Developing Students' Ideas about Lens Imaging: Teaching Experiments with an Image-Based Approach
ERIC Educational Resources Information Center
Grusche, Sascha
2017-01-01
Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists' analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students' ideas, teaching experiments are performed and evaluated using…
Brand, John; Johnson, Aaron P
2014-01-01
In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.
Brand, John; Johnson, Aaron P.
2014-01-01
In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks. PMID:25520675
Bodily Deviations and Body Image in Adolescence
ERIC Educational Resources Information Center
Vilhjalmsson, Runar; Kristjansdottir, Gudrun; Ward, Dianne S.
2012-01-01
Adolescents with unusually sized or shaped bodies may experience ridicule, rejection, or exclusion based on their negatively valued bodily characteristics. Such experiences can have negative consequences for a person's image and evaluation of self. This study focuses on the relationship between bodily deviations and body image and is based on a…
Effect of Reading Ability and Internet Experience on Keyword-Based Image Search
ERIC Educational Resources Information Center
Lei, Pei-Lan; Lin, Sunny S. J.; Sun, Chuen-Tsai
2013-01-01
Image searches are now crucial for obtaining information, constructing knowledge, and building successful educational outcomes. We investigated how reading ability and Internet experience influence keyword-based image search behaviors and performance. We categorized 58 junior-high-school students into four groups of high/low reading ability and…
ATM experiment S-056 image processing requirements definition
NASA Technical Reports Server (NTRS)
1972-01-01
A plan is presented for satisfying the image data processing needs of the S-056 Apollo Telescope Mount experiment. The report is based on information gathered from related technical publications, consultation with numerous image processing experts, and on the experience that was in working on related image processing tasks over a two-year period.
Students' ideas about prismatic images: teaching experiments for an image-based approach
NASA Astrophysics Data System (ADS)
Grusche, Sascha
2017-05-01
Prismatic refraction is a classic topic in science education. To investigate how undergraduate students think about prismatic dispersion, and to see how they change their thinking when observing dispersed images, five teaching experiments were done and analysed according to the Model of Educational Reconstruction. For projection through a prism, the students used a 'split image projection' conceptualisation. For the view through a prism, this conceptualisation was not fruitful. Based on the observed images, six of seven students changed to a 'diverted image projection' conceptualisation. From a comparison between students' and scientists' ideas, teaching implications are derived for an image-based approach.
Developing students’ ideas about lens imaging: teaching experiments with an image-based approach
NASA Astrophysics Data System (ADS)
Grusche, Sascha
2017-07-01
Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists’ analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students’ ideas, teaching experiments are performed and evaluated using qualitative content analysis. Some of the students’ ideas have not been reported before, namely those related to blurry lens images, and those developed by the proposed teaching approach. To describe learning pathways systematically, a conception-versus-time coordinate system is introduced, specifying how teaching actions help students advance toward a scientific understanding.
Psychophysical experiments on the PicHunter image retrieval system
NASA Astrophysics Data System (ADS)
Papathomas, Thomas V.; Cox, Ingemar J.; Yianilos, Peter N.; Miller, Matt L.; Minka, Thomas P.; Conway, Tiffany E.; Ghosn, Joumana
2001-01-01
Psychophysical experiments were conducted on PicHunter, a content-based image retrieval (CBIR) experimental prototype with the following properties: (1) Based on a model of how users respond, it uses Bayes's rule to predict what target users want, given their actions. (2) It possesses an extremely simple user interface. (3) It employs an entropy- based scheme to improve convergence. (4) It introduces a paradigm for assessing the performance of CBIR systems. Experiments 1-3 studied human judgment of image similarity to obtain data for the model. Experiment 4 studied the importance of using: (a) semantic information, (b) memory of earlier input, and (c) relative and absolute judgments of similarity. Experiment 5 tested an approach that we propose for comparing performances of CBIR systems objectively. Finally, experiment 6 evaluated the most informative display-updating scheme that is based on entropy minimization, and confirmed earlier simulation results. These experiments represent one of the first attempts to quantify CBIR performance based on psychophysical studies, and they provide valuable data for improving CBIR algorithms. Even though they were designed with PicHunter in mind, their results can be applied to any CBIR system and, more generally, to any system that involves judgment of image similarity by humans.
Objected-oriented remote sensing image classification method based on geographic ontology model
NASA Astrophysics Data System (ADS)
Chu, Z.; Liu, Z. J.; Gu, H. Y.
