical community, but between the medical and remote sensing communities as well.

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.

Analysis of the IJCNN 2011 UTL Challenge

DTIC Science & Technology

2012-01-13

large datasets from various application domains: handwriting recognition, image recognition, video processing, text processing, and ecology. The goal...http //clopinet.com/ul). We made available large datasets from various application domains handwriting recognition, image recognition, video...evaluation sets consist of 4096 examples each. Dataset Domain Features Sparsity Devel. Transf. AVICENNA Handwriting 120 0% 150205 50000 HARRY Video 5000 98.1

Application of LANDSAT data and digital image processing. [Ruhr Valley, Germany

NASA Technical Reports Server (NTRS)

Bodechtel, J. (Principal Investigator)

1978-01-01

The author has identified the following significant results. Based on LANDSAT 1 and 2 data, applications in the fields of coal mining, lignite exploration, and thematic mapping in geology are demonstrated. The hybrid image processing system, its software, and its utilization for educational purposes is described. A pre-operational European satellite is proposed.

A single FPGA-based portable ultrasound imaging system for point-of-care applications.

PubMed

Kim, Gi-Duck; Yoon, Changhan; Kye, Sang-Bum; Lee, Youngbae; Kang, Jeeun; Yoo, Yangmo; Song, Tai-kyong

2012-07-01

We present a cost-effective portable ultrasound system based on a single field-programmable gate array (FPGA) for point-of-care applications. In the portable ultrasound system developed, all the ultrasound signal and image processing modules, including an effective 32-channel receive beamformer with pseudo-dynamic focusing, are embedded in an FPGA chip. For overall system control, a mobile processor running Linux at 667 MHz is used. The scan-converted ultrasound image data from the FPGA are directly transferred to the system controller via external direct memory access without a video processing unit. The potable ultrasound system developed can provide real-time B-mode imaging with a maximum frame rate of 30, and it has a battery life of approximately 1.5 h. These results indicate that the single FPGA-based portable ultrasound system developed is able to meet the processing requirements in medical ultrasound imaging while providing improved flexibility for adapting to emerging POC applications.

Integration of image capture and processing: beyond single-chip digital camera

NASA Astrophysics Data System (ADS)

Lim, SukHwan; El Gamal, Abbas

2001-05-01

An important trend in the design of digital cameras is the integration of capture and processing onto a single CMOS chip. Although integrating the components of a digital camera system onto a single chip significantly reduces system size and power, it does not fully exploit the potential advantages of integration. We argue that a key advantage of integration is the ability to exploit the high speed imaging capability of CMOS image senor to enable new applications such as multiple capture for enhancing dynamic range and to improve the performance of existing applications such as optical flow estimation. Conventional digital cameras operate at low frame rates and it would be too costly, if not infeasible, to operate their chips at high frame rates. Integration solves this problem. The idea is to capture images at much higher frame rates than he standard frame rate, process the high frame rate data on chip, and output the video sequence and the application specific data at standard frame rate. This idea is applied to optical flow estimation, where significant performance improvements are demonstrate over methods using standard frame rate sequences. We then investigate the constraints on memory size and processing power that can be integrated with a CMOS image sensor in a 0.18 micrometers process and below. We show that enough memory and processing power can be integrated to be able to not only perform the functions of a conventional camera system but also to perform applications such as real time optical flow estimation.

The Multimission Image Processing Laboratory's virtual frame buffer interface

NASA Technical Reports Server (NTRS)

Wolfe, T.

1984-01-01

Large image processing systems use multiple frame buffers with differing architectures and vendor supplied interfaces. This variety of architectures and interfaces creates software development, maintenance and portability problems for application programs. Several machine-dependent graphics standards such as ANSI Core and GKS are available, but none of them are adequate for image processing. Therefore, the Multimission Image Processing laboratory project has implemented a programmer level virtual frame buffer interface. This interface makes all frame buffers appear as a generic frame buffer with a specified set of characteristics. This document defines the virtual frame uffer interface and provides information such as FORTRAN subroutine definitions, frame buffer characteristics, sample programs, etc. It is intended to be used by application programmers and system programmers who are adding new frame buffers to a system.

Rank-based decompositions of morphological templates.

PubMed

Sussner, P; Ritter, G X

2000-01-01

Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application

PubMed Central

Maxwell, Susan K.

2010-01-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. PMID:21135917

Experiments with recursive estimation in astronomical image processing

NASA Technical Reports Server (NTRS)

Busko, I.

1992-01-01

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

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.

Feasibility Analysis and Demonstration of High-Speed Digital Imaging Using Micro-Arrays of Vertical Cavity Surface-Emitting Lasers

DTIC Science & Technology

2011-04-01

Proceedings, Bristol, UK (2006). 5. M. A. Mentzer, Applied Optics Fundamentals and Device Applications: Nano, MOEMS , and Biotechnology, CRC Taylor...ballistic sensing, flash x-ray cineradiography, digital image correlation, image processing al- gorithms, and applications of MOEMS to nano- and

Computational models of human vision with applications

NASA Technical Reports Server (NTRS)

Wandell, B. A.

1985-01-01

Perceptual problems in aeronautics were studied. The mechanism by which color constancy is achieved in human vision was examined. A computable algorithm was developed to model the arrangement of retinal cones in spatial vision. The spatial frequency spectra are similar to the spectra of actual cone mosaics. The Hartley transform as a tool of image processing was evaluated and it is suggested that it could be used in signal processing applications, GR image processing.

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.

Robust Crop and Weed Segmentation under Uncontrolled Outdoor Illumination

PubMed Central

Jeon, Hong Y.; Tian, Lei F.; Zhu, Heping

2011-01-01

An image processing algorithm for detecting individual weeds was developed and evaluated. Weed detection processes included were normalized excessive green conversion, statistical threshold value estimation, adaptive image segmentation, median filter, morphological feature calculation and Artificial Neural Network (ANN). The developed algorithm was validated for its ability to identify and detect weeds and crop plants under uncontrolled outdoor illuminations. A machine vision implementing field robot captured field images under outdoor illuminations and the image processing algorithm automatically processed them without manual adjustment. The errors of the algorithm, when processing 666 field images, ranged from 2.1 to 2.9%. The ANN correctly detected 72.6% of crop plants from the identified plants, and considered the rest as weeds. However, the ANN identification rates for crop plants were improved up to 95.1% by addressing the error sources in the algorithm. The developed weed detection and image processing algorithm provides a novel method to identify plants against soil background under the uncontrolled outdoor illuminations, and to differentiate weeds from crop plants. Thus, the proposed new machine vision and processing algorithm may be useful for outdoor applications including plant specific direct applications (PSDA). PMID:22163954

The Power of Imaging.

ERIC Educational Resources Information Center

Haapaniemi, Peter

1990-01-01

Describes imaging technology, which allows huge numbers of words and illustrations to be reduced to tiny fraction of space required by originals and discusses current applications. Highlights include image processing system at National Archives; use by banks for high-speed check processing; engineering document management systems (EDMS); folder…

Application of digital image processing techniques to astronomical imagery, 1979

NASA Technical Reports Server (NTRS)

Lorre, J. J.

1979-01-01

Several areas of applications of image processing to astronomy were identified and discussed. These areas include: (1) deconvolution for atmospheric seeing compensation; a comparison between maximum entropy and conventional Wiener algorithms; (2) polarization in galaxies from photographic plates; (3) time changes in M87 and methods of displaying these changes; (4) comparing emission line images in planetary nebulae; and (5) log intensity, hue saturation intensity, and principal component color enhancements of M82. Examples are presented of these techniques applied to a variety of objects.

Novel Applications of Rapid Prototyping in Gamma-ray and X-ray Imaging

PubMed Central

Miller, Brian W.; Moore, Jared W.; Gehm, Michael E.; Furenlid, Lars R.; Barrett, Harrison H.

2010-01-01

Advances in 3D rapid-prototyping printers, 3D modeling software, and casting techniques allow for the fabrication of cost-effective, custom components in gamma-ray and x-ray imaging systems. Applications extend to new fabrication methods for custom collimators, pinholes, calibration and resolution phantoms, mounting and shielding components, and imaging apertures. Details of the fabrication process for these components are presented, specifically the 3D printing process, cold casting with a tungsten epoxy, and lost-wax casting in platinum. PMID:22984341

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.

Performance enhancement of various real-time image processing techniques via speculative execution

NASA Astrophysics Data System (ADS)

Younis, Mohamed F.; Sinha, Purnendu; Marlowe, Thomas J.; Stoyenko, Alexander D.

1996-03-01

In real-time image processing, an application must satisfy a set of timing constraints while ensuring the semantic correctness of the system. Because of the natural structure of digital data, pure data and task parallelism have been used extensively in real-time image processing to accelerate the handling time of image data. These types of parallelism are based on splitting the execution load performed by a single processor across multiple nodes. However, execution of all parallel threads is mandatory for correctness of the algorithm. On the other hand, speculative execution is an optimistic execution of part(s) of the program based on assumptions on program control flow or variable values. Rollback may be required if the assumptions turn out to be invalid. Speculative execution can enhance average, and sometimes worst-case, execution time. In this paper, we target various image processing techniques to investigate applicability of speculative execution. We identify opportunities for safe and profitable speculative execution in image compression, edge detection, morphological filters, and blob recognition.

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.

IPL Processing of the Viking Orbiter Images of Mars

NASA Technical Reports Server (NTRS)

Ruiz, R. M.; Elliott, D. A.; Yagi, G. M.; Pomphrey, R. B.; Power, M. A.; Farrell, W., Jr.; Lorre, J. J.; Benton, W. D.; Dewar, R. E.; Cullen, L. E.

1977-01-01

The Viking orbiter cameras returned over 9000 images of Mars during the 6-month nominal mission. Digital image processing was required to produce products suitable for quantitative and qualitative scientific interpretation. Processing included the production of surface elevation data using computer stereophotogrammetric techniques, crater classification based on geomorphological characteristics, and the generation of color products using multiple black-and-white images recorded through spectral filters. The Image Processing Laboratory of the Jet Propulsion Laboratory was responsible for the design, development, and application of the software required to produce these 'second-order' products.

Optical design and testing: introduction.

PubMed

Liang, Chao-Wen; Koshel, John; Sasian, Jose; Breault, Robert; Wang, Yongtian; Fang, Yi Chin

2014-10-10

Optical design and testing has numerous applications in industrial, military, consumer, and medical settings. Assembling a complete imaging or nonimage optical system may require the integration of optics, mechatronics, lighting technology, optimization, ray tracing, aberration analysis, image processing, tolerance compensation, and display rendering. This issue features original research ranging from the optical design of image and nonimage optical stimuli for human perception, optics applications, bio-optics applications, 3D display, solar energy system, opto-mechatronics to novel imaging or nonimage modalities in visible and infrared spectral imaging, modulation transfer function measurement, and innovative interferometry.

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.

Pseudo colour visualization of fused multispectral laser scattering images for optical diagnosis of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Zabarylo, U.; Minet, O.

2010-01-01

Investigations on the application of optical procedures for the diagnosis of rheumatism using scattered light images are only at the beginning both in terms of new image-processing methods and subsequent clinical application. For semi-automatic diagnosis using laser light, the multispectral scattered light images are registered and overlapped to pseudo-coloured images, which depict diagnostically essential contents by visually highlighting pathological changes.

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

Natural Inspired Intelligent Visual Computing and Its Application to Viticulture.

PubMed

Ang, Li Minn; Seng, Kah Phooi; Ge, Feng Lu

2017-05-23

This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.

On-road anomaly detection by multimodal sensor analysis and multimedia processing

NASA Astrophysics Data System (ADS)

Orhan, Fatih; Eren, P. E.

2014-03-01

The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.

3D measurement by digital photogrammetry

NASA Astrophysics Data System (ADS)

Schneider, Carl T.

1993-12-01

Photogrammetry is well known in geodetic surveys as aerial photogrammetry or close range applications as architectural photogrammetry. The photogrammetric methods and algorithms combined with digital cameras and digital image processing methods are now introduced for industrial applications as automation and quality control. The presented paper will describe the photogrammetric and digital image processing algorithms and the calibration methods. These algorithms and methods were demonstrated with application examples. These applications are a digital photogrammetric workstation as a mobil multi purpose 3D measuring tool and a tube measuring system as an example for a single purpose tool.

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.

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.

Research Issues in Image Registration for Remote Sensing

NASA Technical Reports Server (NTRS)

Eastman, Roger D.; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2007-01-01

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Monacos, Steve P. (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

The application of a unique flow modeling technique to complex combustion systems

NASA Astrophysics Data System (ADS)

Waslo, J.; Hasegawa, T.; Hilt, M. B.

1986-06-01

This paper describes the application of a unique three-dimensional water flow modeling technique to the study of complex fluid flow patterns within an advanced gas turbine combustor. The visualization technique uses light scattering, coupled with real-time image processing, to determine flow fields. Additional image processing is used to make concentration measurements within the combustor.

In flight image processing on multi-rotor aircraft for autonomous landing

NASA Astrophysics Data System (ADS)

Henry, Richard, Jr.

An estimated $6.4 billion was spent during the year 2013 on developing drone technology around the world and is expected to double in the next decade. However, drone applications typically require strong pilot skills, safety, responsibilities and adherence to regulations during flight. If the flight control process could be safer and more reliable in terms of landing, it would be possible to further develop a wider range of applications. The objective of this research effort is to describe the design and evaluation of a fully autonomous Unmanned Aerial system (UAS), specifically a four rotor aircraft, commonly known as quad copter for precise landing applications. The full landing autonomy is achieved by image processing capabilities during flight for target recognition by employing the open source library OpenCV. In addition, all imaging data is processed by a single embedded computer that estimates a relative position with respect to the target landing pad. Results shows a reduction on the average offset error by 67.88% in comparison to the current return to lunch (RTL) method which only relies on GPS positioning. The present work validates the need for relying on image processing for precise landing applications instead of the inexact method of a commercial low cost GPS dependency.

Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: a review

PubMed Central

Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong

2017-01-01

Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail. PMID:28303644

Proceedings of the Open Sessions of the Workshop on Imaging Trackers and Autonomous Acquisition Applications for Missile Guidance Held at Redstone Arsenal, Alabama on 19-20 November 1979

DTIC Science & Technology

1979-11-01

a generalized cooccurrence matrix. Describing image texture is an important problem in the design of image understanding systems . Applications as...display system design optimization and video signal processing. Based on a study by Southern Research Institute , a number of options were identified...Specification for Target Acquisition Designation System (U), RFP # AMC-DP-AAH-H4020, i2 Apr 77. 4. Terminal Homing Applications of Solid State Image

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

Phase in Optical Image Processing

NASA Astrophysics Data System (ADS)

Naughton, Thomas J.

2010-04-01

The use of phase has a long standing history in optical image processing, with early milestones being in the field of pattern recognition, such as VanderLugt's practical construction technique for matched filters, and (implicitly) Goodman's joint Fourier transform correlator. In recent years, the flexibility afforded by phase-only spatial light modulators and digital holography, for example, has enabled many processing techniques based on the explicit encoding and decoding of phase. One application area concerns efficient numerical computations. Pushing phase measurement to its physical limits, designs employing the physical properties of phase have ranged from the sensible to the wonderful, in some cases making computationally easy problems easier to solve and in other cases addressing mathematics' most challenging computationally hard problems. Another application area is optical image encryption, in which, typically, a phase mask modulates the fractional Fourier transformed coefficients of a perturbed input image, and the phase of the inverse transform is then sensed as the encrypted image. The inherent linearity that makes the system so elegant mitigates against its use as an effective encryption technique, but we show how a combination of optical and digital techniques can restore confidence in that security. We conclude with the concept of digital hologram image processing, and applications of same that are uniquely suited to optical implementation, where the processing, recognition, or encryption step operates on full field information, such as that emanating from a coherently illuminated real-world three-dimensional object.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

USB video image controller used in CMOS image sensor

NASA Astrophysics Data System (ADS)

Zhang, Wenxuan; Wang, Yuxia; Fan, Hong

2002-09-01

CMOS process is mainstream technique in VLSI, possesses high integration. SE402 is multifunction microcontroller, which integrates image data I/O ports, clock control, exposure control and digital signal processing into one chip. SE402 reduces the number of chips and PCB's room. The paper studies emphatically on USB video image controller used in CMOS image sensor and give the application on digital still camera.

Processing Digital Imagery to Enhance Perceptions of Realism

NASA Technical Reports Server (NTRS)

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

2003-01-01

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Two dimensional recursive digital filters for near real time image processing

NASA Technical Reports Server (NTRS)

Olson, D.; Sherrod, E.

1980-01-01

A program was designed toward the demonstration of the feasibility of using two dimensional recursive digital filters for subjective image processing applications that require rapid turn around. The concept of the use of a dedicated minicomputer for the processor for this application was demonstrated. The minicomputer used was the HP1000 series E with a RTE 2 disc operating system and 32K words of memory. A Grinnel 256 x 512 x 8 bit display system was used to display the images. Sample images were provided by NASA Goddard on a 800 BPI, 9 track tape. Four 512 x 512 images representing 4 spectral regions of the same scene were provided. These images were filtered with enhancement filters developed during this effort.

[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.

A generic FPGA-based detector readout and real-time image processing board

NASA Astrophysics Data System (ADS)

Sarpotdar, Mayuresh; Mathew, Joice; Safonova, Margarita; Murthy, Jayant

2016-07-01

For space-based astronomical observations, it is important to have a mechanism to capture the digital output from the standard detector for further on-board analysis and storage. We have developed a generic (application- wise) field-programmable gate array (FPGA) board to interface with an image sensor, a method to generate the clocks required to read the image data from the sensor, and a real-time image processor system (on-chip) which can be used for various image processing tasks. The FPGA board is applied as the image processor board in the Lunar Ultraviolet Cosmic Imager (LUCI) and a star sensor (StarSense) - instruments developed by our group. In this paper, we discuss the various design considerations for this board and its applications in the future balloon and possible space flights.

GPU computing in medical physics: a review.

PubMed

Pratx, Guillem; Xing, Lei

2011-05-01

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

Image processing for flight crew enhanced situation awareness

NASA Technical Reports Server (NTRS)

Roberts, Barry

1993-01-01

This presentation describes the image processing work that is being performed for the Enhanced Situational Awareness System (ESAS) application. Specifically, the presented work supports the Enhanced Vision System (EVS) component of ESAS.

Generating land cover boundaries from remotely sensed data using object-based image analysis: overview and epidemiological application.

PubMed

Maxwell, Susan K

2010-12-01

Satellite imagery and aerial photography represent a vast resource to significantly enhance environmental mapping and modeling applications for use in understanding spatio-temporal relationships between environment and health. Deriving boundaries of land cover objects, such as trees, buildings, and crop fields, from image data has traditionally been performed manually using a very time consuming process of hand digitizing. Boundary detection algorithms are increasingly being applied using object-based image analysis (OBIA) technology to automate the process. The purpose of this paper is to present an overview and demonstrate the application of OBIA for delineating land cover features at multiple scales using a high resolution aerial photograph (1 m) and a medium resolution Landsat image (30 m) time series in the context of a pesticide spray drift exposure application. Copyright © 2010. Published by Elsevier Ltd.

The power of neural nets

NASA Technical Reports Server (NTRS)

Ryan, J. P.; Shah, B. H.

1987-01-01

Implementation of the Hopfield net which is used in the image processing type of applications where only partial information about the image may be available is discussed. The image classification type of algorithm of Hopfield and other learning algorithms, such as the Boltzmann machine and the back-propagation training algorithm, have many vital applications in space.

Theory on data processing and instrumentation. [remote sensing

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1978-01-01

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Cerenkov luminescence imaging: physics principles and potential applications in biomedical sciences.

PubMed

Ciarrocchi, Esther; Belcari, Nicola

2017-12-01

Cerenkov luminescence imaging (CLI) is a novel imaging modality to study charged particles with optical methods by detecting the Cerenkov luminescence produced in tissue. This paper first describes the physical processes that govern the production and transport in tissue of Cerenkov luminescence. The detectors used for CLI and their most relevant specifications to optimize the acquisition of the Cerenkov signal are then presented, and CLI is compared with the other optical imaging modalities sharing the same data acquisition and processing methods. Finally, the scientific work related to CLI and the applications for which CLI has been proposed are reviewed. The paper ends with some considerations about further perspectives for this novel imaging modality.

High Throughput Multispectral Image Processing with Applications in Food Science.

PubMed

Tsakanikas, Panagiotis; Pavlidis, Dimitris; Nychas, George-John

2015-01-01

Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a high throughput approach appropriate for massive data extraction from food samples.

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.

Three-dimensional rendering of segmented object using matlab - biomed 2010.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2010-01-01

The three-dimensional rendering of microscopic objects is a difficult and challenging task that often requires specialized image processing techniques. Previous work has been described of a semi-automatic segmentation process of fluorescently stained neurons collected as a sequence of slice images with a confocal laser scanning microscope. Once properly segmented, each individual object can be rendered and studied as a three-dimensional virtual object. This paper describes the work associated with the design and development of Matlab files to create three-dimensional images from the segmented object data previously mentioned. Part of the motivation for this work is to integrate both the segmentation and rendering processes into one software application, providing a seamless transition from the segmentation tasks to the rendering and visualization tasks. Previously these tasks were accomplished on two different computer systems, windows and Linux. This transition basically limits the usefulness of the segmentation and rendering applications to those who have both computer systems readily available. The focus of this work is to create custom Matlab image processing algorithms for object rendering and visualization, and merge these capabilities to the Matlab files that were developed especially for the image segmentation task. The completed Matlab application will contain both the segmentation and rendering processes in a single graphical user interface, or GUI. This process for rendering three-dimensional images in Matlab requires that a sequence of two-dimensional binary images, representing a cross-sectional slice of the object, be reassembled in a 3D space, and covered with a surface. Additional segmented objects can be rendered in the same 3D space. The surface properties of each object can be varied by the user to aid in the study and analysis of the objects. This inter-active process becomes a powerful visual tool to study and understand microscopic objects.

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

Light-Field Imaging Toolkit

NASA Astrophysics Data System (ADS)

Bolan, Jeffrey; Hall, Elise; Clifford, Chris; Thurow, Brian

The Light-Field Imaging Toolkit (LFIT) is a collection of MATLAB functions designed to facilitate the rapid processing of raw light field images captured by a plenoptic camera. An included graphical user interface streamlines the necessary post-processing steps associated with plenoptic images. The generation of perspective shifted views and computationally refocused images is supported, in both single image and animated formats. LFIT performs necessary calibration, interpolation, and structuring steps to enable future applications of this technology.

Quantum Image Processing and Its Application to Edge Detection: Theory and Experiment

NASA Astrophysics Data System (ADS)

Yao, Xi-Wei; Wang, Hengyan; Liao, Zeyang; Chen, Ming-Cheng; Pan, Jian; Li, Jun; Zhang, Kechao; Lin, Xingcheng; Wang, Zhehui; Luo, Zhihuang; Zheng, Wenqiang; Li, Jianzhong; Zhao, Meisheng; Peng, Xinhua; Suter, Dieter

2017-07-01

Processing of digital images is continuously gaining in volume and relevance, with concomitant demands on data storage, transmission, and processing power. Encoding the image information in quantum-mechanical systems instead of classical ones and replacing classical with quantum information processing may alleviate some of these challenges. By encoding and processing the image information in quantum-mechanical systems, we here demonstrate the framework of quantum image processing, where a pure quantum state encodes the image information: we encode the pixel values in the probability amplitudes and the pixel positions in the computational basis states. Our quantum image representation reduces the required number of qubits compared to existing implementations, and we present image processing algorithms that provide exponential speed-up over their classical counterparts. For the commonly used task of detecting the edge of an image, we propose and implement a quantum algorithm that completes the task with only one single-qubit operation, independent of the size of the image. This demonstrates the potential of quantum image processing for highly efficient image and video processing in the big data era.

Bioinspired Polarization Imaging Sensors: From Circuits and Optics to Signal Processing Algorithms and Biomedical Applications

PubMed Central

York, Timothy; Powell, Samuel B.; Gao, Shengkui; Kahan, Lindsey; Charanya, Tauseef; Saha, Debajit; Roberts, Nicholas W.; Cronin, Thomas W.; Marshall, Justin; Achilefu, Samuel; Lake, Spencer P.; Raman, Baranidharan; Gruev, Viktor

2015-01-01

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro–optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal–oxide–semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors. PMID:26538682

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

NASA Technical Reports Server (NTRS)

Barrett, Eamon B. (Editor); Pearson, James J. (Editor)

1989-01-01

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

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.

An image-processing software package: UU and Fig for optical metrology applications

NASA Astrophysics Data System (ADS)

Chen, Lujie

2013-06-01

Modern optical metrology applications are largely supported by computational methods, such as phase shifting [1], Fourier Transform [2], digital image correlation [3], camera calibration [4], etc, in which image processing is a critical and indispensable component. While it is not too difficult to obtain a wide variety of image-processing programs from the internet; few are catered for the relatively special area of optical metrology. This paper introduces an image-processing software package: UU (data processing) and Fig (data rendering) that incorporates many useful functions to process optical metrological data. The cross-platform programs UU and Fig are developed based on wxWidgets. At the time of writing, it has been tested on Windows, Linux and Mac OS. The userinterface is designed to offer precise control of the underline processing procedures in a scientific manner. The data input/output mechanism is designed to accommodate diverse file formats and to facilitate the interaction with other independent programs. In terms of robustness, although the software was initially developed for personal use, it is comparably stable and accurate to most of the commercial software of similar nature. In addition to functions for optical metrology, the software package has a rich collection of useful tools in the following areas: real-time image streaming from USB and GigE cameras, computational geometry, computer vision, fitting of data, 3D image processing, vector image processing, precision device control (rotary stage, PZT stage, etc), point cloud to surface reconstruction, volume rendering, batch processing, etc. The software package is currently used in a number of universities for teaching and research.

Digital image processing for photo-reconnaissance applications

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1972-01-01

Digital image-processing techniques developed for processing pictures from NASA space vehicles are analyzed in terms of enhancement, quantitative restoration, and information extraction. Digital filtering, and the action of a high frequency filter in the real and Fourier domain are discussed along with color and brightness.

Image processing techniques and applications to the Earth Resources Technology Satellite program

NASA Technical Reports Server (NTRS)

Polge, R. J.; Bhagavan, B. K.; Callas, L.

1973-01-01

The Earth Resources Technology Satellite system is studied, with emphasis on sensors, data processing requirements, and image data compression using the Fast Fourier and Hadamard transforms. The ERTS-A system and the fundamentals of remote sensing are discussed. Three user applications (forestry, crops, and rangelands) are selected and their spectral signatures are described. It is shown that additional sensors are needed for rangeland management. An on-board information processing system is recommended to reduce the amount of data transmitted.

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.

TIA Software User's Manual

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Syed, Hazari I.

1995-01-01

This user's manual describes the installation and operation of TIA, the Thermal-Imaging acquisition and processing Application, developed by the Nondestructive Evaluation Sciences Branch at NASA Langley Research Center, Hampton, Virginia. TIA is a user friendly graphical interface application for the Macintosh 2 and higher series computers. The software has been developed to interface with the Perceptics/Westinghouse Pixelpipe(TM) and PixelStore(TM) NuBus cards and the GW Instruments MacADIOS(TM) input-output (I/O) card for the Macintosh for imaging thermal data. The software is also capable of performing generic image-processing functions.

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

NASA Astrophysics Data System (ADS)

Laura, Jason; Rodriguez, Kelvin; Paquette, Adam C.; Dunn, Evin

2018-01-01

In this work we describe the AutoCNet library, written in Python, to support the application of computer vision techniques for n-image correspondence identification in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

Spatial Data Exploring by Satellite Image Distributed Processing

NASA Astrophysics Data System (ADS)

Mihon, V. D.; Colceriu, V.; Bektas, F.; Allenbach, K.; Gvilava, M.; Gorgan, D.

2012-04-01

Our society needs and environmental predictions encourage the applications development, oriented on supervising and analyzing different Earth Science related phenomena. Satellite images could be explored for discovering information concerning land cover, hydrology, air quality, and water and soil pollution. Spatial and environment related data could be acquired by imagery classification consisting of data mining throughout the multispectral bands. The process takes in account a large set of variables such as satellite image types (e.g. MODIS, Landsat), particular geographic area, soil composition, vegetation cover, and generally the context (e.g. clouds, snow, and season). All these specific and variable conditions require flexible tools and applications to support an optimal search for the appropriate solutions, and high power computation resources. The research concerns with experiments on solutions of using the flexible and visual descriptions of the satellite image processing over distributed infrastructures (e.g. Grid, Cloud, and GPU clusters). This presentation highlights the Grid based implementation of the GreenLand application. The GreenLand application development is based on simple, but powerful, notions of mathematical operators and workflows that are used in distributed and parallel executions over the Grid infrastructure. Currently it is used in three major case studies concerning with Istanbul geographical area, Rioni River in Georgia, and Black Sea catchment region. The GreenLand application offers a friendly user interface for viewing and editing workflows and operators. The description involves the basic operators provided by GRASS [1] library as well as many other image related operators supported by the ESIP platform [2]. The processing workflows are represented as directed graphs giving the user a fast and easy way to describe complex parallel algorithms, without having any prior knowledge of any programming language or application commands. Also this Web application does not require any kind of install for what the house-hold user is concerned. It is a remote application which may be accessed over the Internet. Currently the GreenLand application is available through the BSC-OS Portal provided by the enviroGRIDS FP7 project [3]. This presentation aims to highlight the challenges and issues of flexible description of the Grid based processing of satellite images, interoperability with other software platforms available in the portal, as well as the particular requirements of the Black Sea related use cases.

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.

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-based information, communication, and retrieval

NASA Technical Reports Server (NTRS)

Bryant, N. A.; Zobrist, A. L.

1980-01-01

IBIS/VICAR system combines video image processing and information management. Flexible programs require user to supply only parameters specific to particular application. Special-purpose input/output routines transfer image data with reduced memory requirements. New application programs are easily incorporated. Program is written in FORTRAN IV, Assembler, and OS JCL for batch execution and has been implemented on IBM 360.

Clinical Applications of a CT Window Blending Algorithm: RADIO (Relative Attenuation-Dependent Image Overlay).

PubMed

Mandell, Jacob C; Khurana, Bharti; Folio, Les R; Hyun, Hyewon; Smith, Stacy E; Dunne, Ruth M; Andriole, Katherine P

2017-06-01

A methodology is described using Adobe Photoshop and Adobe Extendscript to process DICOM images with a Relative Attenuation-Dependent Image Overlay (RADIO) algorithm to visualize the full dynamic range of CT in one view, without requiring a change in window and level settings. The potential clinical uses for such an algorithm are described in a pictorial overview, including applications in emergency radiology, oncologic imaging, and nuclear medicine and molecular imaging.

A new programming metaphor for image processing procedures

NASA Technical Reports Server (NTRS)

Smirnov, O. M.; Piskunov, N. E.