2016-11-01
Nowadays, with the development of high resolution remote sensing image and the wide application of laser point cloud data, proceeding objected-oriented remote sensing classification based on the characteristic knowledge of multi-source spatial data has been an important trend on the field of remote sensing image classification, which gradually replaced the traditional method through improving algorithm to optimize image classification results. For this purpose, the paper puts forward a remote sensing image classification method that uses the he characteristic knowledge of multi-source spatial data to build the geographic ontology semantic network model, and carries out the objected-oriented classification experiment to implement urban features classification, the experiment uses protégé software which is developed by Stanford University in the United States, and intelligent image analysis software—eCognition software as the experiment platform, uses hyperspectral image and Lidar data that is obtained through flight in DaFeng City of JiangSu as the main data source, first of all, the experiment uses hyperspectral image to obtain feature knowledge of remote sensing image and related special index, the second, the experiment uses Lidar data to generate nDSM(Normalized DSM, Normalized Digital Surface Model),obtaining elevation information, the last, the experiment bases image feature knowledge, special index and elevation information to build the geographic ontology semantic network model that implement urban features classification, the experiment results show that, this method is significantly higher than the traditional classification algorithm on classification accuracy, especially it performs more evidently on the respect of building classification. The method not only considers the advantage of multi-source spatial data, for example, remote sensing image, Lidar data and so on, but also realizes multi-source spatial data knowledge integration and application of the knowledge to the field of remote sensing image classification, which provides an effective way for objected-oriented remote sensing image classification in the future.
NASA Astrophysics Data System (ADS)
Lin, Wei; Chen, Yu-hua; Wang, Ji-yuan; Gao, Hong-sheng; Wang, Ji-jun; Su, Rong-hua; Mao, Wei
2011-04-01
Detection probability is an important index to represent and estimate target viability, which provides basis for target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great difference will often exist in the datum obtained. By means of studying the relationship between image features and perception quantity based on psychology experiments, the probability model has been established, in which the process is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four feature similarity degrees between target and background were defined. Secondly, the relationship between single image feature similarity degree and perception quantity was set up based on psychological principle, and psychological experiments of target interpretation were designed which includes about five hundred people for interpretation and two hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which include images with single brightness feature difference, images with single chromaticity feature difference, images with single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and experimental results, the relationship between perception quantity with target detection probability has been found. With the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the model quickly and objectively.
Remote sensing image segmentation based on Hadoop cloud platform
NASA Astrophysics Data System (ADS)
Li, Jie; Zhu, Lingling; Cao, Fubin
2018-01-01
To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.
Pipeline for illumination correction of images for high-throughput microscopy.
Singh, S; Bray, M-A; Jones, T R; Carpenter, A E
2014-12-01
The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.
NASA Astrophysics Data System (ADS)
Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro
2015-03-01
This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.
Chan, Leo Li-Ying; Kuksin, Dmitry; Laverty, Daniel J; Saldi, Stephanie; Qiu, Jean
2015-05-01
The ability to accurately determine cell viability is essential to performing a well-controlled biological experiment. Typical experiments range from standard cell culturing to advanced cell-based assays that may require cell viability measurement for downstream experiments. The traditional cell viability measurement method has been the trypan blue (TB) exclusion assay. However, since the introduction of fluorescence-based dyes for cell viability measurement using flow or image-based cytometry systems, there have been numerous publications comparing the two detection methods. Although previous studies have shown discrepancies between TB exclusion and fluorescence-based viability measurements, image-based morphological analysis was not performed in order to examine the viability discrepancies. In this work, we compared TB exclusion and fluorescence-based viability detection methods using image cytometry to observe morphological changes due to the effect of TB on dead cells. Imaging results showed that as the viability of a naturally-dying Jurkat cell sample decreased below 70 %, many TB-stained cells began to exhibit non-uniform morphological characteristics. Dead cells with these characteristics may be difficult to count under light microscopy, thus generating an artificially higher viability measurement compared to fluorescence-based method. These morphological observations can potentially explain the differences in viability measurement between the two methods.
Content dependent selection of image enhancement parameters for mobile displays
NASA Astrophysics Data System (ADS)
Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo
2011-01-01
Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.
Local multifractal detrended fluctuation analysis for non-stationary image's texture segmentation
NASA Astrophysics Data System (ADS)
Wang, Fang; Li, Zong-shou; Li, Jin-wei
2014-12-01
Feature extraction plays a great important role in image processing and pattern recognition. As a power tool, multifractal theory is recently employed for this job. However, traditional multifractal methods are proposed to analyze the objects with stationary measure and cannot for non-stationary measure. The works of this paper is twofold. First, the definition of stationary image and 2D image feature detection methods are proposed. Second, a novel feature extraction scheme for non-stationary image is proposed by local multifractal detrended fluctuation analysis (Local MF-DFA), which is based on 2D MF-DFA. A set of new multifractal descriptors, called local generalized Hurst exponent (Lhq) is defined to characterize the local scaling properties of textures. To test the proposed method, both the novel texture descriptor and other two multifractal indicators, namely, local Hölder coefficients based on capacity measure and multifractal dimension Dq based on multifractal differential box-counting (MDBC) method, are compared in segmentation experiments. The first experiment indicates that the segmentation results obtained by the proposed Lhq are better than the MDBC-based Dq slightly and superior to the local Hölder coefficients significantly. The results in the second experiment demonstrate that the Lhq can distinguish the texture images more effectively and provide more robust segmentations than the MDBC-based Dq significantly.
NASA Astrophysics Data System (ADS)
Deng, Zhipeng; Lei, Lin; Zhou, Shilin
2015-10-01
Automatic image registration is a vital yet challenging task, particularly for non-rigid deformation images which are more complicated and common in remote sensing images, such as distorted UAV (unmanned aerial vehicle) images or scanning imaging images caused by flutter. Traditional non-rigid image registration methods are based on the correctly matched corresponding landmarks, which usually needs artificial markers. It is a rather challenging task to locate the accurate position of the points and get accurate homonymy point sets. In this paper, we proposed an automatic non-rigid image registration algorithm which mainly consists of three steps: To begin with, we introduce an automatic feature point extraction method based on non-linear scale space and uniform distribution strategy to extract the points which are uniform distributed along the edge of the image. Next, we propose a hybrid point matching algorithm using DaLI (Deformation and Light Invariant) descriptor and local affine invariant geometric constraint based on triangulation which is constructed by K-nearest neighbor algorithm. Based on the accurate homonymy point sets, the two images are registrated by the model of TPS (Thin Plate Spline). Our method is demonstrated by three deliberately designed experiments. The first two experiments are designed to evaluate the distribution of point set and the correctly matching rate on synthetic data and real data respectively. The last experiment is designed on the non-rigid deformation remote sensing images and the three experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm compared with other traditional methods.
NASA Astrophysics Data System (ADS)
Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl
2008-03-01
We present an image analysis approach as part of a high-throughput microscopy siRNA-based screening system using cell arrays for the identification of cellular genes involved in hepatitis C and dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in the neighborhood of segmented cell nuclei, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment and single images. In particular, we propose a novel approach for the localization of regions of transfected cells within cell array images, which combines model-based circle fitting and grid fitting. By this scheme we integrate information from single cell array images and knowledge from the complete cell arrays. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behaviour of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.
Biomedical imaging and sensing using flatbed scanners.
Göröcs, Zoltán; Ozcan, Aydogan
2014-09-07
In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.
Biomedical Imaging and Sensing using Flatbed Scanners
Göröcs, Zoltán; Ozcan, Aydogan
2014-01-01
In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600–700 cm2) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings. PMID:24965011
Students' Ideas about Prismatic Images: Teaching Experiments for an Image-Based Approach
ERIC Educational Resources Information Center
Grusche, Sascha
2017-01-01
Prismatic refraction is a classic topic in science education. To investigate how undergraduate students think about prismatic dispersion, and to see how they change their thinking when observing dispersed images, five teaching experiments were done and analysed according to the Model of Educational Reconstruction. For projection through a prism,…
NASA Astrophysics Data System (ADS)
Feng, Di; Fang, Qimeng; Huang, Huaibo; Zhao, Zhengqi; Song, Ningfang
2017-12-01
The development and implementation of a practical instrument based on an embedded technique for autofocus and polarization alignment of polarization maintaining fiber is presented. For focusing efficiency and stability, an image-based focusing algorithm fully considering the image definition evaluation and the focusing search strategy was used to accomplish autofocus. For improving the alignment accuracy, various image-based algorithms of alignment detection were developed with high calculation speed and strong robustness. The instrument can be operated as a standalone device with real-time processing and convenience operations. The hardware construction, software interface, and image-based algorithms of main modules are described. Additionally, several image simulation experiments were also carried out to analyze the accuracy of the above alignment detection algorithms. Both the simulation results and experiment results indicate that the instrument can achieve the accuracy of polarization alignment <±0.1 deg.
The SPQR experiment: detecting damage to orbiting spacecraft with ground-based telescopes
NASA Astrophysics Data System (ADS)
Paolozzi, Antonio; Porfilio, Manfredi; Currie, Douglas G.; Dantowitz, Ronald F.