1992-01-01

Most image processing systems, besides an Application Program Interface (API) which lets users write their own image processing programs, also feature a higher level of programmability. Traditionally, this is a command or macro language, which can be used to build large procedures (scripts) out of simple programs or commands. This approach, a legacy of the teletypewriter has serious drawbacks. A command language is clumsy when (and if! it attempts to utilize the capabilities of a multitasking or multiprocessor environment, it is but adequate for real-time data acquisition and processing, it has a fairly steep learning curve, and the user interface is very inefficient,. especially when compared to a graphical user interface (GUI) that systems running under Xll or Windows should otherwise be able to provide. ll these difficulties stem from one basic problem: a command language is not a natural metaphor for an image processing procedure. A more natural metaphor - an image processing factory is described in detail. A factory is a set of programs (applications) that execute separate operations on images, connected by pipes that carry data (images and parameters) between them. The programs function concurrently, processing images as they arrive along pipes, and querying the user for whatever other input they need. From the user's point of view, programming (constructing) factories is a lot like playing with LEGO blocks - much more intuitive than writing scripts. Focus is on some of the difficulties of implementing factory support, most notably the design of an appropriate API. It also shows that factories retain all the functionality of a command language (including loops and conditional branches), while suffering from none of the drawbacks outlined above. Other benefits of factory programming include self-tuning factories and the process of encapsulation, which lets a factory take the shape of a standard application both from the system and the user's point of view, and thus be used as a component of other factories. A bare-bones prototype of factory programming was implemented under the PcIPS image processing system, and a complete version (on a multitasking platform) is under development.

Interpretation of medical imaging data with a mobile application: a mobile digital imaging processing environment.

PubMed

Lin, Meng Kuan; Nicolini, Oliver; Waxenegger, Harald; Galloway, Graham J; Ullmann, Jeremy F P; Janke, Andrew L

2013-01-01

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users' expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

Interpretation of Medical Imaging Data with a Mobile Application: A Mobile Digital Imaging Processing Environment

PubMed Central

Lin, Meng Kuan; Nicolini, Oliver; Waxenegger, Harald; Galloway, Graham J.; Ullmann, Jeremy F. P.; Janke, Andrew L.

2013-01-01

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users’ expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services. PMID:23847587

Document Examination: Applications of Image Processing Systems.

PubMed

Kopainsky, B

1989-12-01

Dealing with images is a familiar business for an expert in questioned documents: microscopic, photographic, infrared, and other optical techniques generate images containing the information he or she is looking for. A recent method for extracting most of this information is digital image processing, ranging from the simple contrast and contour enhancement to the advanced restoration of blurred texts. When combined with a sophisticated physical imaging system, an image pricessing system has proven to be a powerful and fast tool for routine non-destructive scanning of suspect documents. This article reviews frequent applications, comprising techniques to increase legibility, two-dimensional spectroscopy (ink discrimination, alterations, erased entries, etc.), comparison techniques (stamps, typescript letters, photo substitution), and densitometry. Computerized comparison of handwriting is not included. Copyright © 1989 Central Police University.

Medical image informatics infrastructure design and applications.

PubMed

Huang, H K; Wong, S T; Pietka, E

1997-01-01

Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications

PubMed Central

Sechopoulos, Ioannis

2013-01-01

Many important post-acquisition aspects of breast tomosynthesis imaging can impact its clinical performance. Chief among them is the reconstruction algorithm that generates the representation of the three-dimensional breast volume from the acquired projections. But even after reconstruction, additional processes, such as artifact reduction algorithms, computer aided detection and diagnosis, among others, can also impact the performance of breast tomosynthesis in the clinical realm. In this two part paper, a review of breast tomosynthesis research is performed, with an emphasis on its medical physics aspects. In the companion paper, the first part of this review, the research performed relevant to the image acquisition process is examined. This second part will review the research on the post-acquisition aspects, including reconstruction, image processing, and analysis, as well as the advanced applications being investigated for breast tomosynthesis. PMID:23298127

Data management in pattern recognition and image processing systems

NASA Technical Reports Server (NTRS)

Zobrist, A. L.; Bryant, N. A.

1976-01-01

Data management considerations are important to any system which handles large volumes of data or where the manipulation of data is technically sophisticated. A particular problem is the introduction of image-formatted files into the mainstream of data processing application. This report describes a comprehensive system for the manipulation of image, tabular, and graphical data sets which involve conversions between the various data types. A key characteristic is the use of image processing technology to accomplish data management tasks. Because of this, the term 'image-based information system' has been adopted.

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.

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

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.

OIPAV: an integrated software system for ophthalmic image processing, analysis and visualization

NASA Astrophysics Data System (ADS)

Zhang, Lichun; Xiang, Dehui; Jin, Chao; Shi, Fei; Yu, Kai; Chen, Xinjian

2018-03-01

OIPAV (Ophthalmic Images Processing, Analysis and Visualization) is a cross-platform software which is specially oriented to ophthalmic images. It provides a wide range of functionalities including data I/O, image processing, interaction, ophthalmic diseases detection, data analysis and visualization to help researchers and clinicians deal with various ophthalmic images such as optical coherence tomography (OCT) images and color photo of fundus, etc. It enables users to easily access to different ophthalmic image data manufactured from different imaging devices, facilitate workflows of processing ophthalmic images and improve quantitative evaluations. In this paper, we will present the system design and functional modules of the platform and demonstrate various applications. With a satisfying function scalability and expandability, we believe that the software can be widely applied in ophthalmology field.

Near Real-Time Image Reconstruction

NASA Astrophysics Data System (ADS)

Denker, C.; Yang, G.; Wang, H.

2001-08-01

In recent years, post-facto image-processing algorithms have been developed to achieve diffraction-limited observations of the solar surface. We present a combination of frame selection, speckle-masking imaging, and parallel computing which provides real-time, diffraction-limited, 256×256 pixel images at a 1-minute cadence. Our approach to achieve diffraction limited observations is complementary to adaptive optics (AO). At the moment, AO is limited by the fact that it corrects wavefront abberations only for a field of view comparable to the isoplanatic patch. This limitation does not apply to speckle-masking imaging. However, speckle-masking imaging relies on short-exposure images which limits its spectroscopic applications. The parallel processing of the data is performed on a Beowulf-class computer which utilizes off-the-shelf, mass-market technologies to provide high computational performance for scientific calculations and applications at low cost. Beowulf computers have a great potential, not only for image reconstruction, but for any kind of complex data reduction. Immediate access to high-level data products and direct visualization of dynamic processes on the Sun are two of the advantages to be gained.

Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities.

PubMed

Buckler, Andrew J; Bresolin, Linda; Dunnick, N Reed; Sullivan, Daniel C; Aerts, Hugo J W L; Bendriem, Bernard; Bendtsen, Claus; Boellaard, Ronald; Boone, John M; Cole, Patricia E; Conklin, James J; Dorfman, Gary S; Douglas, Pamela S; Eidsaunet, Willy; Elsinger, Cathy; Frank, Richard A; Gatsonis, Constantine; Giger, Maryellen L; Gupta, Sandeep N; Gustafson, David; Hoekstra, Otto S; Jackson, Edward F; Karam, Lisa; Kelloff, Gary J; Kinahan, Paul E; McLennan, Geoffrey; Miller, Colin G; Mozley, P David; Muller, Keith E; Patt, Rick; Raunig, David; Rosen, Mark; Rupani, Haren; Schwartz, Lawrence H; Siegel, Barry A; Sorensen, A Gregory; Wahl, Richard L; Waterton, John C; Wolf, Walter; Zahlmann, Gudrun; Zimmerman, Brian

2011-06-01

Quantitative imaging biomarkers could speed the development of new treatments for unmet medical needs and improve routine clinical care. However, it is not clear how the various regulatory and nonregulatory (eg, reimbursement) processes (often referred to as pathways) relate, nor is it clear which data need to be collected to support these different pathways most efficiently, given the time- and cost-intensive nature of doing so. The purpose of this article is to describe current thinking regarding these pathways emerging from diverse stakeholders interested and active in the definition, validation, and qualification of quantitative imaging biomarkers and to propose processes to facilitate the development and use of quantitative imaging biomarkers. A flexible framework is described that may be adapted for each imaging application, providing mechanisms that can be used to develop, assess, and evaluate relevant biomarkers. From this framework, processes can be mapped that would be applicable to both imaging product development and to quantitative imaging biomarker development aimed at increasing the effectiveness and availability of quantitative imaging. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100800/-/DC1. RSNA, 2011

A novel configurable VLSI architecture design of window-based image processing method

NASA Astrophysics Data System (ADS)

Zhao, Hui; Sang, Hongshi; Shen, Xubang

2018-03-01

Most window-based image processing architecture can only achieve a certain kind of specific algorithms, such as 2D convolution, and therefore lack the flexibility and breadth of application. In addition, improper handling of the image boundary can cause loss of accuracy, or consume more logic resources. For the above problems, this paper proposes a new VLSI architecture of window-based image processing operations, which is configurable and based on consideration of the image boundary. An efficient technique is explored to manage the image borders by overlapping and flushing phases at the end of row and the end of frame, which does not produce new delay and reduce the overhead in real-time applications. Maximize the reuse of the on-chip memory data, in order to reduce the hardware complexity and external bandwidth requirements. To perform different scalar function and reduction function operations in pipeline, this can support a variety of applications of window-based image processing. Compared with the performance of other reported structures, the performance of the new structure has some similarities to some of the structures, but also superior to some other structures. Especially when compared with a systolic array processor CWP, this structure at the same frequency of approximately 12.9% of the speed increases. The proposed parallel VLSI architecture was implemented with SIMC 0.18-μm CMOS technology, and the maximum clock frequency, power consumption, and area are 125Mhz, 57mW, 104.8K Gates, respectively, furthermore the processing time is independent of the different window-based algorithms mapped to the structure

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.

Medical Imaging System

NASA Technical Reports Server (NTRS)

1991-01-01

The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

Intelligent Vision On The SM9O Mini-Computer Basis And Applications

NASA Astrophysics Data System (ADS)

Hawryszkiw, J.

1985-02-01

Distinction has to be made between image processing and vision Image processing finds its roots in the strong tradition of linear signal processing and promotes geometrical transform techniques, such as fi I tering , compression, and restoration. Its purpose is to transform an image for a human observer to easily extract from that image information significant for him. For example edges after a gradient operator, or a specific direction after a directional filtering operation. Image processing consists in fact in a set of local or global space-time transforms. The interpretation of the final image is done by the human observer. The purpose of vision is to extract the semantic content of the image. The machine can then understand that content, and run a process of decision, which turns into an action. Thus, intel I i gent vision depends on - Image processing - Pattern recognition - Artificial intel I igence

Interactive brain shift compensation using GPU based programming

NASA Astrophysics Data System (ADS)

van der Steen, Sander; Noordmans, Herke Jan; Verdaasdonk, Rudolf

2009-02-01

Processing large images files or real-time video streams requires intense computational power. Driven by the gaming industry, the processing power of graphic process units (GPUs) has increased significantly. With the pixel shader model 4.0 the GPU can be used for image processing 10x faster than the CPU. Dedicated software was developed to deform 3D MR and CT image sets for real-time brain shift correction during navigated neurosurgery using landmarks or cortical surface traces defined by the navigation pointer. Feedback was given using orthogonal slices and an interactively raytraced 3D brain image. GPU based programming enables real-time processing of high definition image datasets and various applications can be developed in medicine, optics and image sciences.

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.

The PICWidget

NASA Technical Reports Server (NTRS)

Norris, Jeffrey; Fox, Jason; Rabe, Kenneth; Shu, I-Hsiang; Powell, Mark

2007-01-01

The Plug-in Image Component Widget (PICWidget) is a software component for building digital imaging applications. The component is part of a methodology described in GIS Methodology for Planning Planetary-Rover Operations (NPO-41812), which appears elsewhere in this issue of NASA Tech Briefs. Planetary rover missions return a large number and wide variety of image data products that vary in complexity in many ways. Supported by a powerful, flexible image-data-processing pipeline, the PICWidget can process and render many types of imagery, including (but not limited to) thumbnail, subframed, downsampled, stereoscopic, and mosaic images; images coregistred with orbital data; and synthetic red/green/blue images. The PICWidget is capable of efficiently rendering images from data representing many more pixels than are available at a computer workstation where the images are to be displayed. The PICWidget is implemented as an Eclipse plug-in using the Standard Widget Toolkit, which provides a straightforward interface for re-use of the PICWidget in any number of application programs built upon the Eclipse application framework. Because the PICWidget is tile-based and performs aggressive tile caching, it has flexibility to perform faster or slower, depending whether more or less memory is available.

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Visual Attention and Applications in Multimedia Technologies

PubMed Central

Le Callet, Patrick; Niebur, Ernst

2013-01-01

Making technological advances in the field of human-machine interactions requires that the capabilities and limitations of the human perceptual system are taken into account. The focus of this report is an important mechanism of perception, visual selective attention, which is becoming more and more important for multimedia applications. We introduce the concept of visual attention and describe its underlying mechanisms. In particular, we introduce the concepts of overt and covert visual attention, and of bottom-up and top-down processing. Challenges related to modeling visual attention and their validation using ad hoc ground truth are also discussed. Examples of the usage of visual attention models in image and video processing are presented. We emphasize multimedia delivery, retargeting and quality assessment of image and video, medical imaging, and the field of stereoscopic 3D images applications. PMID:24489403

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

USGS Publications Warehouse

Maxwell, S.K.; Schmidt, Gail L.; Storey, James C.

2007-01-01

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Computerized image analysis for acetic acid induced intraepithelial lesions

NASA Astrophysics Data System (ADS)

Li, Wenjing; Ferris, Daron G.; Lieberman, Rich W.

2008-03-01

Cervical Intraepithelial Neoplasia (CIN) exhibits certain morphologic features that can be identified during a visual inspection exam. Immature and dysphasic cervical squamous epithelium turns white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively discriminates between dysphasic and normal tissue. Digital imaging technologies allow us to assist the physician analyzing the acetic acid induced lesions (acetowhite region) in a fully automatic way. This paper reports a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post acetic acid image; the temporal change is extracted from the intensity and color changes between the post acetic acid and pre acetic acid images with an automatic alignment. The imaging and data analysis system has been evaluated with a total of 99 human subjects and demonstrate its potential to screening underserved women where access to skilled colposcopists is limited.

Commercial applications for optical data storage

NASA Astrophysics Data System (ADS)

Tas, Jeroen

1991-03-01

Optical data storage has spurred the market for document imaging systems. These systems are increasingly being used to electronically manage the processing, storage and retrieval of documents. Applications range from straightforward archives to sophisticated workflow management systems. The technology is developing rapidly and within a few years optical imaging facilities will be incorporated in most of the office information systems. This paper gives an overview of the status of the market, the applications and the trends of optical imaging systems.

Client/server approach to image capturing

NASA Astrophysics Data System (ADS)

Tuijn, Chris; Stokes, Earle

1998-01-01

The diversity of the digital image capturing devices on the market today is quite astonishing and ranges from low-cost CCD scanners to digital cameras (for both action and stand-still scenes), mid-end CCD scanners for desktop publishing and pre- press applications and high-end CCD flatbed scanners and drum- scanners with photo multiplier technology. Each device and market segment has its own specific needs which explains the diversity of the associated scanner applications. What all those applications have in common is the need to communicate with a particular device to import the digital images; after the import, additional image processing might be needed as well as color management operations. Although the specific requirements for all of these applications might differ considerably, a number of image capturing and color management facilities as well as other services are needed which can be shared. In this paper, we propose a client/server architecture for scanning and image editing applications which can be used as a common component for all these applications. One of the principal components of the scan server is the input capturing module. The specification of the input jobs is based on a generic input device model. Through this model we make abstraction of the specific scanner parameters and define the scan job definitions by a number of absolute parameters. As a result, scan job definitions will be less dependent on a particular scanner and have a more universal meaning. In this context, we also elaborate on the interaction of the generic parameters and the color characterization (i.e., the ICC profile). Other topics that are covered are the scheduling and parallel processing capabilities of the server, the image processing facilities, the interaction with the ICC engine, the communication facilities (both in-memory and over the network) and the different client architectures (stand-alone applications, TWAIN servers, plug-ins, OLE or Apple-event driven applications). This paper is structured as follows. In the introduction, we further motive the need for a scan server-based architecture. In the second section, we give a brief architectural overview of the scan server and the other components it is connected to. The third chapter exposes the generic model for input devices as well as the image processing model; the fourth chapter reveals the different shapes the scanning applications (or modules) can have. In the last section, we briefly summarize the presented material and point out trends for future development.

Image wavelet decomposition and applications

NASA Technical Reports Server (NTRS)

Treil, N.; Mallat, S.; Bajcsy, R.

1989-01-01

The general problem of computer vision has been investigated for more that 20 years and is still one of the most challenging fields in artificial intelligence. Indeed, taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. An example of low level signal and image processing using the theory of wavelets is introduced which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, images of the same orientation but of different resolutions are contrasted to gather information about an image. An interesting image representation using energy zero crossings is developed. This representation is shown to be experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. The possibilities of feedback between different levels of processing are also discussed.

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.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Application of an enhanced fuzzy algorithm for MR brain tumor image segmentation

NASA Astrophysics Data System (ADS)

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

2010-02-01

Image segmentation is one of the significant digital image processing techniques commonly used in the medical field. One of the specific applications is tumor detection in abnormal Magnetic Resonance (MR) brain images. Fuzzy approaches are widely preferred for tumor segmentation which generally yields superior results in terms of accuracy. But most of the fuzzy algorithms suffer from the drawback of slow convergence rate which makes the system practically non-feasible. In this work, the application of modified Fuzzy C-means (FCM) algorithm to tackle the convergence problem is explored in the context of brain image segmentation. This modified FCM algorithm employs the concept of quantization to improve the convergence rate besides yielding excellent segmentation efficiency. This algorithm is experimented on real time abnormal MR brain images collected from the radiologists. A comprehensive feature vector is extracted from these images and used for the segmentation technique. An extensive feature selection process is performed which reduces the convergence time period and improve the segmentation efficiency. After segmentation, the tumor portion is extracted from the segmented image. Comparative analysis in terms of segmentation efficiency and convergence rate is performed between the conventional FCM and the modified FCM. Experimental results show superior results for the modified FCM algorithm in terms of the performance measures. Thus, this work highlights the application of the modified algorithm for brain tumor detection in abnormal MR brain images.

Unsupervised Detection of Planetary Craters by a Marked Point Process

NASA Technical Reports Server (NTRS)

Troglio, G.; Benediktsson, J. A.; Le Moigne, J.; Moser, G.; Serpico, S. B.

2011-01-01

With the launch of several planetary missions in the last decade, a large amount of planetary images is being acquired. Preferably, automatic and robust processing techniques need to be used for data analysis because of the huge amount of the acquired data. Here, the aim is to achieve a robust and general methodology for crater detection. A novel technique based on a marked point process is proposed. First, the contours in the image are extracted. The object boundaries are modeled as a configuration of an unknown number of random ellipses, i.e., the contour image is considered as a realization of a marked point process. Then, an energy function is defined, containing both an a priori energy and a likelihood term. The global minimum of this function is estimated by using reversible jump Monte-Carlo Markov chain dynamics and a simulated annealing scheme. The main idea behind marked point processes is to model objects within a stochastic framework: Marked point processes represent a very promising current approach in the stochastic image modeling and provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. The proposed method for crater detection has several feasible applications. One such application area is image registration by matching the extracted features.

Rudiments of curvelet with applications

NASA Astrophysics Data System (ADS)

Zahra, Noor e.

2012-07-01

Curvelet transform is now a days a favored tool for image processing. Edges are an important part of an image and usually they are not straight lines. Curvelet prove to be very efficient in representing curve like edges. In this chapter application of curvelet is shown with some examples like seismic wave analysis, oil exploration, fingerprint identification and biomedical images like mammography and MRI.

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate ( C'' or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability bymore » using DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate (``C`` or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability by usingmore » DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

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.

Recent Applications of Neutron Imaging Methods

NASA Astrophysics Data System (ADS)

Lehmann, E.; Mannes, D.; Kaestner, A.; Grünzweig, C.

The methodical progress in the field of neutron imaging is visible in general but on different levels in the particular labs. Consequently, the access to most suitable beam ports, the usage of advanced imaging detector systems and the professional image processing made the technique competitive to other non-destructive tools like X-ray imaging. Based on this performance gain and by new methodical approaches several new application fields came up - in addition to the already established ones. Accordingly, new image data are now mostly in the third dimension available in the format of tomography volumes. The radiography mode is still the basis of neutron imaging, but the extracted information from superimposed image data (like for a grating interferometer) enables completely new insights. In the consequence, many new applications were created.

Advances in feature selection methods for hyperspectral image processing in food industry applications: a review.

PubMed

Dai, Qiong; Cheng, Jun-Hu; Sun, Da-Wen; Zeng, Xin-An

2015-01-01

There is an increased interest in the applications of hyperspectral imaging (HSI) for assessing food quality, safety, and authenticity. HSI provides abundance of spatial and spectral information from foods by combining both spectroscopy and imaging, resulting in hundreds of contiguous wavebands for each spatial position of food samples, also known as the curse of dimensionality. It is desirable to employ feature selection algorithms for decreasing computation burden and increasing predicting accuracy, which are especially relevant in the development of online applications. Recently, a variety of feature selection algorithms have been proposed that can be categorized into three groups based on the searching strategy namely complete search, heuristic search and random search. This review mainly introduced the fundamental of each algorithm, illustrated its applications in hyperspectral data analysis in the food field, and discussed the advantages and disadvantages of these algorithms. It is hoped that this review should provide a guideline for feature selections and data processing in the future development of hyperspectral imaging technique in foods.

ASAP (Automatic Software for ASL Processing): A toolbox for processing Arterial Spin Labeling images.

PubMed

Mato Abad, Virginia; García-Polo, Pablo; O'Daly, Owen; Hernández-Tamames, Juan Antonio; Zelaya, Fernando

2016-04-01

The method of Arterial Spin Labeling (ASL) has experienced a significant rise in its application to functional imaging, since it is the only technique capable of measuring blood perfusion in a truly non-invasive manner. Currently, there are no commercial packages for processing ASL data and there is no recognized standard for normalizing ASL data to a common frame of reference. This work describes a new Automated Software for ASL Processing (ASAP) that can automatically process several ASL datasets. ASAP includes functions for all stages of image pre-processing: quantification, skull-stripping, co-registration, partial volume correction and normalization. To assess the applicability and validity of the toolbox, this work shows its application in the study of hypoperfusion in a sample of healthy subjects at risk of progressing to Alzheimer's disease. ASAP requires limited user intervention, minimizing the possibility of random and systematic errors, and produces cerebral blood flow maps that are ready for statistical group analysis. The software is easy to operate and results in excellent quality of spatial normalization. The results found in this evaluation study are consistent with previous studies that find decreased perfusion in Alzheimer's patients in similar regions and demonstrate the applicability of ASAP. Copyright © 2015 Elsevier Inc. All rights reserved.

Improvement of passive THz camera images

NASA Astrophysics Data System (ADS)

Kowalski, Marcin; Piszczek, Marek; Palka, Norbert; Szustakowski, Mieczyslaw

2012-10-01

Terahertz technology is one of emerging technologies that has a potential to change our life. There are a lot of attractive applications in fields like security, astronomy, biology and medicine. Until recent years, terahertz (THz) waves were an undiscovered, or most importantly, an unexploited area of electromagnetic spectrum. The reasons of this fact were difficulties in generation and detection of THz waves. Recent advances in hardware technology have started to open up the field to new applications such as THz imaging. The THz waves can penetrate through various materials. However, automated processing of THz images can be challenging. The THz frequency band is specially suited for clothes penetration because this radiation does not point any harmful ionizing effects thus it is safe for human beings. Strong technology development in this band have sparked with few interesting devices. Even if the development of THz cameras is an emerging topic, commercially available passive cameras still offer images of poor quality mainly because of its low resolution and low detectors sensitivity. Therefore, THz image processing is very challenging and urgent topic. Digital THz image processing is a really promising and cost-effective way for demanding security and defense applications. In the article we demonstrate the results of image quality enhancement and image fusion of images captured by a commercially available passive THz camera by means of various combined methods. Our research is focused on dangerous objects detection - guns, knives and bombs hidden under some popular types of clothing.

Secure Display of Space-Exploration Images

NASA Technical Reports Server (NTRS)

Cheng, Cecilia; Thornhill, Gillian; McAuley, Michael

2006-01-01

Java EDR Display Interface (JEDI) is software for either local display or secure Internet distribution, to authorized clients, of image data acquired from cameras aboard spacecraft engaged in exploration of remote planets. ( EDR signifies experimental data record, which, in effect, signifies image data.) Processed at NASA s Multimission Image Processing Laboratory (MIPL), the data can be from either near-realtime processing streams or stored files. JEDI uses the Java Advanced Imaging application program interface, plus input/output packages that are parts of the Video Image Communication and Retrieval software of the MIPL, to display images. JEDI can be run as either a standalone application program or within a Web browser as a servlet with an applet front end. In either operating mode, JEDI communicates using the HTTP(s) protocol(s). In the Web-browser case, the user must provide a password to gain access. For each user and/or image data type, there is a configuration file, called a "personality file," containing parameters that control the layout of the displays and the information to be included in them. Once JEDI has accepted the user s password, it processes the requested EDR (provided that user is authorized to receive the specific EDR) to create a display according to the user s personality file.

Industrial applications of automated X-ray inspection

NASA Astrophysics Data System (ADS)

Shashishekhar, N.

2015-03-01

Many industries require that 100% of manufactured parts be X-ray inspected. Factors such as high production rates, focus on inspection quality, operator fatigue and inspection cost reduction translate to an increasing need for automating the inspection process. Automated X-ray inspection involves the use of image processing algorithms and computer software for analysis and interpretation of X-ray images. This paper presents industrial applications and illustrative case studies of automated X-ray inspection in areas such as automotive castings, fuel plates, air-bag inflators and tires. It is usually necessary to employ application-specific automated inspection strategies and techniques, since each application has unique characteristics and interpretation requirements.

Analysis of objects in binary images. M.S. Thesis - Old Dominion Univ.

NASA Technical Reports Server (NTRS)

Leonard, Desiree M.

1991-01-01

Digital image processing techniques are typically used to produce improved digital images through the application of successive enhancement techniques to a given image or to generate quantitative data about the objects within that image. In support of and to assist researchers in a wide range of disciplines, e.g., interferometry, heavy rain effects on aerodynamics, and structure recognition research, it is often desirable to count objects in an image and compute their geometric properties. Therefore, an image analysis application package, focusing on a subset of image analysis techniques used for object recognition in binary images, was developed. This report describes the techniques and algorithms utilized in three main phases of the application and are categorized as: image segmentation, object recognition, and quantitative analysis. Appendices provide supplemental formulas for the algorithms employed as well as examples and results from the various image segmentation techniques and the object recognition algorithm implemented.

Image processing for optical mapping.

PubMed

Ravindran, Prabu; Gupta, Aditya

2015-01-01

Optical Mapping is an established single-molecule, whole-genome analysis system, which has been used to gain a comprehensive understanding of genomic structure and to study structural variation of complex genomes. A critical component of Optical Mapping system is the image processing module, which extracts single molecule restriction maps from image datasets of immobilized, restriction digested and fluorescently stained large DNA molecules. In this review, we describe robust and efficient image processing techniques to process these massive datasets and extract accurate restriction maps in the presence of noise, ambiguity and confounding artifacts. We also highlight a few applications of the Optical Mapping system.

Introduction to Remote Sensing Image Registration

NASA Technical Reports Server (NTRS)

Le Moigne, Jacqueline

2017-01-01

For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a prior information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications

[Bone drilling simulation by three-dimensional imaging].

PubMed

Suto, Y; Furuhata, K; Kojima, T; Kurokawa, T; Kobayashi, M

1989-06-01

The three-dimensional display technique has a wide range of medical applications. Pre-operative planning is one typical application: in orthopedic surgery, three-dimensional image processing has been used very successfully. We have employed this technique in pre-operative planning for orthopedic surgery, and have developed a simulation system for bone-drilling. Positive results were obtained by pre-operative rehearsal; when a region of interest is indicated by means of a mouse on the three-dimensional image displayed on the CRT, the corresponding region appears on the slice image which is displayed simultaneously. Consequently, the status of the bone-drilling is constantly monitored. In developing this system, we have placed emphasis on the quality of the reconstructed three-dimensional images, on fast processing, and on the easy operation of the surgical planning simulation.

Bayesian multi-scale smoothing of photon-limited images with applications to astronomy and medicine

NASA Astrophysics Data System (ADS)

White, John

Multi-scale models for smoothing Poisson signals or images have gained much attention over the past decade. A new Bayesian model is developed using the concept of the Chinese restaurant process to find structures in two-dimensional images when performing image reconstruction or smoothing. This new model performs very well when compared to other leading methodologies for the same problem. It is developed and evaluated theoretically and empirically throughout Chapter 2. The newly developed Bayesian model is extended to three-dimensional images in Chapter 3. The third dimension has numerous different applications, such as different energy spectra, another spatial index, or possibly a temporal dimension. Empirically, this method shows promise in reducing error with the use of simulation studies. A further development removes background noise in the image. This removal can further reduce the error and is done using a modeling adjustment and post-processing techniques. These details are given in Chapter 4. Applications to real world problems are given throughout. Photon-based images are common in astronomical imaging due to the collection of different types of energy such as X-Rays. Applications to real astronomical images are given, and these consist of X-ray images from the Chandra X-ray observatory satellite. Diagnostic medicine uses many types of imaging such as magnetic resonance imaging and computed tomography that can also benefit from smoothing techniques such as the one developed here. Reducing the amount of radiation a patient takes will make images more noisy, but this can be mitigated through the use of image smoothing techniques. Both types of images represent the potential real world use for these methods.

Realization of a single image haze removal system based on DaVinci DM6467T processor

NASA Astrophysics Data System (ADS)

Liu, Zhuang

2014-10-01

Video monitoring system (VMS) has been extensively applied in domains of target recognition, traffic management, remote sensing, auto navigation and national defence. However the VMS has a strong dependence on the weather, for instance, in foggy weather, the quality of images received by the VMS are distinct degraded and the effective range of VMS is also decreased. All in all, the VMS performs terribly in bad weather. Thus the research of fog degraded images enhancement has very high theoretical and practical application value. A design scheme of a fog degraded images enhancement system based on the TI DaVinci processor is presented in this paper. The main function of the referred system is to extract and digital cameras capture images and execute image enhancement processing to obtain a clear image. The processor used in this system is the dual core TI DaVinci DM6467T - ARM@500MHz+DSP@1GH. A MontaVista Linux operating system is running on the ARM subsystem which handles I/O and application processing. The DSP handles signal processing and the results are available to the ARM subsystem in shared memory.The system benefits from the DaVinci processor so that, with lower power cost and smaller volume, it provides the equivalent image processing capability of a X86 computer. The outcome shows that the system in this paper can process images at 25 frames per second on D1 resolution.

Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

ERIC Educational Resources Information Center

Tataw, Oben Moses

2013-01-01

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

Software for hyperspectral, joint photographic experts group (.JPG), portable network graphics (.PNG) and tagged image file format (.TIFF) segmentation

NASA Astrophysics Data System (ADS)

Bruno, L. S.; Rodrigo, B. P.; Lucio, A. de C. Jorge

2016-10-01

This paper presents a system developed by an application of a neural network Multilayer Perceptron for drone acquired agricultural image segmentation. This application allows a supervised user training the classes that will posteriorly be interpreted by neural network. These classes will be generated manually with pre-selected attributes in the application. After the attribute selection a segmentation process is made to allow the relevant information extraction for different types of images, RGB or Hyperspectral. The application allows extracting the geographical coordinates from the image metadata, geo referencing all pixels on the image. In spite of excessive memory consume on hyperspectral images regions of interest, is possible to perform segmentation, using bands chosen by user that can be combined in different ways to obtain different results.

MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

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

Eichel, Paul H.

2013-08-01

MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962more » leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.« less

Image databases: Problems and perspectives

NASA Technical Reports Server (NTRS)

Gudivada, V. Naidu

1989-01-01

With the increasing number of computer graphics, image processing, and pattern recognition applications, economical storage, efficient representation and manipulation, and powerful and flexible query languages for retrieval of image data are of paramount importance. These and related issues pertinent to image data bases are examined.

Segmentation of anatomical structures of the heart based on echocardiography

NASA Astrophysics Data System (ADS)

Danilov, V. V.; Skirnevskiy, I. P.; Gerget, O. M.

2017-01-01

Nowadays, many practical applications in the field of medical image processing require valid and reliable segmentation of images in the capacity of input data. Some of the commonly used imaging techniques are ultrasound, CT, and MRI. However, the main difference between the other medical imaging equipment and EchoCG is that it is safer, low cost, non-invasive and non-traumatic. Three-dimensional EchoCG is a non-invasive imaging modality that is complementary and supplementary to two-dimensional imaging and can be used to examine the cardiovascular function and anatomy in different medical settings. The challenging problems, presented by EchoCG image processing, such as speckle phenomena, noise, temporary non-stationarity of processes, unsharp boundaries, attenuation, etc. forced us to consider and compare existing methods and then to develop an innovative approach that can tackle the problems connected with clinical applications. Actual studies are related to the analysis and development of a cardiac parameters automatic detection system by EchoCG that will provide new data on the dynamics of changes in cardiac parameters and improve the accuracy and reliability of the diagnosis. Research study in image segmentation has highlighted the capabilities of image-based methods for medical applications. The focus of the research is both theoretical and practical aspects of the application of the methods. Some of the segmentation approaches can be interesting for the imaging and medical community. Performance evaluation is carried out by comparing the borders, obtained from the considered methods to those manually prescribed by a medical specialist. Promising results demonstrate the possibilities and the limitations of each technique for image segmentation problems. The developed approach allows: to eliminate errors in calculating the geometric parameters of the heart; perform the necessary conditions, such as speed, accuracy, reliability; build a master model that will be an indispensable assistant for operations on a beating heart.

Digital Image Processing Overview For Helmet Mounted Displays

NASA Astrophysics Data System (ADS)

Parise, Michael J.

1989-09-01

Digital image processing provides a means to manipulate an image and presents a user with a variety of display formats that are not available in the analog image processing environment. When performed in real time and presented on a Helmet Mounted Display, system capability and flexibility are greatly enhanced. The information content of a display can be increased by the addition of real time insets and static windows from secondary sensor sources, near real time 3-D imaging from a single sensor can be achieved, graphical information can be added, and enhancement techniques can be employed. Such increased functionality is generating a considerable amount of interest in the military and commercial markets. This paper discusses some of these image processing techniques and their applications.

Analysis of Variance in Statistical Image Processing

NASA Astrophysics Data System (ADS)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

2014-01-01

Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

PAT: From Western solid dosage forms to Chinese materia medica preparations using NIR-CI.

PubMed

Zhou, Luwei; Xu, Manfei; Wu, Zhisheng; Shi, Xinyuan; Qiao, Yanjiang

2016-01-01

Near-infrared chemical imaging (NIR-CI) is an emerging technology that combines traditional near-infrared spectroscopy with chemical imaging. Therefore, NIR-CI can extract spectral information from pharmaceutical products and simultaneously visualize the spatial distribution of chemical components. The rapid and non-destructive features of NIR-CI make it an attractive process analytical technology (PAT) for identifying and monitoring critical control parameters during the pharmaceutical manufacturing process. This review mainly focuses on the pharmaceutical applications of NIR-CI in each unit operation during the manufacturing processes, from the Western solid dosage forms to the Chinese materia medica preparations. Finally, future applications of chemical imaging in the pharmaceutical industry are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Quantitative optical diagnostics in pathology recognition and monitoring of tissue reaction to PDT

NASA Astrophysics Data System (ADS)

Kirillin, Mikhail; Shakhova, Maria; Meller, Alina; Sapunov, Dmitry; Agrba, Pavel; Khilov, Alexander; Pasukhin, Mikhail; Kondratieva, Olga; Chikalova, Ksenia; Motovilova, Tatiana; Sergeeva, Ekaterina; Turchin, Ilya; Shakhova, Natalia

2017-07-01

Optical coherence tomography (OCT) is currently actively introduced into clinical practice. Besides diagnostics, it can be efficiently employed for treatment monitoring allowing for timely correction of the treatment procedure. In monitoring of photodynamic therapy (PDT) traditionally employed fluorescence imaging (FI) can benefit from complementary use of OCT. Additional diagnostic efficiency can be derived from numerical processing of optical diagnostics data providing more information compared to visual evaluation. In this paper we report on application of OCT together with numerical processing for clinical diagnostic in gynecology and otolaryngology, for monitoring of PDT in otolaryngology and on OCT and FI applications in clinical and aesthetic dermatology. Image numerical processing and quantification provides increase in diagnostic accuracy. Keywords: optical coherence tomography, fluorescence imaging, photod

Architectures and algorithms for digital image processing; Proceedings of the Meeting, Cannes, France, December 5, 6, 1985

NASA Technical Reports Server (NTRS)

Duff, Michael J. B. (Editor); Siegel, Howard J. (Editor); Corbett, Francis J. (Editor)

1986-01-01

The conference presents papers on the architectures, algorithms, and applications of image processing. Particular attention is given to a very large scale integration system for image reconstruction from projections, a prebuffer algorithm for instant display of volume data, and an adaptive image sequence filtering scheme based on motion detection. Papers are also presented on a simple, direct practical method of sensing local motion and analyzing local optical flow, image matching techniques, and an automated biological dosimetry system.

A new automatic SAR-based flood mapping application hosted on the European Space Agency's grid processing on demand fast access to imagery environment

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Chini, Marco; Matgen, Patrick; Giustarini, Laura

2013-04-01

There is a clear need for developing innovative processing chains based on earth observation (EO) data to generate products supporting emergency response and flood management at a global scale. Here an automatic flood mapping application is introduced. The latter is currently hosted on the Grid Processing on Demand (G-POD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver flooded areas using both recent and historical acquisitions of SAR data in an operational framework. It is worth mentioning that the method can be applied to both medium and high resolution SAR images. The flood mapping application consists of two main blocks: 1) A set of query tools for selecting the "crisis image" and the optimal corresponding pre-flood "reference image" from the G-POD archive. 2) An algorithm for extracting flooded areas using the previously selected "crisis image" and "reference image". The proposed method is a hybrid methodology, which combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. The method is based on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Change detection with respect to a pre-flood reference image helps reducing over-detection of inundated areas. The algorithms are computationally efficient and operate with minimum data requirements, considering as input data a flood image and a reference image. Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate pre-flood reference image. Potential users will also be able to apply the implemented flood delineation algorithm. Case studies of several recent high magnitude flooding events (e.g. July 2007 Severn River flood, UK and March 2010 Red River flood, US) observed by high-resolution SAR sensors as well as airborne photography highlight advantages and limitations of the online application. A mid-term target is the exploitation of ESA SENTINEL 1 SAR data streams. In the long term it is foreseen to develop a potential extension of the application for systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis. On-going research activities investigate the usefulness of the method for mapping flood hazard at global scale using databases of historic SAR remote sensing-derived flood inundation maps.

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.

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.

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.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions.

PubMed

Jha, Abhinav K; Barrett, Harrison H; Frey, Eric C; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A

2015-09-21

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions

NASA Astrophysics Data System (ADS)

Jha, Abhinav K.; Barrett, Harrison H.; Frey, Eric C.; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A.

2015-09-01

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Advanced Digital Forensic and Steganalysis Methods

DTIC Science & Technology

2009-02-01

investigation is simultaneously cropped, scaled, and processed, extending the technology when the digital image is printed, developing technology capable ...or other common processing operations). TECNOLOGY APPLICATIONS 1. Determining the origin of digital images 2. Matching an image to a camera...Technology Transfer and Innovation Partnerships Division of Research P.O. Box 6000 State University of New York Binghamton, NY 13902-6000 Phone: 607-777

VIEW-Station software and its graphical user interface

NASA Astrophysics Data System (ADS)

Kawai, Tomoaki; Okazaki, Hiroshi; Tanaka, Koichiro; Tamura, Hideyuki

1992-04-01

VIEW-Station is a workstation-based image processing system which merges the state-of-the- art software environment of Unix with the computing power of a fast image processor. VIEW- Station has a hierarchical software architecture, which facilitates device independence when porting across various hardware configurations, and provides extensibility in the development of application systems. The core image computing language is V-Sugar. V-Sugar provides a set of image-processing datatypes and allows image processing algorithms to be simply expressed, using a functional notation. VIEW-Station provides a hardware independent window system extension called VIEW-Windows. In terms of GUI (Graphical User Interface) VIEW-Station has two notable aspects. One is to provide various types of GUI as visual environments for image processing execution. Three types of interpreters called (mu) V- Sugar, VS-Shell and VPL are provided. Users may choose whichever they prefer based on their experience and tasks. The other notable aspect is to provide facilities to create GUI for new applications on the VIEW-Station system. A set of widgets are available for construction of task-oriented GUI. A GUI builder called VIEW-Kid is developed for WYSIWYG interactive interface design.

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

3D image restoration for confocal microscopy: toward a wavelet deconvolution for the study of complex biological structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, Jacques; Le Calvez, Sophie; Ulfendahl, Mats

2000-05-01

Image restoration algorithms provide efficient tools for recovering part of the information lost in the imaging process of a microscope. We describe recent progress in the application of deconvolution to confocal microscopy. The point spread function of a Biorad-MRC1024 confocal microscope was measured under various imaging conditions, and used to process 3D-confocal images acquired in an intact preparation of the inner ear developed at Karolinska Institutet. Using these experiments we investigate the application of denoising methods based on wavelet analysis as a natural regularization of the deconvolution process. Within the Bayesian approach to image restoration, we compare wavelet denoising with the use of a maximum entropy constraint as another natural regularization method. Numerical experiments performed with test images show a clear advantage of the wavelet denoising approach, allowing to `cool down' the image with respect to the signal, while suppressing much of the fine-scale artifacts appearing during deconvolution due to the presence of noise, incomplete knowledge of the point spread function, or undersampling problems. We further describe a natural development of this approach, which consists of performing the Bayesian inference directly in the wavelet domain.

MIRIADS: miniature infrared imaging applications development system description and operation

NASA Astrophysics Data System (ADS)

Baxter, Christopher R.; Massie, Mark A.; McCarley, Paul L.; Couture, Michael E.

2001-10-01

A cooperative effort between the U.S. Air Force Research Laboratory, Nova Research, Inc., the Raytheon Infrared Operations (RIO) and Optics 1, Inc. has successfully produced a miniature infrared camera system that offers significant real-time signal and image processing capabilities by virtue of its modular design. This paper will present an operational overview of the system as well as results from initial testing of the 'Modular Infrared Imaging Applications Development System' (MIRIADS) configured as a missile early-warning detection system. The MIRIADS device can operate virtually any infrared focal plane array (FPA) that currently exists. Programmable on-board logic applies user-defined processing functions to the real-time digital image data for a variety of functions. Daughterboards may be plugged onto the system to expand the digital and analog processing capabilities of the system. A unique full hemispherical infrared fisheye optical system designed and produced by Optics 1, Inc. is utilized by the MIRIADS in a missile warning application to demonstrate the flexibility of the overall system to be applied to a variety of current and future AFRL missions.

4D megahertz optical coherence tomography (OCT): imaging and live display beyond 1 gigavoxel/sec (Conference Presentation)

NASA Astrophysics Data System (ADS)

Huber, Robert A.; Draxinger, Wolfgang; Wieser, Wolfgang; Kolb, Jan Philip; Pfeiffer, Tom; Karpf, Sebastian N.; Eibl, Matthias; Klein, Thomas

2016-03-01

Over the last 20 years, optical coherence tomography (OCT) has become a valuable diagnostic tool in ophthalmology with several 10,000 devices sold today. Other applications, like intravascular OCT in cardiology and gastro-intestinal imaging will follow. OCT provides 3-dimensional image data with microscopic resolution of biological tissue in vivo. In most applications, off-line processing of the acquired OCT-data is sufficient. However, for OCT applications like OCT aided surgical microscopes, for functional OCT imaging of tissue after a stimulus, or for interactive endoscopy an OCT engine capable of acquiring, processing and displaying large and high quality 3D OCT data sets at video rate is highly desired. We developed such a prototype OCT engine and demonstrate live OCT with 25 volumes per second at a size of 320x320x320 pixels. The computer processing load of more than 1.5 TFLOPS was handled by a GTX 690 graphics processing unit with more than 3000 stream processors operating in parallel. In the talk, we will describe the optics and electronics hardware as well as the software of the system in detail and analyze current limitations. The talk also focuses on new OCT applications, where such a system improves diagnosis and monitoring of medical procedures. The additional acquisition of hyperspectral stimulated Raman signals with the system will be discussed.

Improved detection of soma location and morphology in fluorescence microscopy images of neurons.

PubMed

Kayasandik, Cihan Bilge; Labate, Demetrio

2016-12-01

Automated detection and segmentation of somas in fluorescent images of neurons is a major goal in quantitative studies of neuronal networks, including applications of high-content-screenings where it is required to quantify multiple morphological properties of neurons. Despite recent advances in image processing targeted to neurobiological applications, existing algorithms of soma detection are often unreliable, especially when processing fluorescence image stacks of neuronal cultures. In this paper, we introduce an innovative algorithm for the detection and extraction of somas in fluorescent images of networks of cultured neurons where somas and other structures exist in the same fluorescent channel. Our method relies on a new geometrical descriptor called Directional Ratio and a collection of multiscale orientable filters to quantify the level of local isotropy in an image. To optimize the application of this approach, we introduce a new construction of multiscale anisotropic filters that is implemented by separable convolution. Extensive numerical experiments using 2D and 3D confocal images show that our automated algorithm reliably detects somas, accurately segments them, and separates contiguous ones. We include a detailed comparison with state-of-the-art existing methods to demonstrate that our algorithm is extremely competitive in terms of accuracy, reliability and computational efficiency. Our algorithm will facilitate the development of automated platforms for high content neuron image processing. A Matlab code is released open-source and freely available to the scientific community. Copyright © 2016 Elsevier B.V. All rights reserved.

Image Registration Workshop Proceedings

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline (Editor)

1997-01-01

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research.

The application of a novel optical SPM in biomedicine

NASA Astrophysics Data System (ADS)

Li, Yinli; Chen, Haibo; Wu, Shifa; Song, Linfeng; Zhang, Jian

2005-01-01

As an analysis tool, SPM has been broadly used in biomedicine in recent years, such as AFM and SNOM; they are effective instruments in detecting life nanostructures at atomic level. Atomic force and photon scanning tunneling microscope (AF/PSTM) is one of member of SPM, it can be used to obtain sample" optical and atomic fore images at once scanning, these images include the transmissivity image, reflection index image and topography image. This report mainly introduces the application of AF/PSTM in red blood membrane and the effect of different sample dealt with processes on the experiment result. The materials for preparing red cells membrane samples are anticoagulant blood, isotonic phosphatic buffer solution (PBS) and new two times distilled water. The images of AF/PSTM give real expression to the biology samples" fact despite of different sample dealt with processes, which prove that AF/PSTM suits to biology sample imaging. At the same time, the optical images and the topography image of AF/PSTM of the same sample are complementary with each other; this will make AF/PSTM a facile tool to analysis biologic samples" nanostructure. As another sample, this paper gives the application of AF/PSTM in immunoassay, the result shows that AF/PSTM is suit to analysis biologic sample, and it will become a new tool for biomedicine test.

Color engineering in the age of digital convergence

NASA Astrophysics Data System (ADS)

MacDonald, Lindsay W.

1998-09-01

Digital color imaging has developed over the past twenty years from specialized scientific applications into the mainstream of computing. In addition to the phenomenal growth of computer processing power and storage capacity, great advances have been made in the capabilities and cost-effectiveness of color imaging peripherals. The majority of imaging applications, including the graphic arts, video and film have made the transition from analogue to digital production methods. Digital convergence of computing, communications and television now heralds new possibilities for multimedia publishing and mobile lifestyles. Color engineering, the application of color science to the design of imaging products, is an emerging discipline that poses exciting challenges to the international color imaging community for training, research and standards.

Automatic Feature Extraction from Planetary Images

NASA Technical Reports Server (NTRS)

Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

2010-01-01

With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

Medical image processing on the GPU - past, present and future.

PubMed

Eklund, Anders; Dufort, Paul; Forsberg, Daniel; LaConte, Stephen M

2013-12-01

Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges. Copyright © 2013 Elsevier B.V. All rights reserved.

Ranging Apparatus and Method Implementing Stereo Vision System

NASA Technical Reports Server (NTRS)

Li, Larry C. (Inventor); Cox, Brian J. (Inventor)

1997-01-01

A laser-directed ranging system for use in telerobotics applications and other applications involving physically handicapped individuals. The ranging system includes a left and right video camera mounted on a camera platform, and a remotely positioned operator. The position of the camera platform is controlled by three servo motors to orient the roll axis, pitch axis and yaw axis of the video cameras, based upon an operator input such as head motion. A laser is provided between the left and right video camera and is directed by the user to point to a target device. The images produced by the left and right video cameras are processed to eliminate all background images except for the spot created by the laser. This processing is performed by creating a digital image of the target prior to illumination by the laser, and then eliminating common pixels from the subsequent digital image which includes the laser spot. The horizontal disparity between the two processed images is calculated for use in a stereometric ranging analysis from which range is determined.

USC orthogonal multiprocessor for image processing with neural networks

NASA Astrophysics Data System (ADS)

Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

1990-07-01

This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

New opportunities for quality enhancing of images captured by passive THz camera

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2014-10-01

As it is well-known, the passive THz camera allows seeing concealed object without contact with a person and this camera is non-dangerous for a person. Obviously, efficiency of using the passive THz camera depends on its temperature resolution. This characteristic specifies possibilities of the detection for concealed object: minimal size of the object; maximal distance of the detection; image quality. Computer processing of the THz image may lead to many times improving of the image quality without any additional engineering efforts. Therefore, developing of modern computer code for its application to THz images is urgent problem. Using appropriate new methods one may expect such temperature resolution which will allow to see banknote in pocket of a person without any real contact. Modern algorithms for computer processing of THz images allow also to see object inside the human body using a temperature trace on the human skin. This circumstance enhances essentially opportunity of passive THz camera applications for counterterrorism problems. We demonstrate opportunities, achieved at present time, for the detection both of concealed objects and of clothes components due to using of computer processing of images captured by passive THz cameras, manufactured by various companies. Another important result discussed in the paper consists in observation of both THz radiation emitted by incandescent lamp and image reflected from ceramic floorplate. We consider images produced by THz passive cameras manufactured by Microsemi Corp., and ThruVision Corp., and Capital Normal University (Beijing, China). All algorithms for computer processing of the THz images under consideration in this paper were developed by Russian part of author list. Keywords: THz wave, passive imaging camera, computer processing, security screening, concealed and forbidden objects, reflected image, hand seeing, banknote seeing, ceramic floorplate, incandescent lamp.

Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

NASA Astrophysics Data System (ADS)

Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

2016-04-01

The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

A new full-field digital mammography system with and without the use of an advanced post-processing algorithm: comparison of image quality and diagnostic performance.

PubMed

Ahn, Hye Shin; Kim, Sun Mi; Jang, Mijung; Yun, Bo La; Kim, Bohyoung; Ko, Eun Sook; Han, Boo-Kyung; Chang, Jung Min; Yi, Ann; Cho, Nariya; Moon, Woo Kyung; Choi, Hye Young

2014-01-01

To compare new full-field digital mammography (FFDM) with and without use of an advanced post-processing algorithm to improve image quality, lesion detection, diagnostic performance, and priority rank. During a 22-month period, we prospectively enrolled 100 cases of specimen FFDM mammography (Brestige®), which was performed alone or in combination with a post-processing algorithm developed by the manufacturer: group A (SMA), specimen mammography without application of "Mammogram enhancement ver. 2.0"; group B (SMB), specimen mammography with application of "Mammogram enhancement ver. 2.0". Two sets of specimen mammographies were randomly reviewed by five experienced radiologists. Image quality, lesion detection, diagnostic performance, and priority rank with regard to image preference were evaluated. Three aspects of image quality (overall quality, contrast, and noise) of the SMB were significantly superior to those of SMA (p < 0.05). SMB was significantly superior to SMA for visualizing calcifications (p < 0.05). Diagnostic performance, as evaluated by cancer score, was similar between SMA and SMB. SMB was preferred to SMA by four of the five reviewers. The post-processing algorithm may improve image quality with better image preference in FFDM than without use of the software.

Phase shifting white light interferometry using colour CCD for optical metrology and bio-imaging applications

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Pramanik, Manojit

2018-02-01

Phase shifting white light interferometry (PSWLI) has been widely used for optical metrology applications because of their precision, reliability, and versatility. White light interferometry using monochrome CCD makes the measurement process slow for metrology applications. WLI integrated with Red-Green-Blue (RGB) CCD camera is finding imaging applications in the fields optical metrology and bio-imaging. Wavelength dependent refractive index profiles of biological samples were computed from colour white light interferograms. In recent years, whole-filed refractive index profiles of red blood cells (RBCs), onion skin, fish cornea, etc. were measured from RGB interferograms. In this paper, we discuss the bio-imaging applications of colour CCD based white light interferometry. The approach makes the measurement faster, easier, cost-effective, and even dynamic by using single fringe analysis methods, for industrial applications.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Active pixel sensors: the sensor of choice for future space applications?

NASA Astrophysics Data System (ADS)

Leijtens, Johan; Theuwissen, Albert; Rao, Padmakumar R.; Wang, Xinyang; Xie, Ning

2007-10-01

It is generally known that active pixel sensors (APS) have a number of advantages over CCD detectors if it comes to cost for mass production, power consumption and ease of integration. Nevertheless, most space applications still use CCD detectors because they tend to give better performance and have a successful heritage. To this respect a change may be at hand with the advent of deep sub-micron processed APS imagers (< 0.25-micron feature size). Measurements performed on test structures at the University of Delft have shown that the imagers are very radiation tolerant even if made in a standard process without the use of special design rules. Furthermore it was shown that the 1/f noise associated with deep sub-micron imagers is reduced as compared to previous generations APS imagers due to the improved quality of the gate oxides. Considering that end of life performance will have to be guaranteed, limited budget for adding shielding metal will be available for most applications and lower power operations is always seen as a positive characteristic in space applications, deep sub-micron APS imagers seem to have a number of advantages over CCD's that will probably cause them to replace CCD's in those applications where radiation tolerance and low power operation are important

A possible application of magnetic resonance imaging for pharmaceutical research.

PubMed

Kowalczuk, Joanna; Tritt-Goc, Jadwiga

2011-03-18

Magnetic resonance imaging (MRI) is a non-destructive and non-invasive method, the experiment can be conducted in situ and allows the studying of the sample and the different processes in vitro or in vivo. 1D, 2D or 3D imaging can be undertaken. MRI is nowadays most widely used in medicine as a clinical diagnostic tool, but has still seen limited application in the food and pharmaceutical sciences. The different imaging pulse sequences of MRI allow to image the processes that take place in a wide scale range from ms (dissolution of compact tablets) to hours (hydration of drug delivery systems) for mobile as well as for rigid spins, usually protons. The paper gives examples of MRI application of in vitro imaging of pharmaceutical dosage based on hydroxypropyl methylcellulose which have focused on water-penetration, diffusion, polymer swelling, and drug release, characterized with respect to other physical parameters such as pH and the molecular weight of polymer. Tetracycline hydrochloride was used as a model drug. NMR imaging of density distributions and fast kinetics of the dissolution behavior of compact tablets is presented for paracetamol tablets. Copyright © 2010 Elsevier B.V. All rights reserved.

Image gathering, coding, and processing: End-to-end optimization for efficient and robust acquisition of visual information

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Fales, Carl L.

1990-01-01

Researchers are concerned with the end-to-end performance of image gathering, coding, and processing. The applications range from high-resolution television to vision-based robotics, wherever the resolution, efficiency and robustness of visual information acquisition and processing are critical. For the presentation at this workshop, it is convenient to divide research activities into the following two overlapping areas: The first is the development of focal-plane processing techniques and technology to effectively combine image gathering with coding, with an emphasis on low-level vision processing akin to the retinal processing in human vision. The approach includes the familiar Laplacian pyramid, the new intensity-dependent spatial summation, and parallel sensing/processing networks. Three-dimensional image gathering is attained by combining laser ranging with sensor-array imaging. The second is the rigorous extension of information theory and optimal filtering to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing.

Information Acquisition, Analysis and Integration

DTIC Science & Technology

2016-08-03

of sensing and processing, theory, applications, signal processing, image and video processing, machine learning , technology transfer. 16. SECURITY... learning . 5. Solved elegantly old problems like image and video debluring, intro- ducing new revolutionary approaches. 1 DISTRIBUTION A: Distribution...Polatkan, G. Sapiro, D. Blei, D. B. Dunson, and L. Carin, “ Deep learning with hierarchical convolution factor analysis,” IEEE 6 DISTRIBUTION A

Real-time optical fiber digital speckle pattern interferometry for industrial applications

NASA Astrophysics Data System (ADS)

Chan, Robert K.; Cheung, Y. M.; Lo, C. H.; Tam, T. K.

1997-03-01

There is current interest, especially in the industrial sector, to use the digital speckle pattern interferometry (DSPI) technique to measure surface stress. Indeed, many publications in the subject are evident of the growing interests in the field. However, to bring the technology to industrial use requires the integration of several emerging technologies, viz. optics, feedback control, electronics, imaging processing and digital signal processing. Due to the highly interdisciplinary nature of the technique, successful implementation and development require expertise in all of the fields. At Baptist University, under the funding of a major industrial grant, we are developing the technology for the industrial sector. Our system fully exploits optical fibers and diode lasers in the design to enable practical and rugged systems suited for industrial applications. Besides the development in optics, we have broken away from the reliance of a microcomputer PC platform for both image capture and processing, and have developed a digital signal processing array system that can handle simultaneous and independent image capture/processing with feedback control. The system, named CASPA for 'cascadable architecture signal processing array,' is a third generation development system that utilizes up to 7 digital signal processors has proved to be a very powerful system. With our CASPA we are now in a better position to developing novel optical measurement systems for industrial application that may require different measurement systems to operate concurrently and requiring information exchange between the systems. Applications in mind such as simultaneous in-plane and out-of-plane DSPI image capture/process, vibrational analysis with interactive DSPI and phase shifting control of optical systems are a few good examples of the potentials.

Investigation of autofocus algorithms for brightfield microscopy of unstained cells

NASA Astrophysics Data System (ADS)

Wu, Shu Yu; Dugan, Nazim; Hennelly, Bryan M.

2014-05-01

In the past decade there has been significant interest in image processing for brightfield cell microscopy. Much of the previous research on image processing for microscopy has focused on fluorescence microscopy, including cell counting, cell tracking, cell segmentation and autofocusing. Fluorescence microscopy provides functional image information that involves the use of labels in the form of chemical stains or dyes. For some applications, where the biochemical integrity of the cell is required to remain unchanged so that sensitive chemical testing can later be applied, it is necessary to avoid staining. For this reason the challenge of processing images of unstained cells has become a topic of increasing attention. These cells are often effectively transparent and appear to have a homogenous intensity profile when they are in focus. Bright field microscopy is the most universally available and most widely used form of optical microscopy and for this reason we are interested in investigating image processing of unstained cells recorded using a standard bright field microscope. In this paper we investigate the application of a range of different autofocus metrics applied to unstained bladder cancer cell lines using a standard inverted bright field microscope with microscope objectives that have high magnification and numerical aperture. We present a number of conclusions on the optimum metrics and the manner in which they should be applied for this application.

Capacitive micromachined ultrasonic transducers for medical imaging and therapy.

PubMed

Khuri-Yakub, Butrus T; Oralkan, Omer

2011-05-01

Capacitive micromachined ultrasonic transducers (CMUTs) have been subject to extensive research for the last two decades. Although they were initially developed for air-coupled applications, today their main application space is medical imaging and therapy. This paper first presents a brief description of CMUTs, their basic structure, and operating principles. Our progression of developing several generations of fabrication processes is discussed with an emphasis on the advantages and disadvantages of each process. Monolithic and hybrid approaches for integrating CMUTs with supporting integrated circuits are surveyed. Several prototype transducer arrays with integrated frontend electronic circuits we developed and their use for 2-D and 3-D, anatomical and functional imaging, and ablative therapies are described. The presented results prove the CMUT as a MEMS technology for many medical diagnostic and therapeutic applications.

Capacitive micromachined ultrasonic transducers for medical imaging and therapy

PubMed Central

Khuri-Yakub, Butrus T.; Oralkan, Ömer

2011-01-01

Capacitive micromachined ultrasonic transducers (CMUTs) have been subject to extensive research for the last two decades. Although they were initially developed for air-coupled applications, today their main application space is medical imaging and therapy. This paper first presents a brief description of CMUTs, their basic structure, and operating principles. Our progression of developing several generations of fabrication processes is discussed with an emphasis on the advantages and disadvantages of each process. Monolithic and hybrid approaches for integrating CMUTs with supporting integrated circuits are surveyed. Several prototype transducer arrays with integrated frontend electronic circuits we developed and their use for 2-D and 3-D, anatomical and functional imaging, and ablative therapies are described. The presented results prove the CMUT as a MEMS technology for many medical diagnostic and therapeutic applications. PMID:21860542

Biological applications of phase-contrast electron microscopy.

PubMed

Nagayama, Kuniaki

2014-01-01

Here, I review the principles and applications of phase-contrast electron microscopy using phase plates. First, I develop the principle of phase contrast based on a minimal model of microscopy, introducing a double Fourier-transform process to mathematically formulate the image formation. Next, I explain four phase-contrast (PC) schemes, defocus PC, Zernike PC, Hilbert differential contrast, and schlieren optics, as image-filtering processes in the context of the minimal model, with particular emphases on the Zernike PC and corresponding Zernike phase plates. Finally, I review applications of Zernike PC cryo-electron microscopy to biological systems such as protein molecules, virus particles, and cells, including single-particle analysis to delineate three-dimensional (3D) structures of protein and virus particles and cryo-electron tomography to reconstruct 3D images of complex protein systems and cells.