2007-09-01
The objective of the Specular Point-like Quick Reference (SPQR) experiment was to evaluate the possibility of improving the resolution of ground-based telescopic imaging of manned spacecraft in orbit. The concept was to reduce image distortions due to atmospheric turbulence by evaluating the Point Spread Function (PSF) of a point-like light reference and processing the spacecraft image accordingly. The target spacecraft was the International Space Station (ISS) and the point-like reference was provided by a laser beam emitted by the ground station and reflected back to the telescope by a Cube Corner Reflector (CCR) mounted on an ISS window. The ultimate objective of the experiment was to demonstrate that it is possible to image spacecraft in Low Earth Orbit (LEO) with a resolution of 20 cm, which would have probably been sufficient to detect the damage which caused the Columbia disaster. The experiment was successfully performed from March to May 2005. The paper provides an overview of the SPQR experiment.
Intrinsic motivations drive learning of eye movements: an experiment with human adults.
Caligiore, Daniele; Mustile, Magda; Cipriani, Daniele; Redgrave, Peter; Triesch, Jochen; De Marsico, Maria; Baldassarre, Gianluca
2015-01-01
Intrinsic motivations drive the acquisition of knowledge and skills on the basis of novel or surprising stimuli or the pleasure to learn new skills. In so doing, they are different from extrinsic motivations that are mainly linked to drives that promote survival and reproduction. Intrinsic motivations have been implicitly exploited in several psychological experiments but, due to the lack of proper paradigms, they are rarely a direct subject of investigation. This article investigates how different intrinsic motivation mechanisms can support the learning of visual skills, such as "foveate a particular object in space", using a gaze contingency paradigm. In the experiment participants could freely foveate objects shown in a computer screen. Foveating each of two "button" pictures caused different effects: one caused the appearance of a simple image (blue rectangle) in unexpected positions, while the other evoked the appearance of an always-novel picture (objects or animals). The experiment studied how two possible intrinsic motivation mechanisms might guide learning to foveate one or the other button picture. One mechanism is based on the sudden, surprising appearance of a familiar image at unpredicted locations, and a second one is based on the content novelty of the images. The results show the comparative effectiveness of the mechanism based on image novelty, whereas they do not support the operation of the mechanism based on the surprising location of the image appearance. Interestingly, these results were also obtained with participants that, according to a post experiment questionnaire, had not understood the functions of the different buttons suggesting that novelty-based intrinsic motivation mechanisms might operate even at an unconscious level.
Kalpathy-Cramer, Jayashree; Hersh, William
2008-01-01
In 2006 and 2007, Oregon Health & Science University (OHSU) participated in the automatic image annotation task for medical images at ImageCLEF, an annual international benchmarking event that is part of the Cross Language Evaluation Forum (CLEF). The goal of the automatic annotation task was to classify 1000 test images based on the Image Retrieval in Medical Applications (IRMA) code, given a set of 10,000 training images. There were 116 distinct classes in 2006 and 2007. We evaluated the efficacy of a variety of primarily global features for this classification task. These included features based on histograms, gray level correlation matrices and the gist technique. A multitude of classifiers including k-nearest neighbors, two-level neural networks, support vector machines, and maximum likelihood classifiers were evaluated. Our official error rates for the 1000 test images were 26% in 2006 using the flat classification structure. The error count in 2007 was 67.8 using the hierarchical classification error computation based on the IRMA code in 2007. Confusion matrices as well as clustering experiments were used to identify visually similar classes. The use of the IRMA code did not help us in the classification task as the semantic hierarchy of the IRMA classes did not correspond well with the hierarchy based on clustering of image features that we used. Our most frequent misclassification errors were along the view axis. Subsequent experiments based on a two-stage classification system decreased our error rate to 19.8% for the 2006 dataset and our error count to 55.4 for the 2007 data. PMID:19884953
Detection of latent fingerprints by ultraviolet spectral imaging
NASA Astrophysics Data System (ADS)
Huang, Wei; Xu, Xiaojing; Wang, Guiqiang
2013-12-01
Spectral imaging technology research is becoming more popular in the field of forensic science. Ultraviolet spectral imaging technology is an especial part of the full spectrum of imaging technology. This paper finished the experiment contents of the ultraviolet spectrum imaging method and image acquisition system based on ultraviolet spectral imaging technology. Ultraviolet spectral imaging experiments explores a wide variety of ultraviolet reflectance spectra of the object material curve and its ultraviolet spectrum of imaging modalities, can not only gives a reference for choosing ultraviolet wavelength to show the object surface potential traces of substances, but also gives important data for the ultraviolet spectrum of imaging technology development.
Recognising the forest, but not the trees: an effect of colour on scene perception and recognition.