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.

An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points

NASA Astrophysics Data System (ADS)

Shahamatnia, Ehsan; Dorotovič, Ivan; Fonseca, Jose M.; Ribeiro, Rita A.

2016-03-01

Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy

PubMed Central

Lerner, Thomas R.; Burden, Jemima J.; Nkwe, David O.; Pelchen-Matthews, Annegret; Domart, Marie-Charlotte; Durgan, Joanne; Weston, Anne; Jones, Martin L.; Peddie, Christopher J.; Carzaniga, Raffaella; Florey, Oliver; Marsh, Mark; Gutierrez, Maximiliano G.

2017-01-01

ABSTRACT The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research. PMID:27445312

Generative Adversarial Networks: An Overview

NASA Astrophysics Data System (ADS)

Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.

2018-01-01

Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

An application of stereoscopy and image processing in forensics: recovering obliterated firearms serial number

NASA Astrophysics Data System (ADS)

da Silva Nunes, L. C.; dos Santos, Paulo Acioly M.

2004-10-01

We present an application of the use of stereoscope to recovering obliterated firearms serial number. We investigate a promising new combined cheap method using both non-destructive and destructive techniques. With the use of a stereomicroscope coupled with a digital camera and a flexible cold light source, we can capture the image of the damaged area, and with continuous polishing and sometimes with the help of image processing techniques we could enhance the observed images and they can also be recorded as evidence. This method has already proven to be useful, in certain cases, in aluminum dotted pistol frames, whose serial number is printed with a laser, when etching techniques are not successful. We can also observe acid treated steel surfaces and enhance the images of recovered serial numbers, which sometimes lack of definition.

Proceedings of the Eleventh International Symposium on Remote Sensing of Environment, volume 2. [application and processing of remotely sensed data

NASA Technical Reports Server (NTRS)

1977-01-01

Application and processing of remotely sensed data are discussed. Areas of application include: pollution monitoring, water quality, land use, marine resources, ocean surface properties, and agriculture. Image processing and scene analysis are described along with automated photointerpretation and classification techniques. Data from infrared and multispectral band scanners onboard LANDSAT satellites are emphasized.

Evaluation of a HDR image sensor with logarithmic response for mobile video-based applications

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Pietrzak, Mateusz; Monnin, David

2017-10-01

The performance of mobile video-based applications using conventional LDR (Low Dynamic Range) image sensors highly depends on the illumination conditions. As an alternative, HDR (High Dynamic Range) image sensors with logarithmic response are capable to acquire illumination-invariant HDR images in a single shot. We have implemented a complete image processing framework for a HDR sensor, including preprocessing methods (nonuniformity correction (NUC), cross-talk correction (CTC), and demosaicing) as well as tone mapping (TM). We have evaluated the HDR sensor for video-based applications w.r.t. the display of images and w.r.t. image analysis techniques. Regarding the display we have investigated the image intensity statistics over time, and regarding image analysis we assessed the number of feature correspondences between consecutive frames of temporal image sequences. For the evaluation we used HDR image data recorded from a vehicle on outdoor or combined outdoor/indoor itineraries, and we performed a comparison with corresponding conventional LDR image data.

Observation of the Earth by radar

NASA Technical Reports Server (NTRS)

Elachi, C.

1982-01-01

Techniques and applications of radar observation from Earth satellites are discussed. Images processing and analysis of these images are discussed. Also discussed is radar imaging from aircraft. Uses of this data include ocean wave analysis, surface water evaluation, and topographic analysis.

PAT-tools for process control in pharmaceutical film coating applications.

PubMed

Knop, Klaus; Kleinebudde, Peter

2013-12-05

Recent development of analytical techniques to monitor the coating process of pharmaceutical solid dosage forms such as pellets and tablets are described. The progress from off- or at-line measurements to on- or in-line applications is shown for the spectroscopic methods near infrared (NIR) and Raman spectroscopy as well as for terahertz pulsed imaging (TPI) and image analysis. The common goal of all these methods is to control or at least to monitor the coating process and/or to estimate the coating end point through timely measurements. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

Some technical considerations on the evolution of the IBIS system. [Image Based Information System

NASA Technical Reports Server (NTRS)

Bryant, N. A.; Zobrist, A. L.

1982-01-01

In connection with work related to the use of earth-resources images, it became apparent by 1974, that certain system improvements are necessary for the efficient processing of digital data. To resolve this dilemma, Billingsley and Bryant (1975) proposed the use of image processing technology. Bryant and Zobrist (1976) reported the development of the Image Based Information System (IBIS) as a subset of an overall Video Image Communication and Retrieval (VICAR) image processing system. A description of IBIS is presented, and its employment in connection with advanced applications is discussed. It is concluded that several important lessons have been learned from the development of IBIS. The development of a flexible system such as IBIS is found to rest upon the prior development of a general purpose image processing system, such as VICAR.

WADeG Cell Phone

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

2009-09-01

The on cell phone software captures the images from the CMOS camera periodically, stores the pictures, and periodically transmits those images over the cellular network to the server. The cell phone software consists of several modules: CamTest.cpp, CamStarter.cpp, StreamIOHandler .cpp, and covertSmartDevice.cpp. The camera application on the SmartPhone is CamStarter, which is "the" user interface for the camera system. The CamStarter user interface allows a user to start/stop the camera application and transfer files to the server. The CamStarter application interfaces to the CamTest application through registry settings. Both the CamStarter and CamTest applications must be separately deployed on themore » smartphone to run the camera system application. When a user selects the Start button in CamStarter, CamTest is created as a process. The smartphone begins taking small pictures (CAPTURE mode), analyzing those pictures for certain conditions, and saving those pictures on the smartphone. This process will terminate when the user selects the Stop button. The camtest code spins off an asynchronous thread, StreamIOHandler, to check for pictures taken by the camera. The received image is then tested by StreamIOHandler to see if it meets certain conditions. If those conditions are met, the CamTest program is notified through the setting of a registry key value and the image is saved in a designated directory in a custom BMP file which includes a header and the image data. When the user selects the Transfer button in the CamStarter user interface, the covertsmartdevice code is created as a process. Covertsmartdevice gets all of the files in a designated directory, opens a socket connection to the server, sends each file, and then terminates.« less

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.

Reflectometric measurement of plasma imaging and applications

NASA Astrophysics Data System (ADS)

Mase, A.; Ito, N.; Oda, M.; Komada, Y.; Nagae, D.; Zhang, D.; Kogi, Y.; Tobimatsu, S.; Maruyama, T.; Shimazu, H.; Sakata, E.; Sakai, F.; Kuwahara, D.; Yoshinaga, T.; Tokuzawa, T.; Nagayama, Y.; Kawahata, K.; Yamaguchi, S.; Tsuji-Iio, S.; Domier, C. W.; Luhmann, N. C., Jr.; Park, H. K.; Yun, G.; Lee, W.; Padhi, S.; Kim, K. W.

2012-01-01

Progress in microwave and millimeter-wave technologies has made possible advanced diagnostics for application to various fields, such as, plasma diagnostics, radio astronomy, alien substance detection, airborne and spaceborne imaging radars called as synthetic aperture radars, living body measurements. Transmission, reflection, scattering, and radiation processes of electromagnetic waves are utilized as diagnostic tools. In this report we focus on the reflectometric measurements and applications to biological signals (vital signal detection and breast cancer detection) as well as plasma diagnostics, specifically by use of imaging technique and ultra-wideband radar technique.

Applications of satellite image processing to the analysis of Amazonian cultural ecology

NASA Technical Reports Server (NTRS)

Behrens, Clifford A.

1991-01-01

This paper examines the application of satellite image processing towards identifying and comparing resource exploitation among indigenous Amazonian peoples. The use of statistical and heuristic procedures for developing land cover/land use classifications from Thematic Mapper satellite imagery will be discussed along with actual results from studies of relatively small (100 - 200 people) settlements. Preliminary research indicates that analysis of satellite imagery holds great potential for measuring agricultural intensification, comparing rates of tropical deforestation, and detecting changes in resource utilization patterns over time.

A Comprehensive Analysis of the Physical Properties of Advanced GaAs/AlGaAs Junctions

NASA Technical Reports Server (NTRS)

Menkara, Hicham M.

1996-01-01

Extensive studies have been performed on MQW junctions and structures because of their potential applications as avalanche photodetectors in optical communications and imaging systems. The role of the avalanche photodiode is to provide for the conversion of an optical signal into charge. Knowledge of junction physics, and the various carrier generation/recombination mechanisms, is crucial for effectively optimizing the conversion process and increasing the structure's quantum efficiency. In addition, the recent interest in the use of APDs in imaging systems has necessitated the development of semiconductor junctions with low dark currents and high gains for low light applications. Because of the high frame rate and high pixel density requirements in new imaging applications, it is necessary to provide some front-end gain in the imager to allow operation under reasonable light conditions. Understanding the electron/hole impact ionization process, as well as diffusion and surface leakage effects, is needed to help maintain low dark currents and high gains for such applications. In addition, the APD must be capable of operating with low power, and low noise. Knowledge of the effects of various doping configurations and electric field profiles, as well as the excess noise resulting from the avalanche process, are needed to help maintain low operating bias and minimize the noise output.

Asic developments for radiation imaging applications: The medipix and timepix family

NASA Astrophysics Data System (ADS)

Ballabriga, Rafael; Campbell, Michael; Llopart, Xavier

2018-01-01

Hybrid pixel detectors were developed to meet the requirements for tracking in the inner layers at the LHC experiments. With low input capacitance per channel (10-100 fF) it is relatively straightforward to design pulse processing readout electronics with input referred noise of ∼ 100 e-rms and pulse shaping times consistent with tagging of events to a single LHC bunch crossing providing clean 'images' of the ionising tracks generated. In the Medipix Collaborations the same concept has been adapted to provide practically noise hit free imaging in a wide range of applications. This paper reports on the development of three generations of readout ASICs. Two distinctive streams of development can be identified: the Medipix ASICs which integrate data from multiple hits on a pixel and provide the images in the form of frames and the Timepix ASICs who aim to send as much information about individual interactions as possible off-chip for further processing. One outstanding circumstance in the use of these devices has been their numerous successful applications, thanks to a large and active community of developers and users. That process has even permitted new developments for detectors for High Energy Physics. This paper reviews the ASICs themselves and details some of the many applications.

Real-time microstructural and functional imaging and image processing in optical coherence tomography

NASA Astrophysics Data System (ADS)

Westphal, Volker

Optical Coherence Tomography (OCT) is a noninvasive optical imaging technique that allows high-resolution cross-sectional imaging of tissue microstructure, achieving a spatial resolution of about 10 mum. OCT is similar to B-mode ultrasound (US) except that it uses infrared light instead of ultrasound. In contrast to US, no coupling gel is needed, simplifying the image acquisition. Furthermore, the fiber optic implementation of OCT is compatible with endoscopes. In recent years, the transition from slow imaging, bench-top systems to real-time clinical systems has been under way. This has lead to a variety of applications, namely in ophthalmology, gastroenterology, dermatology and cardiology. First, this dissertation will demonstrate that OCT is capable of imaging and differentiating clinically relevant tissue structures in the gastrointestinal tract. A careful in vitro correlation study between endoscopic OCT images and corresponding histological slides was performed. Besides structural imaging, OCT systems were further developed for functional imaging, as for example to visualize blood flow. Previously, imaging flow in small vessels in real-time was not possible. For this research, a new processing scheme similar to real-time Doppler in US was introduced. It was implemented in dedicated hardware to allow real-time acquisition and overlayed display of blood flow in vivo. A sensitivity of 0.5mm/s was achieved. Optical coherence microscopy (OCM) is a variation of OCT, improving the resolution even further to a few micrometers. Advances made in the OCT scan engine for the Doppler setup enabled real-time imaging in vivo with OCM. In order to generate geometrical correct images for all the previous applications in real-time, extensive image processing algorithms were developed. Algorithms for correction of distortions due to non-telecentric scanning, nonlinear scan mirror movements, and refraction were developed and demonstrated. This has led to interesting new applications, as for example in imaging of the anterior segment of the eye.

Massively parallel information processing systems for space applications

NASA Technical Reports Server (NTRS)

Schaefer, D. H.

1979-01-01

NASA is developing massively parallel systems for ultra high speed processing of digital image data collected by satellite borne instrumentation. Such systems contain thousands of processing elements. Work is underway on the design and fabrication of the 'Massively Parallel Processor', a ground computer containing 16,384 processing elements arranged in a 128 x 128 array. This computer uses existing technology. Advanced work includes the development of semiconductor chips containing thousands of feedthrough paths. Massively parallel image analog to digital conversion technology is also being developed. The goal is to provide compact computers suitable for real-time onboard processing of images.

Investigation of radio astronomy image processing techniques for use in the passive millimetre-wave security screening environment

NASA Astrophysics Data System (ADS)

Taylor, Christopher T.; Hutchinson, Simon; Salmon, Neil A.; Wilkinson, Peter N.; Cameron, Colin D.

2014-06-01

Image processing techniques can be used to improve the cost-effectiveness of future interferometric Passive MilliMetre Wave (PMMW) imagers. The implementation of such techniques will allow for a reduction in the number of collecting elements whilst ensuring adequate image fidelity is maintained. Various techniques have been developed by the radio astronomy community to enhance the imaging capability of sparse interferometric arrays. The most prominent are Multi- Frequency Synthesis (MFS) and non-linear deconvolution algorithms, such as the Maximum Entropy Method (MEM) and variations of the CLEAN algorithm. This investigation focuses on the implementation of these methods in the defacto standard for radio astronomy image processing, the Common Astronomy Software Applications (CASA) package, building upon the discussion presented in Taylor et al., SPIE 8362-0F. We describe the image conversion process into a CASA suitable format, followed by a series of simulations that exploit the highlighted deconvolution and MFS algorithms assuming far-field imagery. The primary target application used for this investigation is an outdoor security scanner for soft-sided Heavy Goods Vehicles. A quantitative analysis of the effectiveness of the aforementioned image processing techniques is presented, with thoughts on the potential cost-savings such an approach could yield. Consideration is also given to how the implementation of these techniques in CASA might be adapted to operate in a near-field target environment. This may enable a much wider usability by the imaging community outside of radio astronomy and thus would be directly relevant to portal screening security systems in the microwave and millimetre wave bands.

The Hico Image Processing System: A Web-Accessible Hyperspectral Remote Sensing Toolbox

NASA Astrophysics Data System (ADS)

Harris, A. T., III; Goodman, J.; Justice, B.

2014-12-01

As the quantity of Earth-observation data increases, the use-case for hosting analytical tools in geospatial data centers becomes increasingly attractive. To address this need, HySpeed Computing and Exelis VIS have developed the HICO Image Processing System, a prototype cloud computing system that provides online, on-demand, scalable remote sensing image processing capabilities. The system provides a mechanism for delivering sophisticated image processing analytics and data visualization tools into the hands of a global user community, who will only need a browser and internet connection to perform analysis. Functionality of the HICO Image Processing System is demonstrated using imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), an imaging spectrometer located on the International Space Station (ISS) that is optimized for acquisition of aquatic targets. Example applications include a collection of coastal remote sensing algorithms that are directed at deriving critical information on water and habitat characteristics of our vulnerable coastal environment. The project leverages the ENVI Services Engine as the framework for all image processing tasks, and can readily accommodate the rapid integration of new algorithms, datasets and processing tools.

Book Review: Reiner Salzer and Heinz W. Siesler (Eds.): Infrared and Raman spectroscopic imaging, 2nd ed.

DOE PAGES

Moore, David Steven

2015-05-10

This second edition of "Infrared and Raman Spectroscopic Imaging" propels practitioners in that wide-ranging field, as well as other readers, to the current state of the art in a well-produced and full-color, completely revised and updated, volume. This new edition chronicles the expanded application of vibrational spectroscopic imaging from yesterday's time-consuming point-by-point buildup of a hyperspectral image cube, through the improvements afforded by the addition of focal plane arrays and line scan imaging, to methods applicable beyond the diffraction limit, instructs the reader on the improved instrumentation and image and data analysis methods, and expounds on their application to fundamentalmore » biomedical knowledge, food and agricultural surveys, materials science, process and quality control, and many others.« less

Imaging live cells at high spatiotemporal resolution for lab-on-a-chip applications.

PubMed

Chin, Lip Ket; Lee, Chau-Hwang; Chen, Bi-Chang

2016-05-24

Conventional optical imaging techniques are limited by the diffraction limit and difficult-to-image biomolecular and sub-cellular processes in living specimens. Novel optical imaging techniques are constantly evolving with the desire to innovate an imaging tool that is capable of seeing sub-cellular processes in a biological system, especially in three dimensions (3D) over time, i.e. 4D imaging. For fluorescence imaging on live cells, the trade-offs among imaging depth, spatial resolution, temporal resolution and photo-damage are constrained based on the limited photons of the emitters. The fundamental solution to solve this dilemma is to enlarge the photon bank such as the development of photostable and bright fluorophores, leading to the innovation in optical imaging techniques such as super-resolution microscopy and light sheet microscopy. With the synergy of microfluidic technology that is capable of manipulating biological cells and controlling their microenvironments to mimic in vivo physiological environments, studies of sub-cellular processes in various biological systems can be simplified and investigated systematically. In this review, we provide an overview of current state-of-the-art super-resolution and 3D live cell imaging techniques and their lab-on-a-chip applications, and finally discuss future research trends in new and breakthrough research areas of live specimen 4D imaging in controlled 3D microenvironments.

A New Vegetation Segmentation Approach for Cropped Fields Based on Threshold Detection from Hue Histograms

PubMed Central

Hassanein, Mohamed; El-Sheimy, Naser

2018-01-01

Over the last decade, the use of unmanned aerial vehicle (UAV) technology has evolved significantly in different applications as it provides a special platform capable of combining the benefits of terrestrial and aerial remote sensing. Therefore, such technology has been established as an important source of data collection for different precision agriculture (PA) applications such as crop health monitoring and weed management. Generally, these PA applications depend on performing a vegetation segmentation process as an initial step, which aims to detect the vegetation objects in collected agriculture fields’ images. The main result of the vegetation segmentation process is a binary image, where vegetations are presented in white color and the remaining objects are presented in black. Such process could easily be performed using different vegetation indexes derived from multispectral imagery. Recently, to expand the use of UAV imagery systems for PA applications, it was important to reduce the cost of such systems through using low-cost RGB cameras Thus, developing vegetation segmentation techniques for RGB images is a challenging problem. The proposed paper introduces a new vegetation segmentation methodology for low-cost UAV RGB images, which depends on using Hue color channel. The proposed methodology follows the assumption that the colors in any agriculture field image can be distributed into vegetation and non-vegetations colors. Therefore, four main steps are developed to detect five different threshold values using the hue histogram of the RGB image, these thresholds are capable to discriminate the dominant color, either vegetation or non-vegetation, within the agriculture field image. The achieved results for implementing the proposed methodology showed its ability to generate accurate and stable vegetation segmentation performance with mean accuracy equal to 87.29% and standard deviation as 12.5%. PMID:29670055

Multispectral data processing from unmanned aerial vehicles: application in precision agriculture using different sensors and platforms

NASA Astrophysics Data System (ADS)

Piermattei, Livia; Bozzi, Carlo Alberto; Mancini, Adriano; Tassetti, Anna Nora; Karel, Wilfried; Pfeifer, Norbert

2017-04-01

Unmanned aerial vehicles (UAVs) in combination with consumer grade cameras have become standard tools for photogrammetric applications and surveying. The recent generation of multispectral, cost-efficient and lightweight cameras has fostered a breakthrough in the practical application of UAVs for precision agriculture. For this application, multispectral cameras typically use Green, Red, Red-Edge (RE) and Near Infrared (NIR) wavebands to capture both visible and invisible images of crops and vegetation. These bands are very effective for deriving characteristics like soil productivity, plant health and overall growth. However, the quality of results is affected by the sensor architecture, the spatial and spectral resolutions, the pattern of image collection, and the processing of the multispectral images. In particular, collecting data with multiple sensors requires an accurate spatial co-registration of the various UAV image datasets. Multispectral processed data in precision agriculture are mainly presented as orthorectified mosaics used to export information maps and vegetation indices. This work aims to investigate the acquisition parameters and processing approaches of this new type of image data in order to generate orthoimages using different sensors and UAV platforms. Within our experimental area we placed a grid of artificial targets, whose position was determined with differential global positioning system (dGPS) measurements. Targets were used as ground control points to georeference the images and as checkpoints to verify the accuracy of the georeferenced mosaics. The primary aim is to present a method for the spatial co-registration of visible, Red-Edge, and NIR image sets. To demonstrate the applicability and accuracy of our methodology, multi-sensor datasets were collected over the same area and approximately at the same time using the fixed-wing UAV senseFly "eBee". The images were acquired with the camera Canon S110 RGB, the multispectral cameras Canon S110 NIR and S110 RE and with the multi-camera system Parrot Sequoia, which is composed of single-band cameras (Green, Red, Red Edge, NIR and RGB). Imagery from each sensor was georeferenced and mosaicked with the commercial software Agisoft PhotoScan Pro and different approaches for image orientation were compared. To assess the overall spatial accuracy of each dataset the root mean square error was computed between check point coordinates measured with dGPS and coordinates retrieved from georeferenced image mosaics. Additionally, image datasets from different UAV platforms (i.e. DJI Phantom 4Pro, DJI Phantom 3 professional, and DJI Inspire 1 Pro) were acquired over the same area and the spatial accuracy of the orthoimages was evaluated.

A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2013-01-01

Point matching is crucial for many computer vision applications. Establishing the correspondence between a large number of data points is a computationally intensive process. Some point matching related applications, such as medical image registration, require real time or near real time performance if applied to critical clinical applications like image assisted surgery. In this paper, we report a new multicore platform based parallel algorithm for fast point matching in the context of landmark based medical image registration. We introduced a non-regular data partition algorithm which utilizes the K-means clustering algorithm to group the landmarks based on the number of available processing cores, which optimize the memory usage and data transfer. We have tested our method using the IBM Cell Broadband Engine (Cell/B.E.) platform. The results demonstrated a significant speed up over its sequential implementation. The proposed data partition and parallelization algorithm, though tested only on one multicore platform, is generic by its design. Therefore the parallel algorithm can be extended to other computing platforms, as well as other point matching related applications. PMID:24308014

Curve and Polygon Evolution Techniques for Image Processing

DTIC Science & Technology

2002-01-01

iterative image registration technique with an application to stereo vision. IJCAI, pages 674–679, 1981. 127 [93] R . Malladi , J.A. Sethian, and B.C...Notation A digital image to be processed is a 2-Dimensional (2-D) function denoted by I , I : ! R , where R2 is the domain of the function. Processing a...function Io(x; y), which depends on two spatial variables, x 2 R , and y 2 R , via a partial differential equation (PDE) takes the form; It = A(I; Ix

ELAS: A powerful, general purpose image processing package

NASA Technical Reports Server (NTRS)

Walters, David; Rickman, Douglas

1991-01-01

ELAS is a software package which has been utilized as an image processing tool for more than a decade. It has been the source of several commercial packages. Now available on UNIX workstations it is a very powerful, flexible set of software. Applications at Stennis Space Center have included a very wide range of areas including medicine, forestry, geology, ecological modeling, and sonar imagery. It remains one of the most powerful image processing packages available, either commercially or in the public domain.

Ultra-high-speed variable focus optics for novel applications in advanced imaging

NASA Astrophysics Data System (ADS)

Kang, S.; Dotsenko, E.; Amrhein, D.; Theriault, C.; Arnold, C. B.

2018-02-01

With the advancement of ultra-fast manufacturing technologies, high speed imaging with high 3D resolution has become increasingly important. Here we show the use of an ultra-high-speed variable focus optical element, the TAG Lens, to enable new ways to acquire 3D information from an object. The TAG Lens uses sound to adjust the index of refraction profile in a liquid and thereby can achieve focal scanning rates greater than 100 kHz. When combined with a high-speed pulsed LED and a high-speed camera, we can exploit this phenomenon to achieve high-resolution imaging through large depths. By combining the image acquisition with digital image processing, we can extract relevant parameters such as tilt and angle information from objects in the image. Due to the high speeds at which images can be collected and processed, we believe this technique can be used as an efficient method of industrial inspection and metrology for high throughput applications.

Photo CD and Other Digital Imaging Technologies: What's out There and What's It For?

ERIC Educational Resources Information Center

Chen, Ching-Chih

1993-01-01

Describes Kodak's Photo CD technology and its impact on digital imaging. Color desktop publishing, image processing and preservation, image archival storage, and interactive multimedia development, as well as the equipment, software, and services that make these applications possible, are described. Contact information for developers and…

Image smoothing and enhancement via min/max curvature flow

NASA Astrophysics Data System (ADS)

Malladi, Ravikanth; Sethian, James A.

1996-03-01

We present a class of PDE-based algorithms suitable for a wide range of image processing applications. The techniques are applicable to both salt-and-pepper gray-scale noise and full- image continuous noise present in black and white images, gray-scale images, texture images and color images. At the core, the techniques rely on a level set formulation of evolving curves and surfaces and the viscosity in profile evolution. Essentially, the method consists of moving the isointensity contours in an image under curvature dependent speed laws to achieve enhancement. Compared to existing techniques, our approach has several distinct advantages. First, it contains only one enhancement parameter, which in most cases is automatically chosen. Second, the scheme automatically stops smoothing at some optimal point; continued application of the scheme produces no further change. Third, the method is one of the fastest possible schemes based on a curvature-controlled approach.

Image-Processing Program

NASA Technical Reports Server (NTRS)

Roth, D. J.; Hull, D. R.

1994-01-01

IMAGEP manipulates digital image data to effect various processing, analysis, and enhancement functions. It is keyboard-driven program organized into nine subroutines. Within subroutines are sub-subroutines also selected via keyboard. Algorithm has possible scientific, industrial, and biomedical applications in study of flows in materials, analysis of steels and ores, and pathology, respectively.

Automatic Co-Registration of QuickBird Data for Change Detection Applications

NASA Technical Reports Server (NTRS)

Bryant, Nevin A.; Logan, Thomas L.; Zobrist, Albert L.

2006-01-01

This viewgraph presentation reviews the use Automatic Fusion of Image Data System (AFIDS) for Automatic Co-Registration of QuickBird Data to ascertain if changes have occurred in images. The process is outlined, and views from Iraq and Los Angelels are shown to illustrate the process.

Integrated segmentation of cellular structures

NASA Astrophysics Data System (ADS)

Ajemba, Peter; Al-Kofahi, Yousef; Scott, Richard; Donovan, Michael; Fernandez, Gerardo

2011-03-01

Automatic segmentation of cellular structures is an essential step in image cytology and histology. Despite substantial progress, better automation and improvements in accuracy and adaptability to novel applications are needed. In applications utilizing multi-channel immuno-fluorescence images, challenges include misclassification of epithelial and stromal nuclei, irregular nuclei and cytoplasm boundaries, and over and under-segmentation of clustered nuclei. Variations in image acquisition conditions and artifacts from nuclei and cytoplasm images often confound existing algorithms in practice. In this paper, we present a robust and accurate algorithm for jointly segmenting cell nuclei and cytoplasm using a combination of ideas to reduce the aforementioned problems. First, an adaptive process that includes top-hat filtering, Eigenvalues-of-Hessian blob detection and distance transforms is used to estimate the inverse illumination field and correct for intensity non-uniformity in the nuclei channel. Next, a minimum-error-thresholding based binarization process and seed-detection combining Laplacian-of-Gaussian filtering constrained by a distance-map-based scale selection is used to identify candidate seeds for nuclei segmentation. The initial segmentation using a local maximum clustering algorithm is refined using a minimum-error-thresholding technique. Final refinements include an artifact removal process specifically targeted at lumens and other problematic structures and a systemic decision process to reclassify nuclei objects near the cytoplasm boundary as epithelial or stromal. Segmentation results were evaluated using 48 realistic phantom images with known ground-truth. The overall segmentation accuracy exceeds 94%. The algorithm was further tested on 981 images of actual prostate cancer tissue. The artifact removal process worked in 90% of cases. The algorithm has now been deployed in a high-volume histology analysis application.

RVC-CAL library for endmember and abundance estimation in hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Lazcano López, R.; Madroñal Quintín, D.; Juárez Martínez, E.; Sanz Álvaro, C.

2015-10-01

Hyperspectral imaging (HI) collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. Although this technology was initially developed for remote sensing and earth observation, its multiple advantages - such as high spectral resolution - led to its application in other fields, as cancer detection. However, this new field has shown specific requirements; for instance, it needs to accomplish strong time specifications, since all the potential applications - like surgical guidance or in vivo tumor detection - imply real-time requisites. Achieving this time requirements is a great challenge, as hyperspectral images generate extremely high volumes of data to process. Thus, some new research lines are studying new processing techniques, and the most relevant ones are related to system parallelization. In that line, this paper describes the construction of a new hyperspectral processing library for RVC-CAL language, which is specifically designed for multimedia applications and allows multithreading compilation and system parallelization. This paper presents the development of the required library functions to implement two of the four stages of the hyperspectral imaging processing chain--endmember and abundances estimation. The results obtained show that the library achieves speedups of 30%, approximately, comparing to an existing software of hyperspectral images analysis; concretely, the endmember estimation step reaches an average speedup of 27.6%, which saves almost 8 seconds in the execution time. It also shows the existence of some bottlenecks, as the communication interfaces among the different actors due to the volume of data to transfer. Finally, it is shown that the library considerably simplifies the implementation process. Thus, experimental results show the potential of a RVC-CAL library for analyzing hyperspectral images in real-time, as it provides enough resources to study the system performance.

Concurrent Image Processing Executive (CIPE). Volume 1: Design overview

NASA Technical Reports Server (NTRS)

Lee, Meemong; Groom, Steven L.; Mazer, Alan S.; Williams, Winifred I.

1990-01-01

The design and implementation of a Concurrent Image Processing Executive (CIPE), which is intended to become the support system software for a prototype high performance science analysis workstation are described. The target machine for this software is a JPL/Caltech Mark 3fp Hypercube hosted by either a MASSCOMP 5600 or a Sun-3, Sun-4 workstation; however, the design will accommodate other concurrent machines of similar architecture, i.e., local memory, multiple-instruction-multiple-data (MIMD) machines. The CIPE system provides both a multimode user interface and an applications programmer interface, and has been designed around four loosely coupled modules: user interface, host-resident executive, hypercube-resident executive, and application functions. The loose coupling between modules allows modification of a particular module without significantly affecting the other modules in the system. In order to enhance hypercube memory utilization and to allow expansion of image processing capabilities, a specialized program management method, incremental loading, was devised. To minimize data transfer between host and hypercube, a data management method which distributes, redistributes, and tracks data set information was implemented. The data management also allows data sharing among application programs. The CIPE software architecture provides a flexible environment for scientific analysis of complex remote sensing image data, such as planetary data and imaging spectrometry, utilizing state-of-the-art concurrent computation capabilities.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

USGS Publications Warehouse

Singha, Kaminit; Day-Lewis, Frederick D.; Johnson, Tim B.; Slater, Lee D.

2015-01-01

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

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

Singha, Kamini; Day-Lewis, Frederick D.; Johnson, Timothy C.

2015-03-15

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

A real time quality control application for animal production by image processing.

PubMed

Sungur, Cemil; Özkan, Halil

2015-11-01

Standards of hygiene and health are of major importance in food production, and quality control has become obligatory in this field. Thanks to rapidly developing technologies, it is now possible for automatic and safe quality control of food production. For this purpose, image-processing-based quality control systems used in industrial applications are being employed to analyze the quality of food products. In this study, quality control of chicken (Gallus domesticus) eggs was achieved using a real time image-processing technique. In order to execute the quality control processes, a conveying mechanism was used. Eggs passing on a conveyor belt were continuously photographed in real time by cameras located above the belt. The images obtained were processed by various methods and techniques. Using digital instrumentation, the volume of the eggs was measured, broken/cracked eggs were separated and dirty eggs were determined. In accordance with international standards for classifying the quality of eggs, the class of separated eggs was determined through a fuzzy implication model. According to tests carried out on thousands of eggs, a quality control process with an accuracy of 98% was possible. © 2014 Society of Chemical Industry.

Liquid crystal thermography and true-colour digital image processing

NASA Astrophysics Data System (ADS)

Stasiek, J.; Stasiek, A.; Jewartowski, M.; Collins, M. W.

2006-06-01

In the last decade thermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLCs at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make visible the temperature and velocity fields in liquids by the simple expedient of directly mixing the liquid crystal material into the liquid (water, glycerol, glycol, and silicone oils) in very small quantities to use as thermal and hydrodynamic tracers. In biomedical situations e.g., skin diseases, breast cancer, blood circulation and other medical application, TLC and image processing are successfully used as an additional non-invasive diagnostic method especially useful for screening large groups of potential patients. The history of this technique is reviewed, principal methods and tools are described and some examples are also presented.

SVM Pixel Classification on Colour Image Segmentation

NASA Astrophysics Data System (ADS)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Towards Automatic Image Segmentation Using Optimised Region Growing Technique

NASA Astrophysics Data System (ADS)

Alazab, Mamoun; Islam, Mofakharul; Venkatraman, Sitalakshmi

Image analysis is being adopted extensively in many applications such as digital forensics, medical treatment, industrial inspection, etc. primarily for diagnostic purposes. Hence, there is a growing interest among researches in developing new segmentation techniques to aid the diagnosis process. Manual segmentation of images is labour intensive, extremely time consuming and prone to human errors and hence an automated real-time technique is warranted in such applications. There is no universally applicable automated segmentation technique that will work for all images as the image segmentation is quite complex and unique depending upon the domain application. Hence, to fill the gap, this paper presents an efficient segmentation algorithm that can segment a digital image of interest into a more meaningful arrangement of regions and objects. Our algorithm combines region growing approach with optimised elimination of false boundaries to arrive at more meaningful segments automatically. We demonstrate this using X-ray teeth images that were taken for real-life dental diagnosis.

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.

Real-time digital signal processing for live electro-optic imaging.

PubMed

Sasagawa, Kiyotaka; Kanno, Atsushi; Tsuchiya, Masahiro

2009-08-31

We present an imaging system that enables real-time magnitude and phase detection of modulated signals and its application to a Live Electro-optic Imaging (LEI) system, which realizes instantaneous visualization of RF electric fields. The real-time acquisition of magnitude and phase images of a modulated optical signal at 5 kHz is demonstrated by imaging with a Si-based high-speed CMOS image sensor and real-time signal processing with a digital signal processor. In the LEI system, RF electric fields are probed with light via an electro-optic crystal plate and downconverted to an intermediate frequency by parallel optical heterodyning, which can be detected with the image sensor. The artifacts caused by the optics and the image sensor characteristics are corrected by image processing. As examples, we demonstrate real-time visualization of electric fields from RF circuits.

Application development environment for advanced digital workstations

NASA Astrophysics Data System (ADS)

Valentino, Daniel J.; Harreld, Michael R.; Liu, Brent J.; Brown, Matthew S.; Huang, Lu J.

1998-06-01

One remaining barrier to the clinical acceptance of electronic imaging and information systems is the difficulty in providing intuitive access to the information needed for a specific clinical task (such as reaching a diagnosis or tracking clinical progress). The purpose of this research was to create a development environment that enables the design and implementation of advanced digital imaging workstations. We used formal data and process modeling to identify the diagnostic and quantitative data that radiologists use and the tasks that they typically perform to make clinical decisions. We studied a diverse range of radiology applications, including diagnostic neuroradiology in an academic medical center, pediatric radiology in a children's hospital, screening mammography in a breast cancer center, and thoracic radiology consultation for an oncology clinic. We used object- oriented analysis to develop software toolkits that enable a programmer to rapidly implement applications that closely match clinical tasks. The toolkits support browsing patient information, integrating patient images and reports, manipulating images, and making quantitative measurements on images. Collectively, we refer to these toolkits as the UCLA Digital ViewBox toolkit (ViewBox/Tk). We used the ViewBox/Tk to rapidly prototype and develop a number of diverse medical imaging applications. Our task-based toolkit approach enabled rapid and iterative prototyping of workstations that matched clinical tasks. The toolkit functionality and performance provided a 'hands-on' feeling for manipulating images, and for accessing textual information and reports. The toolkits directly support a new concept for protocol based-reading of diagnostic studies. The design supports the implementation of network-based application services (e.g., prefetching, workflow management, and post-processing) that will facilitate the development of future clinical applications.

Biomedical applications of a real-time terahertz color scanner

PubMed Central

Schirmer, Markus; Fujio, Makoto; Minami, Masaaki; Miura, Jiro; Araki, Tsutomu; Yasui, Takeshi

2010-01-01

A real-time THz color scanner has the potential to further expand the application scope of THz spectral imaging based on its rapid image acquisition rate. We demonstrated three possible applications of a THz color scanner in the biomedical field: imaging of pharmaceutical tablets, human teeth, and human hair. The first application showed the scanner’s potential in total inspection for rapid quality control of pharmaceutical tablets moving on a conveyor belt. The second application demonstrated that the scanner can be used to identify a potential indicator for crystallinity of dental tissue. In the third application, the scanner was successfully used to visualize the drying process of wet hairs. These demonstrations indicated the high potential of the THz color scanner for practical applications in the biomedical field. PMID:21258472

The Application of Nanoparticles in Gene Therapy and Magnetic Resonance Imaging

PubMed Central

HERRANZ, FERNANDO; ALMARZA, ELENA; RODRÍGUEZ, IGNACIO; SALINAS, BEATRIZ; ROSELL, YAMILKA; DESCO, MANUEL; BULTE, JEFF W.; RUIZ-CABELLO, JESÚS

2012-01-01

The combination of nanoparticles, gene therapy, and medical imaging has given rise to a new field known as gene theranostics, in which a nanobioconjugate is used to diagnose and treat the disease. The process generally involves binding between a vector carrying the genetic information and a nanoparticle, which provides the signal for imaging. The synthesis of this probe generates a synergic effect, enhancing the efficiency of gene transduction and imaging contrast. We discuss the latest approaches in the synthesis of nanoparticles for magnetic resonance imaging, gene therapy strategies, and their conjugation and in vivo application. PMID:21484943

SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

NASA Astrophysics Data System (ADS)

Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

2010-09-01

In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

Developing stereo image based robot control system

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

Suprijadi,; Pambudi, I. R.; Woran, M.

Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based onmore » stereovision captures.« less

A web-based computer aided system for liver surgery planning: initial implementation on RayPlus

NASA Astrophysics Data System (ADS)

Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo

2016-03-01

At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

Autofluorescence detection and imaging of bladder cancer realized through a cystoscope

DOEpatents

Demos, Stavros G [Livermore, CA; deVere White, Ralph W [Sacramento, CA

2007-08-14

Near infrared imaging using elastic light scattering and tissue autofluorescence and utilizing interior examination techniques and equipment are explored for medical applications. The approach involves imaging using cross-polarized elastic light scattering and/or tissue autofluorescence in the Near Infra-Red (NIR) coupled with image processing and inter-image operations to differentiate human tissue components.

System Matrix Analysis for Computed Tomography Imaging

PubMed Central

Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

2015-01-01

In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

Image Analysis Based on Soft Computing and Applied on Space Shuttle During the Liftoff Process

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Klinko, Steve J.

2007-01-01

Imaging techniques based on Soft Computing (SC) and developed at Kennedy Space Center (KSC) have been implemented on a variety of prototype applications related to the safety operation of the Space Shuttle during the liftoff process. These SC-based prototype applications include detection and tracking of moving Foreign Objects Debris (FOD) during the Space Shuttle liftoff, visual anomaly detection on slidewires used in the emergency egress system for the Space Shuttle at the laJlIlch pad, and visual detection of distant birds approaching the Space Shuttle launch pad. This SC-based image analysis capability developed at KSC was also used to analyze images acquired during the accident of the Space Shuttle Columbia and estimate the trajectory and velocity of the foam that caused the accident.

New-style defect inspection system of film

NASA Astrophysics Data System (ADS)

Liang, Yan; Liu, Wenyao; Liu, Ming; Lee, Ronggang

2002-09-01

An inspection system has been developed for on-line detection of film defects, which bases on combination of photoelectric imaging and digital image processing. The system runs in high speed of maximum 60m/min. Moving film is illuminated by LED array which emits even infrared (peak wavelength λp=940nm), and infrared images are obtained with a high quality and high speed CCD camera. The application software based on Visual C++6.0 under Windows processes images in real time by means of such algorithms as median filter, edge detection and projection, etc. The system is made up of four modules, which are introduced in detail in the paper. On-line experiment results shows that the inspection system can recognize defects precisely in high speed and run reliably in practical application.

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.

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining

PubMed Central

Mendikute, Alberto; Zatarain, Mikel; Bertelsen, Álvaro; Leizea, Ibai

2017-01-01

Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g., 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras. PMID:28891946

Self-Calibrated In-Process Photogrammetry for Large Raw Part Measurement and Alignment before Machining.

PubMed

Mendikute, Alberto; Yagüe-Fabra, José A; Zatarain, Mikel; Bertelsen, Álvaro; Leizea, Ibai

2017-09-09

Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g. 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras.

A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

NASA Astrophysics Data System (ADS)

Karimi, Davood; Ward, Rabab K.

2016-03-01

Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

PubMed

Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

2014-01-01

Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

Binary video codec for data reduction in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Khursheed, Khursheed; Ahmad, Naeem; Imran, Muhammad; O'Nils, Mattias

2013-02-01

Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Binary Video Codec (BVC) for the data reduction in WVSN. We proposed to implement all the three compression techniques i.e. image coding, change coding and ROI coding at the VSN and then select the smallest bit stream among the results of the three compression techniques. In this way the compression performance of the BVC will never become worse than that of image coding. We concluded that the compression efficiency of BVC is always better than that of change coding and is always better than or equal that of ROI coding and image coding.

A new automatic synthetic aperture radar-based flood mapping application hosted on the European Space Agency's Grid Processing of Demand Fast Access to Imagery environment

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Hostache, Renaud

2012-10-01

This paper introduces an automatic flood mapping application that is hosted on the Grid Processing on Demand (GPOD) Fast Access to Imagery (Faire) environment of the European Space Agency. The main objective of the online application is to deliver operationally flooded areas using both recent and historical acquisitions of SAR data. Having as a short-term target the flooding-related exploitation of data generated by the upcoming ESA SENTINEL-1 SAR mission, the flood mapping application consists of two building blocks: i) a set of query tools for selecting the "crisis image" and the optimal corresponding "reference image" from the G-POD archive and ii) an algorithm for extracting flooded areas via change detection using the previously selected "crisis image" and "reference image". Stakeholders in flood management and service providers are able to log onto the flood mapping application to get support for the retrieval, from the rolling archive, of the most appropriate reference image. Potential users will also be able to apply the implemented flood delineation algorithm. The latter combines histogram thresholding, region growing and change detection as an approach enabling the automatic, objective and reliable flood extent extraction from SAR images. Both algorithms are computationally efficient and operate with minimum data requirements. The case study of the high magnitude flooding event that occurred in July 2007 on the Severn River, UK, and that was observed with a moderateresolution SAR sensor as well as airborne photography highlights the performance of the proposed online application. The flood mapping application on G-POD can be used sporadically, i.e. whenever a major flood event occurs and there is a demand for SAR-based flood extent maps. In the long term, a potential extension of the application could consist in systematically extracting flooded areas from all SAR images acquired on a daily, weekly or monthly basis.

[Progress in Application of Measuring Skeleton by CT in Forensic Anthropology Research].

PubMed

Miao, C Y; Xu, L; Wang, N; Zhang, M; Li, Y S; Lü, J X

2017-02-01

Individual identification by measuring the human skeleton is an important research in the field of forensic anthropology. Computed tomography （CT） technology can provide high-resolution image of skeleton. Skeleton image can be reformed by software in the post-processing workstation. Different skeleton measurement indexes of anthropology, such as diameter, angle, area and volume, can be measured on section and reformative images. Measurement process is barely affected by human factors. This paper reviews the literatures at home and abroad about the application of measuring skeleton by CT in forensic anthropology research for individual identification in four aspects, including sex determination, height infer, facial soft tissue thickness measurement and age estimation. The major technology and the application of CT in forensic anthropology research are compared and discussed, respectively. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Concurrent Image Processing Executive (CIPE). Volume 3: User's guide

NASA Technical Reports Server (NTRS)

Lee, Meemong; Cooper, Gregory T.; Groom, Steven L.; Mazer, Alan S.; Williams, Winifred I.; Kong, Mih-Seh

1990-01-01

CIPE (the Concurrent Image Processing Executive) is both an executive which organizes the parameter inputs for hypercube applications and an environment which provides temporary data workspace and simple real-time function definition facilities for image analysis. CIPE provides two types of user interface. The Command Line Interface (CLI) provides a simple command-driven environment allowing interactive function definition and evaluation of algebraic expressions. The menu interface employs a hierarchical screen-oriented menu system where the user is led through a menu tree to any specific application and then given a formatted panel screen for parameter entry. How to initialize the system through the setup function, how to read data into CIPE symbols, how to manipulate and display data through the use of executive functions, and how to run an application in either user interface mode, are described.

The microcomputer in the dental office: a new diagnostic aid.

PubMed

van der Stelt, P F

1985-06-01

The first computer applications in the dental office were based upon standard accountancy procedures. Recently, more and more computer applications have become available to meet the specific requirements of dental practice. This implies not only business procedures, but also facilities to store patient records in the system and retrieve them easily. Another development concerns the automatic calculation of diagnostic data such as those provided in cephalometric analysis. Furthermore, growth and surgical results in the craniofacial area can be predicted by computerized extrapolation. Computers have been useful in obtaining the patient's anamnestic data objectively and for the making of decisions based on such data. Computer-aided instruction systems have been developed for undergraduate students to bridge the gap between textbook and patient interaction without the risks inherent in the latter. Radiology will undergo substantial changes as a result of the application of electronic imaging devices instead of the conventional radiographic films. Computer-assisted electronic imaging will enable image processing, image enhancement, pattern recognition and data transmission for consultation and storage purposes. Image processing techniques will increase image quality whilst still allowing low-dose systems. Standardization of software and system configuration and the development of 'user friendly' programs is the major concern for the near future.

A Multimode Optical Imaging System for Preclinical Applications In Vivo: Technology Development, Multiscale Imaging, and Chemotherapy Assessment

PubMed Central

Hwang, Jae Youn; Wachsmann-Hogiu, Sebastian; Ramanujan, V. Krishnan; Ljubimova, Julia; Gross, Zeev; Gray, Harry B.; Medina-Kauwe, Lali K.; Farkas, Daniel L.

2012-01-01

Purpose Several established optical imaging approaches have been applied, usually in isolation, to preclinical studies; however, truly useful in vivo imaging may require a simultaneous combination of imaging modalities to examine dynamic characteristics of cells and tissues. We developed a new multimode optical imaging system designed to be application-versatile, yielding high sensitivity, and specificity molecular imaging. Procedures We integrated several optical imaging technologies, including fluorescence intensity, spectral, lifetime, intravital confocal, two-photon excitation, and bioluminescence, into a single system that enables functional multiscale imaging in animal models. Results The approach offers a comprehensive imaging platform for kinetic, quantitative, and environmental analysis of highly relevant information, with micro-to-macroscopic resolution. Applied to small animals in vivo, this provides superior monitoring of processes of interest, represented here by chemo-/nanoconstruct therapy assessment. Conclusions This new system is versatile and can be optimized for various applications, of which cancer detection and targeted treatment are emphasized here. PMID:21874388

High-performance web viewer for cardiac images

NASA Astrophysics Data System (ADS)

dos Santos, Marcelo; Furuie, Sergio S.

2004-04-01

With the advent of the digital devices for medical diagnosis the use of the regular films in radiology has decreased. Thus, the management and handling of medical images in digital format has become an important and critical task. In Cardiology, for example, the main difficulty is to display dynamic images with the appropriated color palette and frame rate used on acquisition process by Cath, Angio and Echo systems. In addition, other difficulty is handling large images in memory by any existing personal computer, including thin clients. In this work we present a web-based application that carries out these tasks with robustness and excellent performance, without burdening the server and network. This application provides near-diagnostic quality display of cardiac images stored as DICOM 3.0 files via a web browser and provides a set of resources that allows the viewing of still and dynamic images. It can access image files from the local disks, or network connection. Its features include: allows real-time playback, dynamic thumbnails image viewing during loading, access to patient database information, image processing tools, linear and angular measurements, on-screen annotations, image printing and exporting DICOM images to other image formats, and many others, all characterized by a pleasant user-friendly interface, inside a Web browser by means of a Java application. This approach offers some advantages over the most of medical images viewers, such as: facility of installation, integration with other systems by means of public and standardized interfaces, platform independence, efficient manipulation and display of medical images, all with high performance.

Image Processing

NASA Technical Reports Server (NTRS)

1993-01-01

Electronic Imagery, Inc.'s ImageScale Plus software, developed through a Small Business Innovation Research (SBIR) contract with Kennedy Space Flight Center for use on space shuttle Orbiter in 1991, enables astronauts to conduct image processing, prepare electronic still camera images in orbit, display them and downlink images to ground based scientists for evaluation. Electronic Imagery, Inc.'s ImageCount, a spin-off product of ImageScale Plus, is used to count trees in Florida orange groves. Other applications include x-ray and MRI imagery, textile designs and special effects for movies. As of 1/28/98, company could not be located, therefore contact/product information is no longer valid.

A novel dual-frequency imaging method for intravascular ultrasound applications.

PubMed

Qiu, Weibao; Chen, Yan; Wong, Chi-Man; Liu, Baoqiang; Dai, Jiyan; Zheng, Hairong

2015-03-01

Intravascular ultrasound (IVUS), which is able to delineate internal structures of vessel wall with fine spatial resolution, has greatly enriched the knowledge of coronary atherosclerosis. A novel dual-frequency imaging method is proposed in this paper for intravascular imaging applications. A probe combined two ultrasonic transducer elements with different center frequencies (36 MHz and 78 MHz) is designed and fabricated with PMN-PT single crystal material. It has the ability to balance both imaging depth and resolution, which are important imaging parameters for clinical test. A dual-channel imaging platform is also proposed for real-time imaging, and this platform has been proven to support programmable processing algorithms, flexible imaging control, and raw RF data acquisition for IVUS applications. Testing results show that the -6 dB axial and lateral imaging resolutions of low-frequency ultrasound are 78 and 132 μm, respectively. In terms of high-frequency ultrasound, axial and lateral resolutions are determined to be as high as 34 and 106 μm. In vitro intravascular imaging on healthy swine aorta is conducted to demonstrate the performance of the dual-frequency imaging method for IVUS applications. Copyright © 2014 Elsevier B.V. All rights reserved.

Directional ratio based on parabolic molecules and its application to the analysis of tubular structures

NASA Astrophysics Data System (ADS)

Labate, Demetrio; Negi, Pooran; Ozcan, Burcin; Papadakis, Manos

2015-09-01

As advances in imaging technologies make more and more data available for biomedical applications, there is an increasing need to develop efficient quantitative algorithms for the analysis and processing of imaging data. In this paper, we introduce an innovative multiscale approach called Directional Ratio which is especially effective to distingush isotropic from anisotropic structures. This task is especially useful in the analysis of images of neurons, the main units of the nervous systems which consist of a main cell body called the soma and many elongated processes called neurites. We analyze the theoretical properties of our method on idealized models of neurons and develop a numerical implementation of this approach for analysis of fluorescent images of cultured neurons. We show that this algorithm is very effective for the detection of somas and the extraction of neurites in images of small circuits of neurons.

IDIMS/GEOPAK: Users manual for a geophysical data display and analysis system

NASA Technical Reports Server (NTRS)

Libert, J. M.

1982-01-01

The application of an existing image analysis system to the display and analysis of geophysical data is described, the potential for expanding the capabilities of such a system toward more advanced computer analytic and modeling functions is investigated. The major features of the IDIMS (Interactive Display and Image Manipulation System) and its applicability for image type analysis of geophysical data are described. Development of a basic geophysical data processing system to permit the image representation, coloring, interdisplay and comparison of geophysical data sets using existing IDIMS functions and to provide for the production of hard copies of processed images was described. An instruction manual and documentation for the GEOPAK subsystem was produced. A training course for personnel in the use of the IDIMS/GEOPAK was conducted. The effectiveness of the current IDIMS/GEOPAK system for geophysical data analysis was evaluated.

Intranucleus Single-Molecule Imaging in Living Cells.

PubMed

Shao, Shipeng; Xue, Boxin; Sun, Yujie

2018-06-01

Many critical processes occurring in mammalian cells are stochastic and can be directly observed at the single-molecule level within their physiological environment, which would otherwise be obscured in an ensemble measurement. There are various fundamental processes in the nucleus, such as transcription, replication, and DNA repair, the study of which can greatly benefit from intranuclear single-molecule imaging. However, the number of such studies is relatively small mainly because of lack of proper labeling and imaging methods. In the past decade, tremendous efforts have been devoted to developing tools for intranuclear imaging. Here, we mainly describe the recent methodological developments of single-molecule imaging and their emerging applications in the live nucleus. We also discuss the remaining issues and provide a perspective on future developments and applications of this field. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Magnetic resonance imaging of chemistry.

PubMed

Britton, Melanie M

2010-11-01

Magnetic resonance imaging (MRI) has long been recognized as one of the most important tools in medical diagnosis and research. However, MRI is also well placed to image chemical reactions and processes, determine the concentration of chemical species, and look at how chemistry couples with environmental factors, such as flow and heterogeneous media. This tutorial review will explain how magnetic resonance imaging works, reviewing its application in chemistry and its ability to directly visualise chemical processes. It will give information on what resolution and contrast are possible, and what chemical and physical parameters can be measured. It will provide examples of the use of MRI to study chemical systems, its application in chemical engineering and the identification of contrast agents for non-clinical applications. A number of studies are presented including investigation of chemical conversion and selectivity in fixed-bed reactors, temperature probes for catalyst pellets, ion mobility during tablet dissolution, solvent dynamics and ion transport in Nafion polymers and the formation of chemical waves and patterns.

Identification of seedling cabbages and weeds using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Target detectionis one of research focues for precision chemical application. This study developed a method to identify seedling cabbages and weeds using hyperspectral spectral imaging. In processing the image data, with ENVI software, after dimension reduction, noise reduction, de-correlation for h...

Display nonlinearity in digital image processing for visual communications

NASA Astrophysics Data System (ADS)

Peli, Eli

1992-11-01

The luminance emitted from a cathode ray tube (CRT) display is a nonlinear function (the gamma function) of the input video signal voltage. In most analog video systems, compensation for this nonlinear transfer function is implemented in the camera amplifiers. When CRT displays are used to present psychophysical stimuli in vision research, the specific display nonlinearity usually is measured and accounted for to ensure that the luminance of each pixel in the synthetic image property represents the intended value. However, when using digital image processing, the linear analog-to-digital converters store a digital image that is nonlinearly related to the displayed or recorded image. The effect of this nonlinear transformation on a variety of image-processing applications used in visual communications is described.

Display nonlinearity in digital image processing for visual communications

NASA Astrophysics Data System (ADS)

Peli, Eli

1991-11-01

The luminance emitted from a cathode ray tube, (CRT) display is a nonlinear function (the gamma function) of the input video signal voltage. In most analog video systems, compensation for this nonlinear transfer function is implemented in the camera amplifiers. When CRT displays are used to present psychophysical stimuli in vision research, the specific display nonlinearity usually is measured and accounted for to ensure that the luminance of each pixel in the synthetic image properly represents the intended value. However, when using digital image processing, the linear analog-to-digital converters store a digital image that is nonlinearly related to the displayed or recorded image. This paper describes the effect of this nonlinear transformation on a variety of image-processing applications used in visual communications.

Partitioning medical image databases for content-based queries on a Grid.

PubMed

Montagnat, J; Breton, V; E Magnin, I

2005-01-01

In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. Grids are promising for content-based image retrieval in medical databases.

Applications based on restored satellite images

NASA Astrophysics Data System (ADS)

Arbel, D.; Levin, S.; Nir, M.; Bhasteker, I.

2005-08-01

Satellites orbit the earth and obtain imagery of the ground below. The quality of satellite images is affected by the properties of the atmospheric imaging path, which degrade the image by blurring it and reducing its contrast. Applications involving satellite images are many and varied. Imaging systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality satellite images because of the variety of applications based on them. The more qualitative is the recorded image, the more information is yielded from the image. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., satellite communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) satellite images are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.

Image processing of aerodynamic data

NASA Technical Reports Server (NTRS)

Faulcon, N. D.

1985-01-01

The use of digital image processing techniques in analyzing and evaluating aerodynamic data is discussed. An image processing system that converts images derived from digital data or from transparent film into black and white, full color, or false color pictures is described. Applications to black and white images of a model wing with a NACA 64-210 section in simulated rain and to computed low properties for transonic flow past a NACA 0012 airfoil are presented. Image processing techniques are used to visualize the variations of water film thicknesses on the wing model and to illustrate the contours of computed Mach numbers for the flow past the NACA 0012 airfoil. Since the computed data for the NACA 0012 airfoil are available only at discrete spatial locations, an interpolation method is used to provide values of the Mach number over the entire field.

Computer image analysis in obtaining characteristics of images: greenhouse tomatoes in the process of generating learning sets of artificial neural networks

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Przybył, J.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.

2014-04-01

The aim of the project was to make the software which on the basis on image of greenhouse tomato allows for the extraction of its characteristics. Data gathered during the image analysis and processing were used to build learning sets of artificial neural networks. Program enables to process pictures in jpeg format, acquisition of statistical information of the picture and export them to an external file. Produced software is intended to batch analyze collected research material and obtained information saved as a csv file. Program allows for analysis of 33 independent parameters implicitly to describe tested image. The application is dedicated to processing and image analysis of greenhouse tomatoes. The program can be used for analysis of other fruits and vegetables of a spherical shape.

Advanced Secure Optical Image Processing for Communications

NASA Astrophysics Data System (ADS)

Al Falou, Ayman

2018-04-01

New image processing tools and data-processing network systems have considerably increased the volume of transmitted information such as 2D and 3D images with high resolution. Thus, more complex networks and long processing times become necessary, and high image quality and transmission speeds are requested for an increasing number of applications. To satisfy these two requests, several either numerical or optical solutions were offered separately. This book explores both alternatives and describes research works that are converging towards optical/numerical hybrid solutions for high volume signal and image processing and transmission. Without being limited to hybrid approaches, the latter are particularly investigated in this book in the purpose of combining the advantages of both techniques. Additionally, pure numerical or optical solutions are also considered since they emphasize the advantages of one of the two approaches separately.

Real-time blind image deconvolution based on coordinated framework of FPGA and DSP

NASA Astrophysics Data System (ADS)

Wang, Ze; Li, Hang; Zhou, Hua; Liu, Hongjun

2015-10-01

Image restoration takes a crucial place in several important application domains. With the increasing of computation requirement as the algorithms become much more complexity, there has been a significant rise in the need for accelerating implementation. In this paper, we focus on an efficient real-time image processing system for blind iterative deconvolution method by means of the Richardson-Lucy (R-L) algorithm. We study the characteristics of algorithm, and an image restoration processing system based on the coordinated framework of FPGA and DSP (CoFD) is presented. Single precision floating-point processing units with small-scale cascade and special FFT/IFFT processing modules are adopted to guarantee the accuracy of the processing. Finally, Comparing experiments are done. The system could process a blurred image of 128×128 pixels within 32 milliseconds, and is up to three or four times faster than the traditional multi-DSPs systems.

Implementation of a General Real-Time Visual Anomaly Detection System Via Soft Computing

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve; Ferrell, Bob; Steinrock, Todd (Technical Monitor)

2001-01-01

The intelligent visual system detects anomalies or defects in real time under normal lighting operating conditions. The application is basically a learning machine that integrates fuzzy logic (FL), artificial neural network (ANN), and generic algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation to separate the object being tested from the background, preprocesses the image using fuzzy reasoning, performs the final segmentation using fuzzy reasoning techniques to retrieve regions with potential anomalies or defects, and finally retrieves them using a learning model built via ANN and GA techniques. FL provides a powerful framework for knowledge representation and overcomes uncertainty and vagueness typically found in image analysis. ANN provides learning capabilities, and GA leads to robust learning results. An application prototype currently runs on a regular PC under Windows NT, and preliminary work has been performed to build an embedded version with multiple image processors. The application prototype is being tested at the Kennedy Space Center (KSC), Florida, to visually detect anomalies along slide basket cables utilized by the astronauts to evacuate the NASA Shuttle launch pad in an emergency. The potential applications of this anomaly detection system in an open environment are quite wide. Another current, potentially viable application at NASA is in detecting anomalies of the NASA Space Shuttle Orbiter's radiator panels.

Uses of software in digital image analysis: a forensic report

NASA Astrophysics Data System (ADS)

Sharma, Mukesh; Jha, Shailendra

2010-02-01

Forensic image analysis is required an expertise to interpret the content of an image or the image itself in legal matters. Major sub-disciplines of forensic image analysis with law enforcement applications include photo-grammetry, photographic comparison, content analysis and image authentication. It has wide applications in forensic science range from documenting crime scenes to enhancing faint or indistinct patterns such as partial fingerprints. The process of forensic image analysis can involve several different tasks, regardless of the type of image analysis performed. Through this paper authors have tried to explain these tasks, which are described in to three categories: Image Compression, Image Enhancement & Restoration and Measurement Extraction. With the help of examples like signature comparison, counterfeit currency comparison and foot-wear sole impression using the software Canvas and Corel Draw.

High-energy proton imaging for biomedical applications

DOE PAGES

Prall, Matthias; Durante, Marco; Berger, Thomas; ...