Nijboer, Tanja C W; Kanai, Ryota; de Haan, Edward H F; van der Smagt, Maarten J
2008-09-01
Colour has been shown to facilitate the recognition of scene images, but only when these images contain natural scenes, for which colour is 'diagnostic'. Here we investigate whether colour can also facilitate memory for scene images, and whether this would hold for natural scenes in particular. In the first experiment participants first studied a set of colour and greyscale natural and man-made scene images. Next, the same images were presented, randomly mixed with a different set. Participants were asked to indicate whether they had seen the images during the study phase. Surprisingly, performance was better for greyscale than for coloured images, and this difference is due to the higher false alarm rate for both natural and man-made coloured scenes. We hypothesized that this increase in false alarm rate was due to a shift from scrutinizing details of the image to recognition of the gist of the (coloured) image. A second experiment, utilizing images without a nameable gist, confirmed this hypothesis as participants now performed equally on greyscale and coloured images. In the final experiment we specifically targeted the more detail-based perception and recognition for greyscale images versus the more gist-based perception and recognition for coloured images with a change detection paradigm. The results show that changes to images are detected faster when image-pairs were presented in greyscale than in colour. This counterintuitive result held for both natural and man-made scenes (but not for scenes without nameable gist) and thus corroborates the shift from more detailed processing of images in greyscale to more gist-based processing of coloured images.
Performance test and image correction of CMOS image sensor in radiation environment
NASA Astrophysics Data System (ADS)
Wang, Congzheng; Hu, Song; Gao, Chunming; Feng, Chang
2016-09-01
CMOS image sensors rival CCDs in domains that include strong radiation resistance as well as simple drive signals, so it is widely applied in the high-energy radiation environment, such as space optical imaging application and video monitoring of nuclear power equipment. However, the silicon material of CMOS image sensors has the ionizing dose effect in the high-energy rays, and then the indicators of image sensors, such as signal noise ratio (SNR), non-uniformity (NU) and bad point (BP) are degraded because of the radiation. The radiation environment of test experiments was generated by the 60Co γ-rays source. The camera module based on image sensor CMV2000 from CMOSIS Inc. was chosen as the research object. The ray dose used for the experiments was with a dose rate of 20krad/h. In the test experiences, the output signals of the pixels of image sensor were measured on the different total dose. The results of data analysis showed that with the accumulation of irradiation dose, SNR of image sensors decreased, NU of sensors was enhanced, and the number of BP increased. The indicators correction of image sensors was necessary, as it was the main factors to image quality. The image processing arithmetic was adopt to the data from the experiences in the work, which combined local threshold method with NU correction based on non-local means (NLM) method. The results from image processing showed that image correction can effectively inhibit the BP, improve the SNR, and reduce the NU.
Midcourse Space Experiment Data Certification and Technology Transfer
NASA Technical Reports Server (NTRS)
Pollock, David B.
1997-01-01
The University of Alabama in Huntsville contributes to the Technical Management of the Midcourse Space Experiment Program, to the Certification of the Level 2 data produced by the Midcourse Space Experiment's suite of in-orbit imaging radiometers, imaging spectra-radiometers and an interferometer and to the Transfer of the Midcourse Space Experiment Technology to other Government Programs. The Technical Management of the Midcourse Space Experiment Program is expected to continue through out the spacecraft's useful life time, 5 years after its 1996 launch. The Transfer of Midcourse Space Experiment Technology to other government elements is expected to be on a demand basis by the United States Government and other organizations. The University of Alabama Huntsville' contribution specifically supports the nine Ultraviolet Visible Imagers and Spectrographic Imagers (UVISI) and the Pointing and Alignment of all eleven of the science instruments. The science instruments effectively cover the 0.1 to 28 micron spectral region. The Midcourse Space Experiment spacecraft, launched April 24, 1996, is expected to have a 5 year useful lifetime with a 12 month lifetime for the cryogenically cooled IR sensor. A pre-launch, ground based calibration of the instruments provided a basis for the pre-launch certification of the Level 2 data base these instruments produce. With the spacecraft in-orbit the certification of the instruments' Level 2 data base is being extended to the in-orbit environment.
GIFTS EDU Ground-based Measurement Experiment
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Smith, W. L., Sr.; Zollinger, L. J.; Huppi, R. J.; Reisse, R. A.; Larar, A. M.; Liu, X.; Tansock, J. J., Jr.; Jensen, S. M.; Revercomb, H. E.;
2007-01-01
Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. The EDU groundbased measurement experiment was held in Logan, Utah during September 2006 to demonstrate its extensive capabilities for geosynchronous and other applications.