2016-06-10

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allowsmore » imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. As a result, tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.« less

High-energy proton imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Prall, M.; Durante, M.; Berger, T.; Przybyla, B.; Graeff, C.; Lang, P. M.; Latessa, C.; Shestov, L.; Simoniello, P.; Danly, C.; Mariam, F.; Merrill, F.; Nedrow, P.; Wilde, C.; Varentsov, D.

2016-06-01

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allows imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. Tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.

High-energy proton imaging for biomedical applications

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

Prall, Matthias; Durante, Marco; Berger, Thomas

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allowsmore » imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. As a result, tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.« less

Radiographic applications of spatial frequency multiplexing

NASA Technical Reports Server (NTRS)

Macovski, A.

1981-01-01

The application of spacial frequency encoding techniques which allow different regions of the X-ray spectrum to be encoded on conventional radiographs was studied. Clinical considerations were reviewed, as were experimental studies involving the encoding and decoding of X-ray images at different energies and the subsequent processing of the data to produce images of specific materials in the body.

Graphical user interface for image acquisition and processing

DOEpatents

Goldberg, Kenneth A.

2002-01-01

An event-driven GUI-based image acquisition interface for the IDL programming environment designed for CCD camera control and image acquisition directly into the IDL environment where image manipulation and data analysis can be performed, and a toolbox of real-time analysis applications. Running the image acquisition hardware directly from IDL removes the necessity of first saving images in one program and then importing the data into IDL for analysis in a second step. Bringing the data directly into IDL creates an opportunity for the implementation of IDL image processing and display functions in real-time. program allows control over the available charge coupled device (CCD) detector parameters, data acquisition, file saving and loading, and image manipulation and processing, all from within IDL. The program is built using IDL's widget libraries to control the on-screen display and user interface.

Fitting-free algorithm for efficient quantification of collagen fiber alignment in SHG imaging applications.

PubMed

Hall, Gunnsteinn; Liang, Wenxuan; Li, Xingde

2017-10-01

Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.

Design Criteria For Networked Image Analysis System

NASA Astrophysics Data System (ADS)

Reader, Cliff; Nitteberg, Alan

1982-01-01

Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

Aphasia

MedlinePlus

... of speech-generating applications on mobile devices like tablets can also provide an alternative way to communicate ... on using advanced imaging methods, such as functional magnetic resonance imaging (fMRI), to explore how language is processed in ...

AstroImageJ: Image Processing and Photometric Extraction for Ultra-precise Astronomical Light Curves

NASA Astrophysics Data System (ADS)

Collins, Karen A.; Kielkopf, John F.; Stassun, Keivan G.; Hessman, Frederic V.

2017-02-01

ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.

Application of two-dimensional crystallography and image processing to atomic resolution Z-contrast images.

PubMed

Morgan, David G; Ramasse, Quentin M; Browning, Nigel D

2009-06-01

Zone axis images recorded using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM or Z-contrast imaging) reveal the atomic structure with a resolution that is defined by the probe size of the microscope. In most cases, the full images contain many sub-images of the crystal unit cell and/or interface structure. Thanks to the repetitive nature of these images, it is possible to apply standard image processing techniques that have been developed for the electron crystallography of biological macromolecules and have been used widely in other fields of electron microscopy for both organic and inorganic materials. These methods can be used to enhance the signal-to-noise present in the original images, to remove distortions in the images that arise from either the instrumentation or the specimen itself and to quantify properties of the material in ways that are difficult without such data processing. In this paper, we describe briefly the theory behind these image processing techniques and demonstrate them for aberration-corrected, high-resolution HAADF-STEM images of Si(46) clathrates developed for hydrogen storage.

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.

The Fringe-Imaging Skin Friction Technique PC Application User's Manual

NASA Technical Reports Server (NTRS)

Zilliac, Gregory G.

1999-01-01

A personal computer application (CXWIN4G) has been written which greatly simplifies the task of extracting skin friction measurements from interferograms of oil flows on the surface of wind tunnel models. Images are first calibrated, using a novel approach to one-camera photogrammetry, to obtain accurate spatial information on surfaces with curvature. As part of the image calibration process, an auxiliary file containing the wind tunnel model geometry is used in conjunction with a two-dimensional direct linear transformation to relate the image plane to the physical (model) coordinates. The application then applies a nonlinear regression model to accurately determine the fringe spacing from interferometric intensity records as required by the Fringe Imaging Skin Friction (FISF) technique. The skin friction is found through application of a simple expression that makes use of lubrication theory to relate fringe spacing to skin friction.

Intelligent imaging systems for automotive applications

NASA Astrophysics Data System (ADS)

Thompson, Chris; Huang, Yingping; Fu, Shan

2004-03-01

In common with many other application areas, visual signals are becoming an increasingly important information source for many automotive applications. For several years CCD cameras have been used as research tools for a range of automotive applications. Infrared cameras, RADAR and LIDAR are other types of imaging sensors that have also been widely investigated for use in cars. This paper will describe work in this field performed in C2VIP over the last decade - starting with Night Vision Systems and looking at various other Advanced Driver Assistance Systems. Emerging from this experience, we make the following observations which are crucial for "intelligent" imaging systems: 1. Careful arrangement of sensor array. 2. Dynamic-Self-Calibration. 3. Networking and processing. 4. Fusion with other imaging sensors, both at the image level and the feature level, provides much more flexibility and reliability in complex situations. We will discuss how these problems can be addressed and what are the outstanding issues.

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.

Overview of machine vision methods in x-ray imaging and microtomography

NASA Astrophysics Data System (ADS)

Buzmakov, Alexey; Zolotov, Denis; Chukalina, Marina; Nikolaev, Dmitry; Gladkov, Andrey; Ingacheva, Anastasia; Yakimchuk, Ivan; Asadchikov, Victor

2018-04-01

Digital X-ray imaging became widely used in science, medicine, non-destructive testing. This allows using modern digital images analysis for automatic information extraction and interpretation. We give short review of scientific applications of machine vision in scientific X-ray imaging and microtomography, including image processing, feature detection and extraction, images compression to increase camera throughput, microtomography reconstruction, visualization and setup adjustment.

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

ERIC Educational Resources Information Center

Gil, Pablo

2017-01-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the…

Cache write generate for parallel image processing on shared memory architectures.

PubMed

Wittenbrink, C M; Somani, A K; Chen, C H

1996-01-01

We investigate cache write generate, our cache mode invention. We demonstrate that for parallel image processing applications, the new mode improves main memory bandwidth, CPU efficiency, cache hits, and cache latency. We use register level simulations validated by the UW-Proteus system. Many memory, cache, and processor configurations are evaluated.

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

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.

Web-Based Mapping Puts the World at Your Fingertips

NASA Technical Reports Server (NTRS)

2008-01-01

NASA's award-winning Earth Resources Laboratory Applications Software (ELAS) package was developed at Stennis Space Center. Since 1978, ELAS has been used worldwide for processing satellite and airborne sensor imagery data of the Earth's surface into readable and usable information. DATASTAR Inc., of Picayune, Mississippi, has used ELAS software in the DATASTAR Image Processing Exploitation (DIPEx) desktop and Internet image processing, analysis, and manipulation software. The new DIPEx Version III includes significant upgrades and improvements compared to its esteemed predecessor. A true World Wide Web application, this product evolved with worldwide geospatial dimensionality and numerous other improvements that seamlessly support the World Wide Web version.

Deformation-induced speckle-pattern evolution and feasibility of correlational speckle tracking in optical coherence elastography.

PubMed

Zaitsev, Vladimir Y; Matveyev, Alexandr L; Matveev, Lev A; Gelikonov, Grigory V; Gelikonov, Valentin M; Vitkin, Alex

2015-07-01

Feasibility of speckle tracking in optical coherence tomography (OCT) based on digital image correlation (DIC) is discussed in the context of elastography problems. Specifics of applying DIC methods to OCT, compared to processing of photographic images in mechanical engineering applications, are emphasized and main complications are pointed out. Analytical arguments are augmented by accurate numerical simulations of OCT speckle patterns. In contrast to DIC processing for displacement and strain estimation in photographic images, the accuracy of correlational speckle tracking in deformed OCT images is strongly affected by the coherent nature of speckles, for which strain-induced complications of speckle “blinking” and “boiling” are typical. The tracking accuracy is further compromised by the usually more pronounced pixelated structure of OCT scans compared with digital photographic images in classical DIC applications. Processing of complex-valued OCT data (comprising both amplitude and phase) compared to intensity-only scans mitigates these deleterious effects to some degree. Criteria of the attainable speckle tracking accuracy and its dependence on the key OCT system parameters are established.

Implementation of dictionary pair learning algorithm for image quality improvement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

This paper proposes an image denoising on dictionary pair learning algorithm. Visual information is transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmissions is often corrupted with noise. The received image needs processing before it can be used in applications. Image denoising involves the manipulation of the image data to produce a visually high quality image.

Software architecture for time-constrained machine vision applications

NASA Astrophysics Data System (ADS)

Usamentiaga, Rubén; Molleda, Julio; García, Daniel F.; Bulnes, Francisco G.

2013-01-01

Real-time image and video processing applications require skilled architects, and recent trends in the hardware platform make the design and implementation of these applications increasingly complex. Many frameworks and libraries have been proposed or commercialized to simplify the design and tuning of real-time image processing applications. However, they tend to lack flexibility, because they are normally oriented toward particular types of applications, or they impose specific data processing models such as the pipeline. Other issues include large memory footprints, difficulty for reuse, and inefficient execution on multicore processors. We present a novel software architecture for time-constrained machine vision applications that addresses these issues. The architecture is divided into three layers. The platform abstraction layer provides a high-level application programming interface for the rest of the architecture. The messaging layer provides a message-passing interface based on a dynamic publish/subscribe pattern. A topic-based filtering in which messages are published to topics is used to route the messages from the publishers to the subscribers interested in a particular type of message. The application layer provides a repository for reusable application modules designed for machine vision applications. These modules, which include acquisition, visualization, communication, user interface, and data processing, take advantage of the power of well-known libraries such as OpenCV, Intel IPP, or CUDA. Finally, the proposed architecture is applied to a real machine vision application: a jam detector for steel pickling lines.

Detecting Moving Sources in Astronomical Images (Abstract)

NASA Astrophysics Data System (ADS)

Block, A.

2018-06-01

(Abstract only) Source detection in images is an important part of analyzing astronomical data. This project discusses an implementation of image detection in python, as well as processes for performing photometry in python. Application of these tools to looking for moving sources is also discussed.

Review On Feasibility of Using Satellite Imaging for Risk Management of Derailment Related Turnout Component Failures

NASA Astrophysics Data System (ADS)

Dindar, Serdar; Kaewunruen, Sakdirat; Osman, Mohd H.

2017-10-01

One of the emerging significant advances in engineering, satellite imaging (SI) is becoming very common in any kind of civil engineering projects e.g., bridge, canal, dam, earthworks, power plant, water works etc., to provide an accurate, economical and expeditious means of acquiring a rapid assessment. Satellite imaging services in general utilise combinations of high quality satellite imagery, image processing and interpretation to obtain specific required information, e.g. surface movement analysis. To extract, manipulate and provide such a precise knowledge, several systems, including geographic information systems (GIS) and global positioning system (GPS), are generally used for orthorectification. Although such systems are useful for mitigating risk from projects, their productiveness is arguable and operational risk after application is open to discussion. As the applicability of any novel application to the railway industry is often measured in terms of whether or not it has gained in-depth knowledge and to what degree, as a result of errors during its operation, this novel application generates risk in ongoing projects. This study reviews what can be achievable for risk management of railway turnouts thorough satellite imaging. The methodology is established on the basis of other published articles in this area and the results of applications to understand how applicable such imagining process is on railway turnouts, and how sub-systems in turnouts can be effectively traced/operated with less risk than at present. As a result of this review study, it is aimed that the railway sector better understands risk mitigation in particular applications.

CMOS Image Sensors for High Speed Applications.

PubMed

El-Desouki, Munir; Deen, M Jamal; Fang, Qiyin; Liu, Louis; Tse, Frances; Armstrong, David

2009-01-01

Recent advances in deep submicron CMOS technologies and improved pixel designs have enabled CMOS-based imagers to surpass charge-coupled devices (CCD) imaging technology for mainstream applications. The parallel outputs that CMOS imagers can offer, in addition to complete camera-on-a-chip solutions due to being fabricated in standard CMOS technologies, result in compelling advantages in speed and system throughput. Since there is a practical limit on the minimum pixel size (4∼5 μm) due to limitations in the optics, CMOS technology scaling can allow for an increased number of transistors to be integrated into the pixel to improve both detection and signal processing. Such smart pixels truly show the potential of CMOS technology for imaging applications allowing CMOS imagers to achieve the image quality and global shuttering performance necessary to meet the demands of ultrahigh-speed applications. In this paper, a review of CMOS-based high-speed imager design is presented and the various implementations that target ultrahigh-speed imaging are described. This work also discusses the design, layout and simulation results of an ultrahigh acquisition rate CMOS active-pixel sensor imager that can take 8 frames at a rate of more than a billion frames per second (fps).

Enhancing Web applications in radiology with Java: estimating MR imaging relaxation times.

PubMed

Dagher, A P; Fitzpatrick, M; Flanders, A E; Eng, J

1998-01-01

Java is a relatively new programming language that has been used to develop a World Wide Web-based tool for estimating magnetic resonance (MR) imaging relaxation times, thereby demonstrating how Java may be used for Web-based radiology applications beyond improving the user interface of teaching files. A standard processing algorithm coded with Java is downloaded along with the hypertext markup language (HTML) document. The user (client) selects the desired pulse sequence and inputs data obtained from a region of interest on the MR images. The algorithm is used to modify selected MR imaging parameters in an equation that models the phenomenon being evaluated. MR imaging relaxation times are estimated, and confidence intervals and a P value expressing the accuracy of the final results are calculated. Design features such as simplicity, object-oriented programming, and security restrictions allow Java to expand the capabilities of HTML by offering a more versatile user interface that includes dynamic annotations and graphics. Java also allows the client to perform more sophisticated information processing and computation than is usually associated with Web applications. Java is likely to become a standard programming option, and the development of stand-alone Java applications may become more common as Java is integrated into future versions of computer operating systems.

A Versatile Image Processor For Digital Diagnostic Imaging And Its Application In Computed Radiography

NASA Astrophysics Data System (ADS)

Blume, H.; Alexandru, R.; Applegate, R.; Giordano, T.; Kamiya, K.; Kresina, R.

1986-06-01

In a digital diagnostic imaging department, the majority of operations for handling and processing of images can be grouped into a small set of basic operations, such as image data buffering and storage, image processing and analysis, image display, image data transmission and image data compression. These operations occur in almost all nodes of the diagnostic imaging communications network of the department. An image processor architecture was developed in which each of these functions has been mapped into hardware and software modules. The modular approach has advantages in terms of economics, service, expandability and upgradeability. The architectural design is based on the principles of hierarchical functionality, distributed and parallel processing and aims at real time response. Parallel processing and real time response is facilitated in part by a dual bus system: a VME control bus and a high speed image data bus, consisting of 8 independent parallel 16-bit busses, capable of handling combined up to 144 MBytes/sec. The presented image processor is versatile enough to meet the video rate processing needs of digital subtraction angiography, the large pixel matrix processing requirements of static projection radiography, or the broad range of manipulation and display needs of a multi-modality diagnostic work station. Several hardware modules are described in detail. For illustrating the capabilities of the image processor, processed 2000 x 2000 pixel computed radiographs are shown and estimated computation times for executing the processing opera-tions are presented.

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.

Focus measure method based on the modulus of the gradient of the color planes for digital microscopy

NASA Astrophysics Data System (ADS)

Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel

2018-02-01

The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.

Spatial information technologies for remote sensing today and tomorrow; Proceedings of the Ninth Pecora Symposium, Sioux Falls, SD, October 2-4, 1984

NASA Technical Reports Server (NTRS)

1984-01-01

Topics discussed at the symposium include hardware, geographic information system (GIS) implementation, processing remotely sensed data, spatial data structures, and NASA programs in remote sensing information systems. Attention is also given GIS applications, advanced techniques, artificial intelligence, graphics, spatial navigation, and classification. Papers are included on the design of computer software for geographic image processing, concepts for a global resource information system, algorithm development for spatial operators, and an application of expert systems technology to remotely sensed image analysis.

Non-contact temperature measurement requirements for electronic materials processing

NASA Technical Reports Server (NTRS)

Lehoczky, S. L.; Szofran, F. R.

1988-01-01

The requirements for non-contact temperature measurement capabilities for electronic materials processing in space are assessed. Non-contact methods are probably incapable of sufficient accuracy for the actual absolute measurement of temperatures in most such applications but would be useful for imaging in some applications.

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.

Multispectral image enhancement processing for microsat-borne imager

NASA Astrophysics Data System (ADS)

Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

2017-10-01

With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

Recent advances in high-performance fluorescent and bioluminescent RNA imaging probes.

PubMed

Xia, Yuqiong; Zhang, Ruili; Wang, Zhongliang; Tian, Jie; Chen, Xiaoyuan

2017-05-22

RNA plays an important role in life processes. Imaging of messenger RNAs (mRNAs) and micro-RNAs (miRNAs) not only allows us to learn the formation and transcription of mRNAs and the biogenesis of miRNAs involved in various life processes, but also helps in detecting cancer. High-performance RNA imaging probes greatly expand our view of life processes and enhance the cancer detection accuracy. In this review, we summarize the state-of-the-art high-performance RNA imaging probes, including exogenous probes that can image RNA sequences with special modification and endogeneous probes that can directly image endogenous RNAs without special treatment. For each probe, we review its structure and imaging principle in detail. Finally, we summarize the application of mRNA and miRNA imaging probes in studying life processes as well as in detecting cancer. By correlating the structures and principles of various probes with their practical uses, we compare different RNA imaging probes and offer guidance for better utilization of the current imaging probes and the future design of higher-performance RNA imaging probes.

Video image processing

NASA Technical Reports Server (NTRS)

Murray, N. D.

1985-01-01

Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

The Medical Imaging Interaction Toolkit: challenges and advances : 10 years of open-source development.

PubMed

Nolden, Marco; Zelzer, Sascha; Seitel, Alexander; Wald, Diana; Müller, Michael; Franz, Alfred M; Maleike, Daniel; Fangerau, Markus; Baumhauer, Matthias; Maier-Hein, Lena; Maier-Hein, Klaus H; Meinzer, Hans-Peter; Wolf, Ivo

2013-07-01

The Medical Imaging Interaction Toolkit (MITK) has been available as open-source software for almost 10 years now. In this period the requirements of software systems in the medical image processing domain have become increasingly complex. The aim of this paper is to show how MITK evolved into a software system that is able to cover all steps of a clinical workflow including data retrieval, image analysis, diagnosis, treatment planning, intervention support, and treatment control. MITK provides modularization and extensibility on different levels. In addition to the original toolkit, a module system, micro services for small, system-wide features, a service-oriented architecture based on the Open Services Gateway initiative (OSGi) standard, and an extensible and configurable application framework allow MITK to be used, extended and deployed as needed. A refined software process was implemented to deliver high-quality software, ease the fulfillment of regulatory requirements, and enable teamwork in mixed-competence teams. MITK has been applied by a worldwide community and integrated into a variety of solutions, either at the toolkit level or as an application framework with custom extensions. The MITK Workbench has been released as a highly extensible and customizable end-user application. Optional support for tool tracking, image-guided therapy, diffusion imaging as well as various external packages (e.g. CTK, DCMTK, OpenCV, SOFA, Python) is available. MITK has also been used in several FDA/CE-certified applications, which demonstrates the high-quality software and rigorous development process. MITK provides a versatile platform with a high degree of modularization and interoperability and is well suited to meet the challenging tasks of today's and tomorrow's clinically motivated research.

Conference on Charge-Coupled Device Technology and Applications

NASA Technical Reports Server (NTRS)

1976-01-01

Papers were presented from the conference on charge coupled device technology and applications. The following topics were investigated: data processing; infrared; devices and testing; electron-in, x-ray, radiation; and applications. The emphasis was on the advances of mutual relevance and potential significance both to industry and NASA's current and future requirements in all fields of imaging, signal processing and memory.

Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.

1995-10-01

In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.

Gold nanoparticle contrast agents in advanced X-ray imaging technologies.

PubMed

Ahn, Sungsook; Jung, Sung Yong; Lee, Sang Joon

2013-05-17

Recently, there has been significant progress in the field of soft- and hard-X-ray imaging for a wide range of applications, both technically and scientifically, via developments in sources, optics and imaging methodologies. While one community is pursuing extensive applications of available X-ray tools, others are investigating improvements in techniques, including new optics, higher spatial resolutions and brighter compact sources. For increased image quality and more exquisite investigation on characteristic biological phenomena, contrast agents have been employed extensively in imaging technologies. Heavy metal nanoparticles are excellent absorbers of X-rays and can offer excellent improvements in medical diagnosis and X-ray imaging. In this context, the role of gold (Au) is important for advanced X-ray imaging applications. Au has a long-history in a wide range of medical applications and exhibits characteristic interactions with X-rays. Therefore, Au can offer a particular advantage as a tracer and a contrast enhancer in X-ray imaging technologies by sensing the variation in X-ray attenuation in a given sample volume. This review summarizes basic understanding on X-ray imaging from device set-up to technologies. Then this review covers recent studies in the development of X-ray imaging techniques utilizing gold nanoparticles (AuNPs) and their relevant applications, including two- and three-dimensional biological imaging, dynamical processes in a living system, single cell-based imaging and quantitative analysis of circulatory systems and so on. In addition to conventional medical applications, various novel research areas have been developed and are expected to be further developed through AuNP-based X-ray imaging technologies.

Study on field weed recognition in real time

NASA Astrophysics Data System (ADS)

He, Yong; Pan, Jiazhi; Zhang, Yun

2006-02-01

This research aimed to identify weeds from crops in early stage in the field 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, ir red), 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. In this research, MS3100 3CCD camera is used to get images of 6 kinds of weeds and crops. Part of these images contained more than 2 kinds of plants. The leaves' shapes, sizes and colors may be very similar or differs from each other greatly. Some are sword-shaped and some (are) round. Some are large as palm and some small as peanut. Some are little brown while other is blue or green. Different combinations are taken into consideration. By the application of image-processing toolkit in MATLAB, the different areas in the image can be segmented clearly. The texture of the images was also analyzed. The processing methods include operations, such as edge detection, erosion, dilation and other algorithms to process the edge vectors and textures. It is of great importance to segment, in real time, the different areas in digital images in field. When the technique is applied in precision farming, many energies and herbicides and many other materials can be saved. At present time large scale softwares as MATLAB on PC are also used, but the computation can be reduced and integrated into a small embedded system. The research results have shown that the application of this technique in agricultural engineering is feasible and of great economical value.

Processing Cones: A Computational Structure for Image Analysis.

DTIC Science & Technology

1981-12-01

image analysis applications, referred to as a processing cone, is described and sample algorithms are presented. A fundamental characteristic of the structure is its hierarchical organization into two-dimensional arrays of decreasing resolution. In this architecture, a protypical function is defined on a local window of data and applied uniformly to all windows in a parallel manner. Three basic modes of processing are supported in the cone: reduction operations (upward processing), horizontal operations (processing at a single level) and projection operations (downward

Radar image enhancement and simulation as an aid to interpretation and training

NASA Technical Reports Server (NTRS)

Frost, V. S.; Stiles, J. A.; Holtzman, J. C.; Dellwig, L. F.; Held, D. N.

1980-01-01

Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.

Satellite land remote sensing advancements for the eighties; Proceedings of the Eighth Pecora Symposium, Sioux Falls, SD, October 4-7, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

Among the topics discussed are NASA's land remote sensing plans for the 1980s, the evolution of Landsat 4 and the performance of its sensors, the Landsat 4 thematic mapper image processing system radiometric and geometric characteristics, data quality, image data radiometric analysis and spectral/stratigraphic analysis, and thematic mapper agricultural, forest resource and geological applications. Also covered are geologic applications of side-looking airborne radar, digital image processing, the large format camera, the RADARSAT program, the SPOT 1 system's program status, distribution plans, and simulation program, Space Shuttle multispectral linear array studies of the optical and biological properties of terrestrial land cover, orbital surveys of solar-stimulated luminescence, the Space Shuttle imaging radar research facility, and Space Shuttle-based polar ice sounding altimetry.

A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

PubMed

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

PubMed Central

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

Automatic Extraction of Planetary Image Features

NASA Technical Reports Server (NTRS)

Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

2009-01-01

With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

UWGSP7: a real-time optical imaging workstation

NASA Astrophysics Data System (ADS)

Bush, John E.; Kim, Yongmin; Pennington, Stan D.; Alleman, Andrew P.

1995-04-01

With the development of UWGSP7, the University of Washington Image Computing Systems Laboratory has a real-time workstation for continuous-wave (cw) optical reflectance imaging. Recent discoveries in optical science and imaging research have suggested potential practical use of the technology as a medical imaging modality and identified the need for a machine to support these applications in real time. The UWGSP7 system was developed to provide researchers with a high-performance, versatile tool for use in optical imaging experiments with the eventual goal of bringing the technology into clinical use. One of several major applications of cw optical reflectance imaging is tumor imaging which uses a light-absorbing dye that preferentially sequesters in tumor tissue. This property could be used to locate tumors and to identify tumor margins intraoperatively. Cw optical reflectance imaging consists of illumination of a target with a band-limited light source and monitoring the light transmitted by or reflected from the target. While continuously illuminating the target, a control image is acquired and stored. A dye is injected into a subject and a sequence of data images are acquired and processed. The data images are aligned with the control image and then subtracted to obtain a signal representing the change in optical reflectance over time. This signal can be enhanced by digital image processing and displayed in pseudo-color. This type of emerging imaging technique requires a computer system that is versatile and adaptable. The UWGSP7 utilizes a VESA local bus PC as a host computer running the Windows NT operating system and includes ICSL developed add-on boards for image acquisition and processing. The image acquisition board is used to digitize and format the analog signal from the input device into digital frames and to the average frames into images. To accommodate different input devices, the camera interface circuitry is designed in a small mezzanine board that supports the RS-170 standard. The image acquisition board is connected to the image- processing board using a direct connect port which provides a 66 Mbytes/s channel independent of the system bus. The image processing board utilizes the Texas Instruments TMS320C80 Multimedia Video Processor chip. This chip is capable of 2 billion operations per second providing the UWGSP7 with the capability to perform real-time image processing functions like median filtering, convolution and contrast enhancement. This processing power allows interactive analysis of the experiments as compared to current practice of off-line processing and analysis. Due to its flexibility and programmability, the UWGSP7 can be adapted into various research needs in intraoperative optical imaging.

Self-calibration of a noisy multiple-sensor system with genetic algorithms

NASA Astrophysics Data System (ADS)

Brooks, Richard R.; Iyengar, S. Sitharama; Chen, Jianhua

1996-01-01

This paper explores an image processing application of optimization techniques which entails interpreting noisy sensor data. The application is a generalization of image correlation; we attempt to find the optimal gruence which matches two overlapping gray-scale images corrupted with noise. Both taboo search and genetic algorithms are used to find the parameters which match the two images. A genetic algorithm approach using an elitist reproduction scheme is found to provide significantly superior results. The presentation includes a graphic presentation of the paths taken by tabu search and genetic algorithms when trying to find the best possible match between two corrupted images.

Incorporating digital imaging into dental hygiene practice.

PubMed

Saxe, M J; West, D J

1997-01-01

The objective of this paper is to describe digital imaging technology: available modalities, scientific imaging process, advantages and limitations, and applications to dental hygiene practice. Advances in technology have created innovative imaging modalities for intraoral radiography that eliminate film as the traditional image receptor. Digital imaging generates instantaneous radiographic images on a display monitor following exposure. Advantages include lower patient exposure per image and elimination of film processing. Digital imaging enhances diagnostic capabilities and, therefore, treatment decisions by the oral healthcare provider. Utilization of digital imaging technology for intraoral radiography will advance the practice of dental hygiene. Although spatial resolution is inferior to conventional film, digital imaging provides adequate resolution to diagnose oral diseases. Dental hygienists must evaluate new technologies in radiography to continue providing quality care while reducing patient exposure to ionizing radiation.

Photocontrollable Fluorescent Proteins for Superresolution Imaging

PubMed Central

Shcherbakova, Daria M.; Sengupta, Prabuddha; Lippincott-Schwartz, Jennifer; Verkhusha, Vladislav V.

2014-01-01

Superresolution fluorescence microscopy permits the study of biological processes at scales small enough to visualize fine subcellular structures that are unresolvable by traditional diffraction-limited light microscopy. Many superresolution techniques, including those applicable to live cell imaging, utilize genetically encoded photocontrollable fluorescent proteins. The fluorescence of these proteins can be controlled by light of specific wavelengths. In this review, we discuss the biochemical and photophysical properties of photocontrollable fluorescent proteins that are relevant to their use in superresolution microscopy. We then describe the recently developed photoactivatable, photoswitchable, and reversibly photoswitchable fluorescent proteins, and we detail their particular usefulness in single-molecule localization–based and nonlinear ensemble–based superresolution techniques. Finally, we discuss recent applications of photocontrollable proteins in superresolution imaging, as well as how these applications help to clarify properties of intracellular structures and processes that are relevant to cell and developmental biology, neuroscience, cancer biology and biomedicine. PMID:24895855

The Practical Application of Uav-Based Photogrammetry Under Economic Aspects

NASA Astrophysics Data System (ADS)

Sauerbier, M.; Siegrist, E.; Eisenbeiss, H.; Demir, N.

2011-09-01

Nowadays, small size UAVs (Unmanned Aerial Vehicles) have reached a level of practical reliability and functionality that enables this technology to enter the geomatics market as an additional platform for spatial data acquisition. Though one could imagine a wide variety of interesting sensors to be mounted on such a device, here we will focus on photogrammetric applications using digital cameras. In praxis, UAV-based photogrammetry will only be accepted if it a) provides the required accuracy and an additional value and b) if it is competitive in terms of economic application compared to other measurement technologies. While a) was already proven by the scientific community and results were published comprehensively during the last decade, b) still has to be verified under real conditions. For this purpose, a test data set representing a realistic scenario provided by ETH Zurich was used to investigate cost effectiveness and to identify weak points in the processing chain that require further development. Our investigations are limited to UAVs carrying digital consumer cameras, for larger UAVs equipped with medium format cameras the situation has to be considered as significantly different. Image data was acquired during flights using a microdrones MD4-1000 quadrocopter equipped with an Olympus PE-1 digital compact camera. From these images, a subset of 5 images was selected for processing in order to register the effort of time required for the whole production chain of photogrammetric products. We see the potential of mini UAV-based photogrammetry mainly in smaller areas, up to a size of ca. 100 hectares. Larger areas can be efficiently covered by small airplanes with few images, reducing processing effort drastically. In case of smaller areas of a few hectares only, it depends more on the products required. UAVs can be an enhancement or alternative to GNSS measurements, terrestrial laser scanning and ground based photogrammetry. We selected the above mentioned test data from a project featuring an area of interest within the practical range for mini UAVs. While flight planning and flight operation are already quite efficient processes, the bottlenecks identified are mainly related to image processing. Although we used specific software for image processing, the identified gaps in the processing chain today are valid for most commercial photogrammetric software systems on the market. An outlook proposing improvements for a practicable workflow applicable in projects in private economy will be given.

VICAR - VIDEO IMAGE COMMUNICATION AND RETRIEVAL

NASA Technical Reports Server (NTRS)

Wall, R. J.

1994-01-01

VICAR (Video Image Communication and Retrieval) is a general purpose image processing software system that has been under continuous development since the late 1960's. Originally intended for data from the NASA Jet Propulsion Laboratory's unmanned planetary spacecraft, VICAR is now used for a variety of other applications including biomedical image processing, cartography, earth resources, and geological exploration. The development of this newest version of VICAR emphasized a standardized, easily-understood user interface, a shield between the user and the host operating system, and a comprehensive array of image processing capabilities. Structurally, VICAR can be divided into roughly two parts; a suite of applications programs and an executive which serves as the interfaces between the applications, the operating system, and the user. There are several hundred applications programs ranging in function from interactive image editing, data compression/decompression, and map projection, to blemish, noise, and artifact removal, mosaic generation, and pattern recognition and location. An information management system designed specifically for handling image related data can merge image data with other types of data files. The user accesses these programs through the VICAR executive, which consists of a supervisor and a run-time library. From the viewpoint of the user and the applications programs, the executive is an environment that is independent of the operating system. VICAR does not replace the host computer's operating system; instead, it overlays the host resources. The core of the executive is the VICAR Supervisor, which is based on NASA Goddard Space Flight Center's Transportable Applications Executive (TAE). Various modifications and extensions have been made to optimize TAE for image processing applications, resulting in a user friendly environment. The rest of the executive consists of the VICAR Run-Time Library, which provides a set of subroutines (image I/O, label I/O, parameter I/O, etc.) to facilitate image processing and provide the fastest I/O possible while maintaining a wide variety of capabilities. The run-time library also includes the Virtual Raster Display Interface (VRDI) which allows display oriented applications programs to be written for a variety of display devices using a set of common routines. (A display device can be any frame-buffer type device which is attached to the host computer and has memory planes for the display and manipulation of images. A display device may have any number of separate 8-bit image memory planes (IMPs), a graphics overlay plane, pseudo-color capabilities, hardware zoom and pan, and other features). The VRDI supports the following display devices: VICOM (Gould/Deanza) IP8500, RAMTEK RM-9465, ADAGE (Ikonas) IK3000 and the International Imaging Systems IVAS. VRDI's purpose is to provide a uniform operating environment not only for an application programmer, but for the user as well. The programmer is able to write programs without being concerned with the specifics of the device for which the application is intended. The VICAR Interactive Display Subsystem (VIDS) is a collection of utilities for easy interactive display and manipulation of images on a display device. VIDS has characteristics of both the executive and an application program, and offers a wide menu of image manipulation options. VIDS uses the VRDI to communicate with display devices. The first step in using VIDS to analyze and enhance an image (one simple example of VICAR's numerous capabilities) is to examine the histogram of the image. The histogram is a plot of frequency of occurrence for each pixel value (0 - 255) loaded in the image plane. If, for example, the histogram shows that there are no pixel values below 64 or above 192, the histogram can be "stretched" so that the value of 64 is mapped to zero and 192 is mapped to 255. Now the user can use the full dynamic range of the display device to display the data and better see its contents. Another example of a VIDS procedure is the JMOVIE command, which allows the user to run animations interactively on the display device. JMOVIE uses the concept of "frames", which are the individual frames which comprise the animation to be viewed. The user loads images into the frames after the size and number of frames has been selected. VICAR's source languages are primarily FORTRAN and C, with some VAX Assembler and array processor code. The VICAR run-time library is designed to work equally easily from either FORTRAN or C. The program was implemented on a DEC VAX series computer operating under VMS 4.7. The virtual memory required is 1.5MB. Approximately 180,000 blocks of storage are needed for the saveset. VICAR (version 2.3A/3G/13H) is a copyrighted work with all copyright vested in NASA and is available by license for a period of ten (10) years to approved licensees. This program was developed in 1989.

Pre-Hardware Optimization of Spacecraft Image Processing Software Algorithms and Hardware Implementation

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Flatley, Thomas P.; Hestnes, Phyllis; Jentoft-Nilsen, Marit; Petrick, David J.; Day, John H. (Technical Monitor)

2001-01-01

Spacecraft telemetry rates have steadily increased over the last decade presenting a problem for real-time processing by ground facilities. This paper proposes a solution to a related problem for the Geostationary Operational Environmental Spacecraft (GOES-8) image processing application. Although large super-computer facilities are the obvious heritage solution, they are very costly, making it imperative to seek a feasible alternative engineering solution at a fraction of the cost. The solution is based on a Personal Computer (PC) platform and synergy of optimized software algorithms and re-configurable computing hardware technologies, such as Field Programmable Gate Arrays (FPGA) and Digital Signal Processing (DSP). It has been shown in [1] and [2] that this configuration can provide superior inexpensive performance for a chosen application on the ground station or on-board a spacecraft. However, since this technology is still maturing, intensive pre-hardware steps are necessary to achieve the benefits of hardware implementation. This paper describes these steps for the GOES-8 application, a software project developed using Interactive Data Language (IDL) (Trademark of Research Systems, Inc.) on a Workstation/UNIX platform. The solution involves converting the application to a PC/Windows/RC platform, selected mainly by the availability of low cost, adaptable high-speed RC hardware. In order for the hybrid system to run, the IDL software was modified to account for platform differences. It was interesting to examine the gains and losses in performance on the new platform, as well as unexpected observations before implementing hardware. After substantial pre-hardware optimization steps, the necessity of hardware implementation for bottleneck code in the PC environment became evident and solvable beginning with the methodology described in [1], [2], and implementing a novel methodology for this specific application [6]. The PC-RC interface bandwidth problem for the class of applications with moderate input-output data rates but large intermediate multi-thread data streams has been addressed and mitigated. This opens a new class of satellite image processing applications for bottleneck problems solution using RC technologies. The issue of a science algorithm level of abstraction necessary for RC hardware implementation is also described. Selected Matlab functions already implemented in hardware were investigated for their direct applicability to the GOES-8 application with the intent to create a library of Matlab and IDL RC functions for ongoing work. A complete class of spacecraft image processing applications using embedded re-configurable computing technology to meet real-time requirements, including performance results and comparison with the existing system, is described in this paper.

Development of CCD imaging sensors for space applications, phase 1

NASA Technical Reports Server (NTRS)

Antcliffe, G. A.

1975-01-01

The results of an experimental investigation to develop a large area charge coupled device (CCD) imager for space photography applications are described. Details of the design and processing required to achieve 400 X 400 imagers are presented together with a discussion of the optical characterization techniques developed for this program. A discussion of several aspects of large CCD performance is given with detailed test reports. The areas covered include dark current, uniformity of optical response, square wave amplitude response, spectral responsivity and dynamic range.

Single-pixel imaging by Hadamard transform and its application for hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mizutani, Yasuhiro; Shibuya, Kyuki; Taguchi, Hiroki; Iwata, Tetsuo; Takaya, Yasuhiro; Yasui, Takeshi

2016-10-01

In this paper, we report on comparisons of single-pixel imagings using Hadamard Transform (HT) and the ghost imaging (GI) in the view point of the visibility under weak light conditions. For comparing the two methods, we have discussed about qualities of images based on experimental results and numerical analysis. To detect images by the TH method, we have illuminated the Hadamard-pattern mask and calculated by orthogonal transform. On the other hand, the GH method can detect images by illuminating random patterns and a correlation measurement. For comparing two methods under weak light intensity, we have controlled illuminated intensities of a DMD projector about 0.1 in signal-to-noise ratio. Though a process speed of the HT image was faster then an image via the GI, the GI method has an advantage of detection under weak light condition. An essential difference between the HT and the GI method is discussed about reconstruction process. Finally, we also show a typical application of the single-pixel imaging such as hyperspectral images by using dual-optical frequency combs. An optical setup consists of two fiber lasers, spatial light modulated for generating patten illumination, and a single pixel detector. We are successful to detect hyperspectrul images in a range from 1545 to 1555 nm at 0.01nm resolution.

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.

Three-dimensional imaging and remote sensing imaging; Proceedings of the Meeting, Los Angeles, CA, Jan. 14, 15, 1988

NASA Astrophysics Data System (ADS)

Robbins, Woodrow E.

1988-01-01

The present conference discusses topics in novel technologies and techniques of three-dimensional imaging, human factors-related issues in three-dimensional display system design, three-dimensional imaging applications, and image processing for remote sensing. Attention is given to a 19-inch parallactiscope, a chromostereoscopic CRT-based display, the 'SpaceGraph' true three-dimensional peripheral, advantages of three-dimensional displays, holographic stereograms generated with a liquid crystal spatial light modulator, algorithms and display techniques for four-dimensional Cartesian graphics, an image processing system for automatic retina diagnosis, the automatic frequency control of a pulsed CO2 laser, and a three-dimensional display of magnetic resonance imaging of the spine.

IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java

PubMed Central

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM’s image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis. PMID:25612319

IQM: an extensible and portable open source application for image and signal analysis in Java.

PubMed

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Imperceptible watermarking for security of fundus images in tele-ophthalmology applications and computer-aided diagnosis of retina diseases.

PubMed

Singh, Anushikha; Dutta, Malay Kishore

2017-12-01

The authentication and integrity verification of medical images is a critical and growing issue for patients in e-health services. Accurate identification of medical images and patient verification is an essential requirement to prevent error in medical diagnosis. The proposed work presents an imperceptible watermarking system to address the security issue of medical fundus images for tele-ophthalmology applications and computer aided automated diagnosis of retinal diseases. In the proposed work, patient identity is embedded in fundus image in singular value decomposition domain with adaptive quantization parameter to maintain perceptual transparency for variety of fundus images like healthy fundus or disease affected image. In the proposed method insertion of watermark in fundus image does not affect the automatic image processing diagnosis of retinal objects & pathologies which ensure uncompromised computer-based diagnosis associated with fundus image. Patient ID is correctly recovered from watermarked fundus image for integrity verification of fundus image at the diagnosis centre. The proposed watermarking system is tested in a comprehensive database of fundus images and results are convincing. results indicate that proposed watermarking method is imperceptible and it does not affect computer vision based automated diagnosis of retinal diseases. Correct recovery of patient ID from watermarked fundus image makes the proposed watermarking system applicable for authentication of fundus images for computer aided diagnosis and Tele-ophthalmology applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Text extraction from images in the wild using the Viola-Jones algorithm

NASA Astrophysics Data System (ADS)

Saabna, Raid M.; Zingboim, Eran

2018-04-01

Text Localization and extraction is an important issue in modern applications of computer vision. Applications such as reading and translating texts in the wild or from videos are among the many applications that can benefit results of this field. In this work, we adopt the well-known Viola-Jones algorithm to enable text extraction and localization from images in the wild. The Viola-Jones is an efficient, and a fast image-processing algorithm originally used for face detection. Based on some resemblance between text and face detection tasks in the wild, we have modified the viola-jones to detect regions of interest where text may be localized. In the proposed approach, some modification to the HAAR like features and a semi-automatic process of data set generating and manipulation were presented to train the algorithm. A process of sliding windows with different sizes have been used to scan the image for individual letters and letter clusters existence. A post processing step is used in order to combine the detected letters into words and to remove false positives. The novelty of the presented approach is using the strengths of a modified Viola-Jones algorithm to identify many different objects representing different letters and clusters of similar letters and later combine them into words of varying lengths. Impressive results were obtained on the ICDAR contest data sets.

A software tool of digital tomosynthesis application for patient positioning in radiotherapy.

PubMed

Yan, Hui; Dai, Jian-Rong

2016-03-08

Digital Tomosynthesis (DTS) is an image modality in reconstructing tomographic images from two-dimensional kV projections covering a narrow scan angles. Comparing with conventional cone-beam CT (CBCT), it requires less time and radiation dose in data acquisition. It is feasible to apply this technique in patient positioning in radiotherapy. To facilitate its clinical application, a software tool was developed and the reconstruction processes were accelerated by graphic process-ing unit (GPU). Two reconstruction and two registration processes are required for DTS application which is different from conventional CBCT application which requires one image reconstruction process and one image registration process. The reconstruction stage consists of productions of two types of DTS. One type of DTS is reconstructed from cone-beam (CB) projections covering a narrow scan angle and is named onboard DTS (ODTS), which represents the real patient position in treatment room. Another type of DTS is reconstructed from digitally reconstructed radiography (DRR) and is named reference DTS (RDTS), which represents the ideal patient position in treatment room. Prior to the reconstruction of RDTS, The DRRs are reconstructed from planning CT using the same acquisition setting of CB projections. The registration stage consists of two matching processes between ODTS and RDTS. The target shift in lateral and longitudinal axes are obtained from the matching between ODTS and RDTS in coronal view, while the target shift in longitudinal and vertical axes are obtained from the matching between ODTS and RDTS in sagittal view. In this software, both DRR and DTS reconstruction algorithms were implemented on GPU environments for acceleration purpose. The comprehensive evaluation of this software tool was performed including geometric accuracy, image quality, registration accuracy, and reconstruction efficiency. The average correlation coefficient between DRR/DTS generated by GPU-based algorithm and CPU-based algorithm is 0.99. Based on the measurements of cube phantom on DTS, the geometric errors are within 0.5 mm in three axes. For both cube phantom and pelvic phantom, the registration errors are within 0.5 mm in three axes. Compared with reconstruction performance of CPU-based algorithms, the performances of DRR and DTS reconstructions are improved by a factor of 15 to 20. A GPU-based software tool was developed for DTS application for patient positioning of radiotherapy. The geometric and registration accuracy met the clinical requirement in patient setup of radiotherapy. The high performance of DRR and DTS reconstruction algorithms was achieved by the GPU-based computation environments. It is a useful software tool for researcher and clinician in evaluating DTS application in patient positioning of radiotherapy.

Image processing for drawing recognition

NASA Astrophysics Data System (ADS)

Feyzkhanov, Rustem; Zhelavskaya, Irina

2014-03-01

The task of recognizing edges of rectangular structures is well known. Still, almost all of them work with static images and has no limit on work time. We propose application of conducting homography for the video stream which can be obtained from the webcam. We propose algorithm which can be successfully used for this kind of application. One of the main use cases of such application is recognition of drawings by person on the piece of paper before webcam.

3D printing in X-ray and Gamma-Ray Imaging: A novel method for fabricating high-density imaging apertures☆

PubMed Central

Miller, Brian W.; Moore, Jared W.; Barrett, Harrison H.; Fryé, Teresa; Adler, Steven; Sery, Joe; Furenlid, Lars R.

2011-01-01

Advances in 3D rapid-prototyping printers, 3D modeling software, and casting techniques allow for cost-effective fabrication of custom components in gamma-ray and X-ray imaging systems. Applications extend to new fabrication methods for custom collimators, pinholes, calibration and resolution phantoms, mounting and shielding components, and imaging apertures. Details of the fabrication process for these components, specifically the 3D printing process, cold casting with a tungsten epoxy, and lost-wax casting in platinum are presented. PMID:22199414

Remote hardware-reconfigurable robotic camera

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar; Maya-Rueda, Selene E.

2001-10-01

In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software functionalities that can be exchanged during run time. The system has been validated with an edge detection and a motion processing architecture, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.

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.

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images

PubMed Central

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-01-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM). PMID:24940551

Registration of adaptive optics corrected retinal nerve fiber layer (RNFL) images.

PubMed

Ramaswamy, Gomathy; Lombardo, Marco; Devaney, Nicholas

2014-06-01

Glaucoma is the leading cause of preventable blindness in the western world. Investigation of high-resolution retinal nerve fiber layer (RNFL) images in patients may lead to new indicators of its onset. Adaptive optics (AO) can provide diffraction-limited images of the retina, providing new opportunities for earlier detection of neuroretinal pathologies. However, precise processing is required to correct for three effects in sequences of AO-assisted, flood-illumination images: uneven illumination, residual image motion and image rotation. This processing can be challenging for images of the RNFL due to their low contrast and lack of clearly noticeable features. Here we develop specific processing techniques and show that their application leads to improved image quality on the nerve fiber bundles. This in turn improves the reliability of measures of fiber texture such as the correlation of Gray-Level Co-occurrence Matrix (GLCM).

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

Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

PubMed

Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

2009-08-01

We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

Translational Imaging Spectroscopy for Proximal Sensing

PubMed Central

Rogass, Christian; Koerting, Friederike M.; Mielke, Christian; Brell, Maximilian; Boesche, Nina K.; Bade, Maria; Hohmann, Christian

2017-01-01

Proximal sensing as the near field counterpart of remote sensing offers a broad variety of applications. Imaging spectroscopy in general and translational laboratory imaging spectroscopy in particular can be utilized for a variety of different research topics. Geoscientific applications require a precise pre-processing of hyperspectral data cubes to retrieve at-surface reflectance in order to conduct spectral feature-based comparison of unknown sample spectra to known library spectra. A new pre-processing chain called GeoMAP-Trans for at-surface reflectance retrieval is proposed here as an analogue to other algorithms published by the team of authors. It consists of a radiometric, a geometric and a spectral module. Each module consists of several processing steps that are described in detail. The processing chain was adapted to the broadly used HySPEX VNIR/SWIR imaging spectrometer system and tested using geological mineral samples. The performance was subjectively and objectively evaluated using standard artificial image quality metrics and comparative measurements of mineral and Lambertian diffuser standards with standard field and laboratory spectrometers. The proposed algorithm provides highly qualitative results, offers broad applicability through its generic design and might be the first one of its kind to be published. A high radiometric accuracy is achieved by the incorporation of the Reduction of Miscalibration Effects (ROME) framework. The geometric accuracy is higher than 1 μpixel. The critical spectral accuracy was relatively estimated by comparing spectra of standard field spectrometers to those from HySPEX for a Lambertian diffuser. The achieved spectral accuracy is better than 0.02% for the full spectrum and better than 98% for the absorption features. It was empirically shown that point and imaging spectrometers provide different results for non-Lambertian samples due to their different sensing principles, adjacency scattering impacts on the signal and anisotropic surface reflection properties. PMID:28800111

Processing of Fine-Scale Piezoelectric Ceramic/Polymer Composites for Sensors and Actuators

NASA Technical Reports Server (NTRS)

Janas, V. F.; Safari, A.

1996-01-01

The objective of the research effort at Rutgers is the development of lead zirconate titanate (PZT) ceramic/polymer composites with different designs for transducer applications including hydrophones, biomedical imaging, non-destructive testing, and air imaging. In this review, methods for processing both large area and multifunctional ceramic/polymer composites for acoustic transducers were discussed.

Genetic Algorithms Evolve Optimized Transforms for Signal Processing Applications

DTIC Science & Technology

2005-04-01

coefficient sets describing inverse transforms and matched forward/ inverse transform pairs that consistently outperform wavelets for image compression and reconstruction applications under conditions subject to quantization error.

An evaluation on CT image acquisition method for medical VR applications

NASA Astrophysics Data System (ADS)

Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

2017-02-01

Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

FITS Liberator: Image processing software

NASA Astrophysics Data System (ADS)

Lindberg Christensen, Lars; Nielsen, Lars Holm; Nielsen, Kaspar K.; Johansen, Teis; Hurt, Robert; de Martin, David

2012-06-01

The ESA/ESO/NASA FITS Liberator makes it possible to process and edit astronomical science data in the FITS format to produce stunning images of the universe. Formerly a plugin for Adobe Photoshop, the current version of FITS Liberator is a stand-alone application and no longer requires Photoshop. This image processing software makes it possible to create color images using raw observations from a range of telescopes; the FITS Liberator continues to support the FITS and PDS formats, preferred by astronomers and planetary scientists respectively, which enables data to be processed from a wide range of telescopes and planetary probes, including ESO's Very Large Telescope, the NASA/ESA Hubble Space Telescope, NASA's Spitzer Space Telescope, ESA's XMM-Newton Telescope and Cassini-Huygens or Mars Reconnaissance Orbiter.

Stable image acquisition for mobile image processing applications

NASA Astrophysics Data System (ADS)

Henning, Kai-Fabian; Fritze, Alexander; Gillich, Eugen; Mönks, Uwe; Lohweg, Volker

2015-02-01

Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.

Integrated Imaging and Vision Techniques for Industrial Inspection: A Special Issue on Machine Vision and Applications

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

Liu, Zheng; Ukida, H.; Ramuhalli, Pradeep

2010-06-05

Imaging- and vision-based techniques play an important role in industrial inspection. The sophistication of the techniques assures high- quality performance of the manufacturing process through precise positioning, online monitoring, and real-time classification. Advanced systems incorporating multiple imaging and/or vision modalities provide robust solutions to complex situations and problems in industrial applications. A diverse range of industries, including aerospace, automotive, electronics, pharmaceutical, biomedical, semiconductor, and food/beverage, etc., have benefited from recent advances in multi-modal imaging, data fusion, and computer vision technologies. Many of the open problems in this context are in the general area of image analysis methodologies (preferably in anmore » automated fashion). This editorial article introduces a special issue of this journal highlighting recent advances and demonstrating the successful applications of integrated imaging and vision technologies in industrial inspection.« less

Application of AIS Technology to Forest Mapping

NASA Technical Reports Server (NTRS)

Yool, S. R.; Star, J. L.

1985-01-01

Concerns about environmental effects of large scale deforestation have prompted efforts to map forests over large areas using various remote sensing data and image processing techniques. Basic research on the spectral characteristics of forest vegetation are required to form a basis for development of new techniques, and for image interpretation. Examination of LANDSAT data and image processing algorithms over a portion of boreal forest have demonstrated the complexity of relations between the various expressions of forest canopies, environmental variability, and the relative capacities of different image processing algorithms to achieve high classification accuracies under these conditions. Airborne Imaging Spectrometer (AIS) data may in part provide the means to interpret the responses of standard data and techniques to the vegetation based on its relatively high spectral resolution.

Advances in Clinical and Biomedical Applications of Photoacoustic Imaging

PubMed Central

Su, Jimmy L.; Wang, Bo; Wilson, Katheryne E.; Bayer, Carolyn L.; Chen, Yun-Sheng; Kim, Seungsoo; Homan, Kimberly A.; Emelianov, Stanislav Y.

2010-01-01

Importance of the field Photoacoustic imaging is an imaging modality that derives image contrast from the optical absorption coefficient of the tissue being imaged. The imaging technique is able to differentiate between healthy and diseased tissue with either deeper penetration or higher resolution than other functional imaging modalities currently available. From a clinical standpoint, photoacoustic imaging has demonstrated safety and effectiveness in diagnosing diseased tissue regions using either endogenous tissue contrast or exogenous contrast agents. Furthermore, the potential of photoacoustic imaging has been demonstrated in various therapeutic interventions ranging from drug delivery and release to image-guided therapy and monitoring. Areas covered in this review This article reviews the current state of photoacoustic imaging in biomedicine from a technological perspective, highlights various biomedical and clinical applications of photoacoustic imaging, and gives insights on future directions. What the reader will gain Readers will learn about the various applications of photoacoustic imaging, as well as the various contrast agents that can be used to assist photoacoustic imaging. This review will highlight both pre-clinical and clinical uses for photoacoustic imaging, as well as discuss some of the challenges that must be addressed to move photoacoustic imaging into the clinical realm. Take home message Photoacoustic imaging offers unique advantages over existing imaging modalities. The imaging field is broad with many exciting applications for detecting and diagnosing diseased tissue or processes. Photoacoustics is also used in therapeutic applications to identify and characterize the pathology and then to monitor the treatment. Although the technology is still in its infancy, much work has been done in the pre-clinical arena, and photoacoustic imaging is fast approaching the clinical setting. PMID:21344060

Multimodal nanoparticle imaging agents: design and applications

NASA Astrophysics Data System (ADS)

Burke, Benjamin P.; Cawthorne, Christopher; Archibald, Stephen J.

2017-10-01

Molecular imaging, where the location of molecules or nanoscale constructs can be tracked in the body to report on disease or biochemical processes, is rapidly expanding to include combined modality or multimodal imaging. No single imaging technique can offer the optimum combination of properties (e.g. resolution, sensitivity, cost, availability). The rapid technological advances in hardware to scan patients, and software to process and fuse images, are pushing the boundaries of novel medical imaging approaches, and hand-in-hand with this is the requirement for advanced and specific multimodal imaging agents. These agents can be detected using a selection from radioisotope, magnetic resonance and optical imaging, among others. Nanoparticles offer great scope in this area as they lend themselves, via facile modification procedures, to act as multifunctional constructs. They have relevance as therapeutics and drug delivery agents that can be tracked by molecular imaging techniques with the particular development of applications in optically guided surgery and as radiosensitizers. There has been a huge amount of research work to produce nanoconstructs for imaging, and the parameters for successful clinical translation and validation of therapeutic applications are now becoming much better understood. It is an exciting time of progress for these agents as their potential is closer to being realized with translation into the clinic. The coming 5-10 years will be critical, as we will see if the predicted improvement in clinical outcomes becomes a reality. Some of the latest advances in combination modality agents are selected and the progression pathway to clinical trials analysed. This article is part of the themed issue 'Challenges for chemistry in molecular imaging'.

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

An evolution of image source camera attribution approaches.

PubMed

Jahanirad, Mehdi; Wahab, Ainuddin Wahid Abdul; Anuar, Nor Badrul

2016-05-01

Camera attribution plays an important role in digital image forensics by providing the evidence and distinguishing characteristics of the origin of the digital image. It allows the forensic analyser to find the possible source camera which captured the image under investigation. However, in real-world applications, these approaches have faced many challenges due to the large set of multimedia data publicly available through photo sharing and social network sites, captured with uncontrolled conditions and undergone variety of hardware and software post-processing operations. Moreover, the legal system only accepts the forensic analysis of the digital image evidence if the applied camera attribution techniques are unbiased, reliable, nondestructive and widely accepted by the experts in the field. The aim of this paper is to investigate the evolutionary trend of image source camera attribution approaches from fundamental to practice, in particular, with the application of image processing and data mining techniques. Extracting implicit knowledge from images using intrinsic image artifacts for source camera attribution requires a structured image mining process. In this paper, we attempt to provide an introductory tutorial on the image processing pipeline, to determine the general classification of the features corresponding to different components for source camera attribution. The article also reviews techniques of the source camera attribution more comprehensively in the domain of the image forensics in conjunction with the presentation of classifying ongoing developments within the specified area. The classification of the existing source camera attribution approaches is presented based on the specific parameters, such as colour image processing pipeline, hardware- and software-related artifacts and the methods to extract such artifacts. The more recent source camera attribution approaches, which have not yet gained sufficient attention among image forensics researchers, are also critically analysed and further categorised into four different classes, namely, optical aberrations based, sensor camera fingerprints based, processing statistics based and processing regularities based, to present a classification. Furthermore, this paper aims to investigate the challenging problems, and the proposed strategies of such schemes based on the suggested taxonomy to plot an evolution of the source camera attribution approaches with respect to the subjective optimisation criteria over the last decade. The optimisation criteria were determined based on the strategies proposed to increase the detection accuracy, robustness and computational efficiency of source camera brand, model or device attribution. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Image processing in biodosimetry: A proposal of a generic free software platform.

PubMed

Dumpelmann, Matthias; Cadena da Matta, Mariel; Pereira de Lemos Pinto, Marcela Maria; de Salazar E Fernandes, Thiago; Borges da Silva, Edvane; Amaral, Ademir

2015-08-01

The scoring of chromosome aberrations is the most reliable biological method for evaluating individual exposure to ionizing radiation. However, microscopic analyses of chromosome human metaphases, generally employed to identify aberrations mainly dicentrics (chromosome with two centromeres), is a laborious task. This method is time consuming and its application in biological dosimetry would be almost impossible in case of a large scale radiation incidents. In this project, a generic software was enhanced for automatic chromosome image processing from a framework originally developed for the Framework V project Simbio, of the European Union for applications in the area of source localization from electroencephalographic signals. The platforms capability is demonstrated by a study comparing automatic segmentation strategies of chromosomes from microscopic images.

Applications of Subsurface Radar for Mine Detection

DTIC Science & Technology

1990-12-31

sofware routines for signal/image processing and image display, which are included in the Appendix along with examples of recent images obtained of the... maxima and minima. The case of the M19 shown a main backscattering lobe only 5* wide. These results demonstrate the realiability and consistency of

Open source software in a practical approach for post processing of radiologic images.

PubMed

Valeri, Gianluca; Mazza, Francesco Antonino; Maggi, Stefania; Aramini, Daniele; La Riccia, Luigi; Mazzoni, Giovanni; Giovagnoni, Andrea

2015-03-01

The purpose of this paper is to evaluate the use of open source software (OSS) to process DICOM images. We selected 23 programs for Windows and 20 programs for Mac from 150 possible OSS programs including DICOM viewers and various tools (converters, DICOM header editors, etc.). The programs selected all meet the basic requirements such as free availability, stand-alone application, presence of graphical user interface, ease of installation and advanced features beyond simple display monitor. Capabilities of data import, data export, metadata, 2D viewer, 3D viewer, support platform and usability of each selected program were evaluated on a scale ranging from 1 to 10 points. Twelve programs received a score higher than or equal to eight. Among them, five obtained a score of 9: 3D Slicer, MedINRIA, MITK 3M3, VolView, VR Render; while OsiriX received 10. OsiriX appears to be the only program able to perform all the operations taken into consideration, similar to a workstation equipped with proprietary software, allowing the analysis and interpretation of images in a simple and intuitive way. OsiriX is a DICOM PACS workstation for medical imaging and software for image processing for medical research, functional imaging, 3D imaging, confocal microscopy and molecular imaging. This application is also a good tool for teaching activities because it facilitates the attainment of learning objectives among students and other specialists.

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

Real-time implementations of image segmentation algorithms on shared memory multicore architecture: a survey (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akil, Mohamed

2017-05-01

The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.

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.

Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

NASA Astrophysics Data System (ADS)

Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

The application of use case modeling in designing medical imaging information systems.

PubMed

Safdari, Reza; Farzi, Jebraeil; Ghazisaeidi, Marjan; Mirzaee, Mahboobeh; Goodini, Azadeh

2013-01-01

Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control.

Recent Developments and Applications of Radiation/Detection Technology in Tsinghua University

NASA Astrophysics Data System (ADS)

Kang, Ke-Jun

2010-03-01

Nuclear technology applications have been very important research fields in Tsinghua University (THU) for more than 50 years. This paper describes two major directions and related projects running in THU concerning nuclear technology applications for radiation imaging and nuclear technology applications for astrophysics. Radiation imaging is a significant application of nuclear technology for all kinds of real world needs including security inspections, anti-smuggling operations, and medicine. The current improved imaging systems give much higher quality radiation images. THU has produced accelerating tubes for both industrial and medical accelerators with energy levels ranging from 2.5˜20Mev. Detectors have been produced for medical and industrial imaging as well as for high energy physics experiments such as the MRPC with fast time and position resolutions. DR and CT systems for radiation imaging systems have been continuously improved with new system designs and improved algorithms for image reconstruction and processing. Two important new key initiatives are the dual-energy radiography and dual-energy CT systems. Dual-energy CT imaging improves material discrimination by providing both the electron density and the atomic number distribution of scanned objects. Finally, this paper also introduces recent developments related to the hard X-ray modulation telescope (HXMT) provided by THU.