NASA Astrophysics Data System (ADS)
Wang, Zhongpeng; Chen, Fangni; Qiu, Weiwei; Chen, Shoufa; Ren, Dongxiao
2018-03-01
In this paper, a two-layer image encryption scheme for a discrete cosine transform (DCT) precoded orthogonal frequency division multiplexing (OFDM) visible light communication (VLC) system is proposed. Firstly, in the proposed scheme the transmitted image is first encrypted by a chaos scrambling sequence,which is generated from the hybrid 4-D hyper- and Arnold map in the upper-layer. After that, the encrypted image is converted into digital QAM modulation signal, which is re-encrypted by chaos scrambling sequence based on Arnold map in physical layer to further enhance the security of the transmitted image. Moreover, DCT precoding is employed to improve BER performance of the proposed system and reduce the PAPR of OFDM signal. The BER and PAPR performances of the proposed system are evaluated by simulation experiments. The experiment results show that the proposed two-layer chaos scrambling schemes achieve image secure transmission for image-based OFDM VLC. Furthermore, DCT precoding can reduce the PAPR and improve the BER performance of OFDM-based VLC.
Decision-Based Design of a Low Vision Aid
1999-12-05
No loss ML 32 Aniridia Cloudy No Loss TT 35 Glaucoma Cloudy No Loss MM 23 Stargardt Disease Clear Loss AP 40 Congenital Retinal Malformations...brief clinical background evaluation, and a post-experiment questionnaire. The study was further expanded in scope to gather data for the VRD...Introduction and clinical evaluation 3) Experiments with red, blue and green images 4) Experiments with white images 5) Post experiment
[A web-based biomedical image mosaicing system].
Zhang, Meng; Yan, Zhuang-zhi; Pan, Zhi-jun; Shao, Shi-jie
2006-11-01
This paper describes a web service for biomedical image mosaicing. A web site based on CGI (Common Gateway Interface) is implemented. The system is based on Browser/Server model and is tested in www. Finally implementation examples and experiment results are provided.
Rapid analysis and exploration of fluorescence microscopy images.
Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J
2014-03-19
Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.
Visual Based Retrieval Systems and Web Mining--Introduction.
ERIC Educational Resources Information Center
Iyengar, S. S.
2001-01-01
Briefly discusses Web mining and image retrieval techniques, and then presents a summary of articles in this special issue. Articles focus on Web content mining, artificial neural networks as tools for image retrieval, content-based image retrieval systems, and personalizing the Web browsing experience using media agents. (AEF)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, T; Torres, M; Rossi, P
Purpose: Radiation-induced fibrosis is a common long-term complication affecting many patients following cancer radiotherapy. Standard clinical assessment of subcutaneous fibrosis is subjective and often limited to visual inspection and palpation. Ultrasound strain imaging describes the compressibility (elasticity) of biological tissues. This study’s purpose is to develop a quantitative ultrasound strain imaging that can consistently and accurately characterize radiation-induce fibrosis. Methods: In this study, we propose a 2D strain imaging method based on deformable image registration. A combined affine and B-spline transformation model is used to calculate the displacement of tissue between pre-stress and post-stress B-mode image sequences. The 2D displacementmore » is estimated through a hybrid image similarity measure metric, which is a combination of the normalized mutual information (NMI) and normalized sum-of-squared-differences (NSSD). And 2D strain is obtained from the gradient of the local displacement. We conducted phantom experiments under various compressions and compared the performance of our proposed method with the standard cross-correlation (CC)- based method using the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. In addition, we conducted ex-vivo beef muscle experiment to further validate the proposed method. Results: For phantom study, the SNR and CNS values of the proposed method were significantly higher than those calculated from the CC-based method under different strains. The SNR and CNR increased by a factor of 1.9 and 2.7 comparing to the CC-based method. For the ex-vivo experiment, the CC-based method failed to work due to large deformation (6.7%), while our proposed method could accurately detect the stiffness change. Conclusion: We have developed a 2D strain imaging technique based on the deformable image registration, validated its accuracy and feasibility with phantom and ex-vivo data. This 2D ultrasound strain imaging technology may be valuable as physicians try to eliminate radiation-induce fibrosis and improve the therapeutic ratio of cancer radiotherapy. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.« less
Adapting Local Features for Face Detection in Thermal Image.
Ma, Chao; Trung, Ngo Thanh; Uchiyama, Hideaki; Nagahara, Hajime; Shimada, Atsushi; Taniguchi, Rin-Ichiro
2017-11-27
A thermal camera captures the temperature distribution of a scene as a thermal image. In thermal images, facial appearances of different people under different lighting conditions are similar. This is because facial temperature distribution is generally constant and not affected by lighting condition. This similarity in face appearances is advantageous for face detection. To detect faces in thermal images, cascade classifiers with Haar-like features are generally used. However, there are few studies exploring the local features for face detection in thermal images. In this paper, we introduce two approaches relying on local features for face detection in thermal images. First, we create new feature types by extending Multi-Block LBP. We consider a margin around the reference and the generally constant distribution of facial temperature. In this way, we make the features more robust to image noise and more effective for face detection in thermal images. Second, we propose an AdaBoost-based training method to get cascade classifiers with multiple types of local features. These feature types have different advantages. In this way we enhance the description power of local features. We did a hold-out validation experiment and a field experiment. In the hold-out validation experiment, we captured a dataset from 20 participants, comprising 14 males and 6 females. For each participant, we captured 420 images with 10 variations in camera distance, 21 poses, and 2 appearances (participant with/without glasses). We compared the performance of cascade classifiers trained by different sets of the features. The experiment results showed that the proposed approaches effectively improve the performance of face detection in thermal images. In the field experiment, we compared the face detection performance in realistic scenes using thermal and RGB images, and gave discussion based on the results.