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.

Technique of diffusion weighted imaging and its application in stroke

NASA Astrophysics Data System (ADS)

Li, Enzhong; Tian, Jie; Han, Ying; Wang, Huifang; Li, Wu; He, Huiguang

2003-05-01

To study the application of diffusion weighted imaging and image post processing in the diagnosis of stroke, especially in acute stroke, 205 patients were examined by 1.5 T or 1.0 T MRI scanner and the images such as T1, T2 and diffusion weighted images were obtained. Image post processing was done with "3D Med System" developed by our lab to analyze data and acquire the apparent diffusion coefficient (ADC) map. In acute and subacute stage of stroke, the signal in cerebral infarction areas changed to hyperintensity in T2- and diffusion-weighted images, normal or hypointensity in T1-weighted images. In hyperacute stage, however, the signal was hyperintense just in the diffusion weighted imaes; others were normal. In the chronic stage, the signal in T1- and diffusion-weighted imaging showed hypointensity and hyperintensity in T2 weighted imaging. Because ADC declined obviously in acute and subacute stage of stroke, the lesion area was hypointensity in ADC map. With the development of the disease, ADC gradually recovered and then changed to hyperintensity in ADC map in chronic stage. Using diffusion weighted imaging and ADC mapping can make a diagnosis of stroke, especially in the hyperacute stage of stroke, and can differentiate acute and chronic stroke.

Active thermography and post-processing image enhancement for recovering of abraded and paint-covered alphanumeric identification marks

NASA Astrophysics Data System (ADS)

Montanini, R.; Quattrocchi, A.; Piccolo, S. A.

2016-09-01

Alphanumeric marking is a common technique employed in industrial applications for identification of products. However, the realised mark can undergo deterioration, either by extensive use or voluntary deletion (e.g. removal of identification numbers of weapons or vehicles). For recovery of the lost data many destructive or non-destructive techniques have been endeavoured so far, which however present several restrictions. In this paper, active infrared thermography has been exploited for the first time in order to assess its effectiveness in restoring paint covered and abraded labels made by means of different manufacturing processes (laser, dot peen, impact, cold press and scribe). Optical excitation of the target surface has been achieved using pulse (PT), lock-in (LT) and step heating (SHT) thermography. Raw infrared images were analysed with a dedicated image processing software originally developed in Matlab™, exploiting several methods, which include thermographic signal reconstruction (TSR), guided filtering (GF), block guided filtering (BGF) and logarithmic transformation (LN). Proper image processing of the raw infrared images resulted in superior contrast and enhanced readability. In particular, for deeply abraded marks, good outcomes have been obtained by application of logarithmic transformation to raw PT images and block guided filtering to raw phase LT images. With PT and LT it was relatively easy to recover labels covered by paint, with the latter one providing better thermal contrast for all the examined targets. Step heating thermography never led to adequate label identification instead.

Prewarping techniques in imaging: applications in nanotechnology and biotechnology

NASA Astrophysics Data System (ADS)

Poonawala, Amyn; Milanfar, Peyman

2005-03-01

In all imaging systems, the underlying process introduces undesirable distortions that cause the output signal to be a warped version of the input. When the input to such systems can be controlled, pre-warping techniques can be employed which consist of systematically modifying the input such that it cancels out (or compensates for) the process losses. In this paper, we focus on the mask (reticle) design problem for 'optical micro-lithography', a process similar to photographic printing used for transferring binary circuit patterns onto silicon wafers. We use a pixel-based mask representation and model the above process as a cascade of convolution (aerial image formation) and thresholding (high-contrast recording) operations. The pre-distorted mask is obtained by minimizing the norm of the difference between the 'desired' output image and the 'reproduced' output image. We employ the regularization framework to ensure that the resulting masks are close-to-binary as well as simple and easy to fabricate. Finally, we provide insight into two additional applications of pre-warping techniques. First is 'e-beam lithography', used for fabricating nano-scale structures, and second is 'electronic visual prosthesis' which aims at providing limited vision to the blind by using a prosthetic retinally implanted chip capable of electrically stimulating the retinal neuron cells.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

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

Small Interactive Image Processing System (SMIPS) system description

NASA Technical Reports Server (NTRS)

Moik, J. G.

1973-01-01

The Small Interactive Image Processing System (SMIPS) operates under control of the IBM-OS/MVT operating system and uses an IBM-2250 model 1 display unit as interactive graphic device. The input language in the form of character strings or attentions from keys and light pen is interpreted and causes processing of built-in image processing functions as well as execution of a variable number of application programs kept on a private disk file. A description of design considerations is given and characteristics, structure and logic flow of SMIPS are summarized. Data management and graphic programming techniques used for the interactive manipulation and display of digital pictures are also discussed.

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.

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.

Rare-earth-doped materials with application to optical signal processing, quantum information science, and medical imaging technology

NASA Astrophysics Data System (ADS)

Cone, R. L.; Thiel, C. W.; Sun, Y.; Böttger, Thomas; Macfarlane, R. M.

2012-02-01

Unique spectroscopic properties of isolated rare earth ions in solids offer optical linewidths rivaling those of trapped single atoms and enable a variety of recent applications. We design rare-earth-doped crystals, ceramics, and fibers with persistent or transient "spectral hole" recording properties for applications including high-bandwidth optical signal processing where light and our solids replace the high-bandwidth portion of the electronics; quantum cryptography and information science including the goal of storage and recall of single photons; and medical imaging technology for the 700-900 nm therapeutic window. Ease of optically manipulating rare-earth ions in solids enables capturing complex spectral information in 105 to 108 frequency bins. Combining spatial holography and spectral hole burning provides a capability for processing high-bandwidth RF and optical signals with sub-MHz spectral resolution and bandwidths of tens to hundreds of GHz for applications including range-Doppler radar and high bandwidth RF spectral analysis. Simply stated, one can think of these crystals as holographic recording media capable of distinguishing up to 108 different colors. Ultra-narrow spectral holes also serve as a vibration-insensitive sub-kHz frequency reference for laser frequency stabilization to a part in 1013 over tens of milliseconds. The unusual properties and applications of spectral hole burning of rare earth ions in optical materials are reviewed. Experimental results on the promising Tm3+:LiNbO3 material system are presented and discussed for medical imaging applications. Finally, a new application of these materials as dynamic optical filters for laser noise suppression is discussed along with experimental demonstrations and theoretical modeling of the process.

The future of imaging spectroscopy - Prospective technologies and applications

USGS Publications Warehouse

Schaepman, M.E.; Green, R.O.; Ungar, S.G.; Curtiss, B.; Boardman, J.; Plaza, A.J.; Gao, B.-C.; Ustin, S.; Kokaly, R.; Miller, J.R.; Jacquemoud, S.; Ben-Dor, E.; Clark, R.; Davis, C.; Dozier, J.; Goodenough, D.G.; Roberts, D.; Swayze, G.; Milton, E.J.; Goetz, A.F.H.

2006-01-01

Spectroscopy has existed for more than three centuries now. Nonetheless, significant scientific advances have been achieved. We discuss the history of spectroscopy in relation to emerging technologies and applications. Advanced focal plane arrays, optical design, and intelligent on-board logic are prime prospective technologies. Scalable approaches in pre-processing of imaging spectrometer data will receive additional focus. Finally, we focus on new applications monitoring transitional ecological zones, where human impact and disturbance have highest impact as well as in monitoring changes in our natural resources and environment We conclude that imaging spectroscopy enables mapping of biophysical and biochemical variables of the Earth's surface and atmospheric composition with unprecedented accuracy.

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.

Mobile service for open data visualization on geo-based images

NASA Astrophysics Data System (ADS)

Lee, Kiwon; Kim, Kwangseob; Kang, Sanggoo

2015-12-01

Since the early 2010s, governments in most countries have adopted and promoted open data policy and open data platform. Korea are in the same situation, and government and public organizations have operated the public-accessible open data portal systems since 2011. The number of open data and data type have been increasing every year. These trends are more expandable or extensible on mobile environments. The purpose of this study is to design and implement a mobile application service to visualize various typed or formatted public open data with geo-based images on the mobile web. Open data cover downloadable data sets or open-accessible data application programming interface API. Geo-based images mean multi-sensor satellite imageries which are referred in geo-coordinates and matched with digital map sets. System components for mobile service are fully based on open sources and open development environments without any commercialized tools: PostgreSQL for database management system, OTB for remote sensing image processing, GDAL for data conversion, GeoServer for application server, OpenLayers for mobile web mapping, R for data analysis and D3.js for web-based data graphic processing. Mobile application in client side was implemented by using HTML5 for cross browser and cross platform. The result shows many advantageous points such as linking open data and geo-based data, integrating open data and open source, and demonstrating mobile applications with open data. It is expected that this approach is cost effective and process efficient implementation strategy for intelligent earth observing data.

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.

Laser scanning stereomicroscopy for fast volumetric imaging with two-photon excitation and scanned Bessel beams

NASA Astrophysics Data System (ADS)

Yang, Yanlong; Zhou, Xing; Li, Runze; Van Horn, Mark; Peng, Tong; Lei, Ming; Wu, Di; Chen, Xun; Yao, Baoli; Ye, Tong

2015-03-01

Bessel beams have been used in many applications due to their unique optical properties of maintaining their intensity profiles unchanged during propagation. In imaging applications, Bessel beams have been successfully used to provide extended focuses for volumetric imaging and uniformed illumination plane in light-sheet microscopy. Coupled with two-photon excitation, Bessel beams have been successfully used in realizing fluorescence projected volumetric imaging. We demonstrated previously a stereoscopic solution-two-photon fluorescence stereomicroscopy (TPFSM)-for recovering the depth information in volumetric imaging with Bessel beams. In TPFSM, tilted Bessel beams were used to generate stereoscopic images on a laser scanning two-photon fluorescence microscope; upon post image processing we could successfully provide 3D perception of acquired volume images by wearing anaglyph 3D glasses. However, tilted Bessel beams were generated by shifting either an axicon or an objective laterally; the slow imaging speed and severe aberrations made it hard to use in real-time volume imaging. In this article, we report recent improvements of TPFSM with newly designed scanner and imaging software, which allows 3D stereoscopic imaging without moving any of the optical components on the setup. This improvement has dramatically improved focusing qualities and imaging speed so that the TPFSM can be performed potentially in real-time to provide 3D visualization in scattering media without post image processing.

A Spaceborne Synthetic Aperture Radar Partial Fixed-Point Imaging System Using a Field- Programmable Gate Array—Application-Specific Integrated Circuit Hybrid Heterogeneous Parallel Acceleration Technique

PubMed Central

Li, Bingyi; Chen, Liang; Wei, Chunpeng; Xie, Yizhuang; Chen, He; Yu, Wenyue

2017-01-01

With the development of satellite load technology and very large scale integrated (VLSI) circuit technology, onboard real-time synthetic aperture radar (SAR) imaging systems have become a solution for allowing rapid response to disasters. A key goal of the onboard SAR imaging system design is to achieve high real-time processing performance with severe size, weight, and power consumption constraints. In this paper, we analyse the computational burden of the commonly used chirp scaling (CS) SAR imaging algorithm. To reduce the system hardware cost, we propose a partial fixed-point processing scheme. The fast Fourier transform (FFT), which is the most computation-sensitive operation in the CS algorithm, is processed with fixed-point, while other operations are processed with single precision floating-point. With the proposed fixed-point processing error propagation model, the fixed-point processing word length is determined. The fidelity and accuracy relative to conventional ground-based software processors is verified by evaluating both the point target imaging quality and the actual scene imaging quality. As a proof of concept, a field- programmable gate array—application-specific integrated circuit (FPGA-ASIC) hybrid heterogeneous parallel accelerating architecture is designed and realized. The customized fixed-point FFT is implemented using the 130 nm complementary metal oxide semiconductor (CMOS) technology as a co-processor of the Xilinx xc6vlx760t FPGA. A single processing board requires 12 s and consumes 21 W to focus a 50-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. PMID:28672813

A Spaceborne Synthetic Aperture Radar Partial Fixed-Point Imaging System Using a Field- Programmable Gate Array-Application-Specific Integrated Circuit Hybrid Heterogeneous Parallel Acceleration Technique.

PubMed

Yang, Chen; Li, Bingyi; Chen, Liang; Wei, Chunpeng; Xie, Yizhuang; Chen, He; Yu, Wenyue

2017-06-24

With the development of satellite load technology and very large scale integrated (VLSI) circuit technology, onboard real-time synthetic aperture radar (SAR) imaging systems have become a solution for allowing rapid response to disasters. A key goal of the onboard SAR imaging system design is to achieve high real-time processing performance with severe size, weight, and power consumption constraints. In this paper, we analyse the computational burden of the commonly used chirp scaling (CS) SAR imaging algorithm. To reduce the system hardware cost, we propose a partial fixed-point processing scheme. The fast Fourier transform (FFT), which is the most computation-sensitive operation in the CS algorithm, is processed with fixed-point, while other operations are processed with single precision floating-point. With the proposed fixed-point processing error propagation model, the fixed-point processing word length is determined. The fidelity and accuracy relative to conventional ground-based software processors is verified by evaluating both the point target imaging quality and the actual scene imaging quality. As a proof of concept, a field- programmable gate array-application-specific integrated circuit (FPGA-ASIC) hybrid heterogeneous parallel accelerating architecture is designed and realized. The customized fixed-point FFT is implemented using the 130 nm complementary metal oxide semiconductor (CMOS) technology as a co-processor of the Xilinx xc6vlx760t FPGA. A single processing board requires 12 s and consumes 21 W to focus a 50-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384.

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.

Handheld hyperspectral imager for standoff detection of chemical and biological aerosols

NASA Astrophysics Data System (ADS)

Hinnrichs, Michele; Jensen, James O.; McAnally, Gerard

2004-02-01

Pacific Advanced Technology has developed a small hand held imaging spectrometer, Sherlock, for gas leak and aerosol detection and imaging. The system is based on a patent technique that uses diffractive optics and image processing algorithms to detect spectral information about objects in the scene of the camera (IMSS Image Multi-spectral Sensing). This camera has been tested at Dugway Proving Ground and Dstl Porton Down facility looking at Chemical and Biological agent simulants. The camera has been used to investigate surfaces contaminated with chemical agent simulants. In addition to Chemical and Biological detection the camera has been used for environmental monitoring of green house gases and is currently undergoing extensive laboratory and field testing by the Gas Technology Institute, British Petroleum and Shell Oil for applications for gas leak detection and repair. The camera contains an embedded Power PC and a real time image processor for performing image processing algorithms to assist in the detection and identification of gas phase species in real time. In this paper we will present an over view of the technology and show how it has performed for different applications, such as gas leak detection, surface contamination, remote sensing and surveillance applications. In addition a sampling of the results form TRE field testing at Dugway in July of 2002 and Dstl at Porton Down in September of 2002 will be given.

The evolution of medical imaging from qualitative to quantitative: opportunities, challenges, and approaches (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jackson, Edward F.

2016-04-01

Over the past decade, there has been an increasing focus on quantitative imaging biomarkers (QIBs), which are defined as "objectively measured characteristics derived from in vivo images as indicators of normal biological processes, pathogenic processes, or response to a therapeutic intervention"1. To evolve qualitative imaging assessments to the use of QIBs requires the development and standardization of data acquisition, data analysis, and data display techniques, as well as appropriate reporting structures. As such, successful implementation of QIB applications relies heavily on expertise from the fields of medical physics, radiology, statistics, and informatics as well as collaboration from vendors of imaging acquisition, analysis, and reporting systems. When successfully implemented, QIBs will provide image-derived metrics with known bias and variance that can be validated with anatomically and physiologically relevant measures, including treatment response (and the heterogeneity of that response) and outcome. Such non-invasive quantitative measures can then be used effectively in clinical and translational research and will contribute significantly to the goals of precision medicine. This presentation will focus on 1) outlining the opportunities for QIB applications, with examples to demonstrate applications in both research and patient care, 2) discussing key challenges in the implementation of QIB applications, and 3) providing overviews of efforts to address such challenges from federal, scientific, and professional organizations, including, but not limited to, the RSNA, NCI, FDA, and NIST. 1Sullivan, Obuchowski, Kessler, et al. Radiology, epub August 2015.

Liver CT image processing: a short introduction of the technical elements.

PubMed

Masutani, Y; Uozumi, K; Akahane, Masaaki; Ohtomo, Kuni

2006-05-01

In this paper, we describe the technical aspects of image analysis for liver diagnosis and treatment, including the state-of-the-art of liver image analysis and its applications. After discussion on modalities for liver image analysis, various technical elements for liver image analysis such as registration, segmentation, modeling, and computer-assisted detection are covered with examples performed with clinical data sets. Perspective in the imaging technologies is also reviewed and discussed.

Scalable, High-performance 3D Imaging Software Platform: System Architecture and Application to Virtual Colonoscopy

PubMed Central

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli; Brett, Bevin

2013-01-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. In this work, we have developed a software platform that is designed to support high-performance 3D medical image processing for a wide range of applications using increasingly available and affordable commodity computing systems: multi-core, clusters, and cloud computing systems. To achieve scalable, high-performance computing, our platform (1) employs size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D image processing algorithms; (2) supports task scheduling for efficient load distribution and balancing; and (3) consists of a layered parallel software libraries that allow a wide range of medical applications to share the same functionalities. We evaluated the performance of our platform by applying it to an electronic cleansing system in virtual colonoscopy, with initial experimental results showing a 10 times performance improvement on an 8-core workstation over the original sequential implementation of the system. PMID:23366803

The modulation transfer function and signal-to-noise ratio of different digital filters: a technical approach.

PubMed

Brüllmann, D D; d'Hoedt, B

2011-05-01

The aim of this study was to illustrate the influence of digital filters on the signal-to-noise ratio (SNR) and modulation transfer function (MTF) of digital images. The article will address image pre-processing that may be beneficial for the production of clinically useful digital radiographs with lower radiation dose. Three filters, an arithmetic mean filter, a median filter and a Gaussian filter (standard deviation (SD) = 0.4), with kernel sizes of 3 × 3 pixels and 5 × 5 pixels were tested. Synthetic images with exactly increasing amounts of Gaussian noise were created to gather linear regression of SNR before and after application of digital filters. Artificial stripe patterns with defined amounts of line pairs per millimetre were used to calculate MTF before and after the application of the digital filters. The Gaussian filter with a 5 × 5 kernel size caused the highest noise suppression (SNR increased from 2.22, measured in the synthetic image, to 11.31 in the filtered image). The smallest noise reduction was found with the 3 × 3 median filter. The application of the median filters resulted in no changes in MTF at the different resolutions but did result in the deletion of smaller structures. The 5 × 5 Gaussian filter and the 5 × 5 arithmetic mean filter showed the strongest changes of MTF. The application of digital filters can improve the SNR of a digital sensor; however, MTF can be adversely affected. As such, imaging systems should not be judged solely on their quoted spatial resolutions because pre-processing may influence image quality.

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.

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.

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

Divers-Operated Underwater Photogrammetry: Applications in the Study of Antarctic Benthos

NASA Astrophysics Data System (ADS)

Piazza, P.; Cummings, V.; Lohrer, D.; Marini, S.; Marriott, P.; Menna, F.; Nocerino, E.; Peirano, A.; Schiaparelli, S.

2018-05-01

Ecological studies about marine benthic communities received a major leap from the application of a variety of non-destructive sampling and mapping techniques based on underwater image and video recording. The well-established scientific diving practice consists in the acquisition of single path or `round-trip' over elongated transects, with the imaging device oriented in a nadir looking direction. As it may be expected, the application of automatic image processing procedures to data not specifically acquired for 3D modelling can be risky, especially if proper tools for assessing the quality of the produced results are not employed. This paper, born from an international cooperation, focuses on this topic, which is of great interest for ecological and monitoring benthic studies in Antarctica. Several video footages recorded from different scientific teams in different years are processed with an automatic photogrammetric procedure and salient statistical features are reported to critically analyse the derived results. As expected, the inclusion of oblique images from additional lateral strips may improve the expected accuracy in the object space, without altering too much the current video recording practices.

NASA spinoffs to bioengineering and medicine

NASA Technical Reports Server (NTRS)

Rouse, Doris J.; Winfield, Daniel L.; Canada, S. Catherine

1989-01-01

The societal and economic benefits derived from the application of aerospace technology to improved health care are examined, and examples of the space-technology spinoffs are presented. Special attention is given to the applications of aerospace technology from digital image processing, space medicine and biology, microelectronics, optics and electrooptics, and ultrasonic imaging. The role of the NASA Technology Application Team in helping the potential technology users to identify and evaluate the technology transfer opportunities and to apply space technology in the field of medicine is discussed.

MULTIPLE IMAGING TECHNIQUES DEMONSTRATE THE MANIPULATION OF SURFACES TO REDUCE BACTERIAL CONTAMINATION

EPA Science Inventory

Surface imaging techniques were combined to determine appropriate manipulation of technologically important surfaces for commercial applications. Stainless steel surfaces were engineered to reduce bacterial contamination, biofilm formation, and corrosion during product processing...

Fast Image Subtraction Using Multi-cores and GPUs

NASA Astrophysics Data System (ADS)

Hartung, Steven; Shukla, H.

2013-01-01

Many important image processing techniques in astronomy require a massive number of computations per pixel. Among them is an image differencing technique known as Optimal Image Subtraction (OIS), which is very useful for detecting and characterizing transient phenomena. Like many image processing routines, OIS computations increase proportionally with the number of pixels being processed, and the number of pixels in need of processing is increasing rapidly. Utilizing many-core graphical processing unit (GPU) technology in a hybrid conjunction with multi-core CPU and computer clustering technologies, this work presents a new astronomy image processing pipeline architecture. The chosen OIS implementation focuses on the 2nd order spatially-varying kernel with the Dirac delta function basis, a powerful image differencing method that has seen limited deployment in part because of the heavy computational burden. This tool can process standard image calibration and OIS differencing in a fashion that is scalable with the increasing data volume. It employs several parallel processing technologies in a hierarchical fashion in order to best utilize each of their strengths. The Linux/Unix based application can operate on a single computer, or on an MPI configured cluster, with or without GPU hardware. With GPU hardware available, even low-cost commercial video cards, the OIS convolution and subtraction times for large images can be accelerated by up to three orders of magnitude.

Neutron radiographic viewing system

NASA Technical Reports Server (NTRS)

1972-01-01

The design, development and application of a neutron radiographic viewing system for use in nondestructive testing applications is considered. The system consists of a SEC vidicon camera, neutron image intensifier system, disc recorder, and TV readout. Neutron bombardment of the subject is recorded by an image converter and passed through an optical system into the SEC vidicon. The vidicon output may be stored, or processed for visual readout.

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

Demosaiced pixel super-resolution for multiplexed holographic color imaging

PubMed Central

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2016-01-01

To synthesize a holographic color image, one can sequentially take three holograms at different wavelengths, e.g., at red (R), green (G) and blue (B) parts of the spectrum, and digitally merge them. To speed up the imaging process by a factor of three, a Bayer color sensor-chip can also be used to demultiplex three wavelengths that simultaneously illuminate the sample and digitally retrieve individual set of holograms using the known transmission spectra of the Bayer color filters. However, because the pixels of different channels (R, G, B) on a Bayer color sensor are not at the same physical location, conventional demosaicing techniques generate color artifacts in holographic imaging using simultaneous multi-wavelength illumination. Here we demonstrate that pixel super-resolution can be merged into the color de-multiplexing process to significantly suppress the artifacts in wavelength-multiplexed holographic color imaging. This new approach, termed Demosaiced Pixel Super-Resolution (D-PSR), generates color images that are similar in performance to sequential illumination at three wavelengths, and therefore improves the speed of holographic color imaging by 3-fold. D-PSR method is broadly applicable to holographic microscopy applications, where high-resolution imaging and multi-wavelength illumination are desired. PMID:27353242

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Application of the EM algorithm to radiographic images.

PubMed

Brailean, J C; Little, D; Giger, M L; Chen, C T; Sullivan, B J

1992-01-01

The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.

The Application of Virtex-II Pro FPGA in High-Speed Image Processing Technology of Robot Vision Sensor

NASA Astrophysics Data System (ADS)

Ren, Y. J.; Zhu, J. G.; Yang, X. Y.; Ye, S. H.

2006-10-01

The Virtex-II Pro FPGA is applied to the vision sensor tracking system of IRB2400 robot. The hardware platform, which undertakes the task of improving SNR and compressing data, is constructed by using the high-speed image processing of FPGA. The lower level image-processing algorithm is realized by combining the FPGA frame and the embedded CPU. The velocity of image processing is accelerated due to the introduction of FPGA and CPU. The usage of the embedded CPU makes it easily to realize the logic design of interface. Some key techniques are presented in the text, such as read-write process, template matching, convolution, and some modules are simulated too. In the end, the compare among the modules using this design, using the PC computer and using the DSP, is carried out. Because the high-speed image processing system core is a chip of FPGA, the function of which can renew conveniently, therefore, to a degree, the measure system is intelligent.

An automated dose tracking system for adaptive radiation therapy.

PubMed

Liu, Chang; Kim, Jinkoo; Kumarasiri, Akila; Mayyas, Essa; Brown, Stephen L; Wen, Ning; Siddiqui, Farzan; Chetty, Indrin J

2018-02-01

The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART. Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools. The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement. An efficient and convenient dose tracking system for ART in the clinical setting is presented. The software and automated processes were rigorously evaluated and validated using patient image datasets. Automation of the various procedures has improved efficiency significantly, allowing for the routine clinical application of ART for improving radiation therapy effectiveness. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A Real-Time Image Acquisition And Processing System For A RISC-Based Microcomputer

NASA Astrophysics Data System (ADS)

Luckman, Adrian J.; Allinson, Nigel M.

1989-03-01

A low cost image acquisition and processing system has been developed for the Acorn Archimedes microcomputer. Using a Reduced Instruction Set Computer (RISC) architecture, the ARM (Acorn Risc Machine) processor provides instruction speeds suitable for image processing applications. The associated improvement in data transfer rate has allowed real-time video image acquisition without the need for frame-store memory external to the microcomputer. The system is comprised of real-time video digitising hardware which interfaces directly to the Archimedes memory, and software to provide an integrated image acquisition and processing environment. The hardware can digitise a video signal at up to 640 samples per video line with programmable parameters such as sampling rate and gain. Software support includes a work environment for image capture and processing with pixel, neighbourhood and global operators. A friendly user interface is provided with the help of the Archimedes Operating System WIMP (Windows, Icons, Mouse and Pointer) Manager. Windows provide a convenient way of handling images on the screen and program control is directed mostly by pop-up menus.

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

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

Direct Digital Demultiplexing of Analog TDM Signals for Cable Reduction in Ultrasound Imaging Catheters

PubMed Central

Carpenter, Thomas M.; Rashid, M. Wasequr; Ghovanloo, Maysam; Cowell, David M. J.; Freear, Steven; Degertekin, F. Levent

2016-01-01

In real-time catheter based 3D ultrasound imaging applications, gathering data from the transducer arrays is difficult as there is a restriction on cable count due to the diameter of the catheter. Although area and power hungry multiplexing circuits integrated at the catheter tip are used in some applications, these are unsuitable for use in small sized catheters for applications like intracardiac imaging. Furthermore, the length requirement for catheters and limited power available to on-chip cable drivers leads to limited signal strength at the receiver end. In this paper an alternative approach using Analog Time Division Multiplexing (TDM) is presented which addresses the cable restrictions of ultrasound catheters. A novel digital demultiplexing technique is also described which allows for a reduction in the number of analog signal processing stages required. The TDM and digital demultiplexing schemes are demonstrated for an intracardiac imaging system that would operate in the 4 MHz to 11 MHz range. A TDM integrated circuit (IC) with 8:1 multiplexer is interfaced with a fast ADC through a micro-coaxial catheter cable bundle, and processed with an FPGA RTL simulation. Input signals to the TDM IC are recovered with −40 dB crosstalk between channels on the same micro-coax, showing the feasibility of this system for ultrasound imaging applications. PMID:27116738

Quantum image processing: A review of advances in its security technologies

NASA Astrophysics Data System (ADS)

Yan, Fei; Iliyasu, Abdullah M.; Le, Phuc Q.

In this review, we present an overview of the advances made in quantum image processing (QIP) comprising of the image representations, the operations realizable on them, and the likely protocols and algorithms for their applications. In particular, we focus on recent progresses on QIP-based security technologies including quantum watermarking, quantum image encryption, and quantum image steganography. This review is aimed at providing readers with a succinct, yet adequate compendium of the progresses made in the QIP sub-area. Hopefully, this effort will stimulate further interest aimed at the pursuit of more advanced algorithms and experimental validations for available technologies and extensions to other domains.

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.

Efficient image acquisition design for a cancer detection system

NASA Astrophysics Data System (ADS)

Nguyen, Dung; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

2013-09-01

Modern imaging modalities, such as Computed Tomography (CT), Digital Breast Tomosynthesis (DBT) or Magnetic Resonance Tomography (MRT) are able to acquire volumetric images with an isotropic resolution in micrometer (um) or millimeter (mm) range. When used in interactive telemedicine applications, these raw images need a huge storage unit, thereby necessitating the use of high bandwidth data communication link. To reduce the cost of transmission and enable archiving, especially for medical applications, image compression is performed. Recent advances in compression algorithms have resulted in a vast array of data compression techniques, but because of the characteristics of these images, there are challenges to overcome to transmit these images efficiently. In addition, the recent studies raise the low dose mammography risk on high risk patient. Our preliminary studies indicate that by bringing the compression before the analog-to-digital conversion (ADC) stage is more efficient than other compression techniques after the ADC. The linearity characteristic of the compressed sensing and ability to perform the digital signal processing (DSP) during data conversion open up a new area of research regarding the roles of sparsity in medical image registration, medical image analysis (for example, automatic image processing algorithm to efficiently extract the relevant information for the clinician), further Xray dose reduction for mammography, and contrast enhancement.

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Real-time image mosaicing for medical applications.

PubMed

Loewke, Kevin E; Camarillo, David B; Jobst, Christopher A; Salisbury, J Kenneth

2007-01-01

In this paper we describe the development of a robotically-assisted image mosaicing system for medical applications. The processing occurs in real-time due to a fast initial image alignment provided by robotic position sensing. Near-field imaging, defined by relatively large camera motion, requires translations as well as pan and tilt orientations to be measured. To capture these measurements we use 5-d.o.f. sensing along with a hand-eye calibration to account for sensor offset. This sensor-based approach speeds up the mosaicing, eliminates cumulative errors, and readily handles arbitrary camera motions. Our results have produced visually satisfactory mosaics on a dental model but can be extended to other medical images.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

SAR image registration based on Susan algorithm

NASA Astrophysics Data System (ADS)

Wang, Chun-bo; Fu, Shao-hua; Wei, Zhong-yi

2011-10-01

Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the Susan algorithm knowledge firstly, then introduces the process of SAR image registration based on Susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.