Design and realization of retina-like three-dimensional imaging based on a MOEMS mirror
NASA Astrophysics Data System (ADS)
Cao, Jie; Hao, Qun; Xia, Wenze; Peng, Yuxin; Cheng, Yang; Mu, Jiaxing; Wang, Peng
2016-07-01
To balance conflicts for high-resolution, large-field-of-view and real-time imaging, a retina-like imaging method based on time-of flight (TOF) is proposed. Mathematical models of 3D imaging based on MOEMS are developed. Based on this method, we perform simulations of retina-like scanning properties, including compression of redundant information and rotation and scaling invariance. To validate the theory, we develop a prototype and conduct relevant experiments. The preliminary results agree well with the simulations.
Recognition of blurred images by the method of moments.
Flusser, J; Suk, T; Saic, S
1996-01-01
The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.
The Mast Cameras and Mars Descent Imager (MARDI) for the 2009 Mars Science Laboratory
NASA Technical Reports Server (NTRS)
Malin, M. C.; Bell, J. F.; Cameron, J.; Dietrich, W. E.; Edgett, K. S.; Hallet, B.; Herkenhoff, K. E.; Lemmon, M. T.; Parker, T. J.; Sullivan, R. J.
2005-01-01
Based on operational experience gained during the Mars Exploration Rover (MER) mission, we proposed and were selected to conduct two related imaging experiments: (1) an investigation of the geology and short-term atmospheric vertical wind profile local to the Mars Science Laboratory (MSL) landing site using descent imaging, and (2) a broadly-based scientific investigation of the MSL locale employing visible and very near infra-red imaging techniques from a pair of mast-mounted, high resolution cameras. Both instruments share a common electronics design, a design also employed for the MSL Mars Hand Lens Imager (MAHLI) [1]. The primary differences between the cameras are in the nature and number of mechanisms and specific optics tailored to each camera s requirements.
Combining textual and visual information for image retrieval in the medical domain.
Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore
2011-01-01
In this article we have assembled the experience obtained from our participation in the imageCLEF evaluation task over the past two years. Exploitation on the use of linear combinations for image retrieval has been attempted by combining visual and textual sources of images. From our experiments we conclude that a mixed retrieval technique that applies both textual and visual retrieval in an interchangeably repeated manner improves the performance while overcoming the scalability limitations of visual retrieval. In particular, the mean average precision (MAP) has increased from 0.01 to 0.15 and 0.087 for 2009 and 2010 data, respectively, when content-based image retrieval (CBIR) is performed on the top 1000 results from textual retrieval based on natural language processing (NLP).
Intrinsic Motivations Drive Learning of Eye Movements: An Experiment with Human Adults
Caligiore, Daniele; Mustile, Magda; Cipriani, Daniele; Redgrave, Peter; Triesch, Jochen; De Marsico, Maria; Baldassarre, Gianluca
2015-01-01
Intrinsic motivations drive the acquisition of knowledge and skills on the basis of novel or surprising stimuli or the pleasure to learn new skills. In so doing, they are different from extrinsic motivations that are mainly linked to drives that promote survival and reproduction. Intrinsic motivations have been implicitly exploited in several psychological experiments but, due to the lack of proper paradigms, they are rarely a direct subject of investigation. This article investigates how different intrinsic motivation mechanisms can support the learning of visual skills, such as “foveate a particular object in space”, using a gaze contingency paradigm. In the experiment participants could freely foveate objects shown in a computer screen. Foveating each of two “button” pictures caused different effects: one caused the appearance of a simple image (blue rectangle) in unexpected positions, while the other evoked the appearance of an always-novel picture (objects or animals). The experiment studied how two possible intrinsic motivation mechanisms might guide learning to foveate one or the other button picture. One mechanism is based on the sudden, surprising appearance of a familiar image at unpredicted locations, and a second one is based on the content novelty of the images. The results show the comparative effectiveness of the mechanism based on image novelty, whereas they do not support the operation of the mechanism based on the surprising location of the image appearance. Interestingly, these results were also obtained with participants that, according to a post experiment questionnaire, had not understood the functions of the different buttons suggesting that novelty-based intrinsic motivation mechanisms might operate even at an unconscious level. PMID:25775248
Performance evaluation of infrared imaging system in field test
NASA Astrophysics Data System (ADS)
Wang, Chensheng; Guo, Xiaodong; Ren, Tingting; Zhang, Zhi-jie
2014-11-01
Infrared imaging system has been applied widely in both military and civilian fields. Since the infrared imager has various types and different parameters, for system manufacturers and customers, there is great demand for evaluating the performance of IR imaging systems with a standard tool or platform. Since the first generation IR imager was developed, the standard method to assess the performance has been the MRTD or related improved methods which are not perfect adaptable for current linear scanning imager or 2D staring imager based on FPA detector. For this problem, this paper describes an evaluation method based on the triangular orientation discrimination metric which is considered as the effective and emerging method to evaluate the synthesis performance of EO system. To realize the evaluation in field test, an experiment instrument is developed. And considering the importance of operational environment, the field test is carried in practical atmospheric environment. The test imagers include panoramic imaging system and staring imaging systems with different optics and detectors parameters (both cooled and uncooled). After showing the instrument and experiment setup, the experiment results are shown. The target range performance is analyzed and discussed. In data analysis part, the article gives the range prediction values obtained from TOD method, MRTD method and practical experiment, and shows the analysis and results discussion. The experimental results prove the effectiveness of this evaluation tool, and it can be taken as a platform to give the uniform performance prediction reference.
Validating a Geographical Image Retrieval System.
ERIC Educational Resources Information Center
Zhu, Bin; Chen, Hsinchun
2000-01-01
Summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. Describes an experiment to validate the performance of this image retrieval system against that of human subjects by examining similarity analysis…
Shi, Weisong; Gao, Wanrong; Chen, Chaoliang; Yang, Victor X D
2017-12-01
In this paper, a differential standard deviation of log-scale intensity (DSDLI) based optical coherence tomography angiography (OCTA) is presented for calculating microvascular images of human skin. The DSDLI algorithm calculates the variance in difference images of two consecutive log-scale intensity based structural images from the same position along depth direction to contrast blood flow. The en face microvascular images were then generated by calculating the standard deviation of the differential log-scale intensities within the specific depth range, resulting in an improvement in spatial resolution and SNR in microvascular images compared to speckle variance OCT and power intensity differential method. The performance of DSDLI was testified by both phantom and in vivo experiments. In in vivo experiments, a self-adaptive sub-pixel image registration algorithm was performed to remove the bulk motion noise, where 2D Fourier transform was utilized to generate new images with spatial interval equal to half of the distance between two pixels in both fast-scanning and depth directions. The SNRs of signals of flowing particles are improved by 7.3 dB and 6.8 dB on average in phantom and in vivo experiments, respectively, while the average spatial resolution of images of in vivo blood vessels is increased by 21%. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Image cloning beyond diffraction based on coherent population trapping in a hot rubidium vapor.
Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen
2014-01-15
Following recent theoretical predictions, we report on an experimental realization of image cloning beyond usual diffraction, through the coherent population trapping (CPT) effect in a hot rubidium vapor. In our experiment, an alphabet letter image was transferred from a coupling field to a probe field, based on the CPT effect. Furthermore, we demonstrate that the cloned probe field carrying the image is transmitted without the usual diffraction. To our best knowledge, this is the first experimental report about image cloning beyond diffraction. We believe this mechanism, based on CPT, has definite and important applications in image metrology, image processing, and biomedical imaging.
Two Pathways to Stimulus Encoding in Category Learning?
Davis, Tyler; Love, Bradley C.; Maddox, W. Todd
2008-01-01
Category learning theorists tacitly assume that stimuli are encoded by a single pathway. Motivated by theories of object recognition, we evaluate a dual-pathway account of stimulus encoding. The part-based pathway establishes mappings between sensory input and symbols that encode discrete stimulus features, whereas the image-based pathway applies holistic templates to sensory input. Our experiments use rule-plus-exception structures in which one exception item in each category violates a salient regularity and must be distinguished from other items. In Experiment 1, we find that discrete representations are crucial for recognition of exceptions following brief training. Experiments 2 and 3 involve multi-session training regimens designed to encourage either part or image-based encoding. We find that both pathways are able to support exception encoding, but have unique characteristics. We speculate that one advantage of the part-based pathway is the ability to generalize across domains, whereas the image-based pathway provides faster and more effortless recognition. PMID:19460948
Gender differences in the content of cognitive distraction during sex.
Meana, Marta; Nunnink, Sarah E
2006-02-01
This study compared 220 college men and 237 college women on two types of self-reported cognitive distraction during sex, performance- and appearance-based. Affect, psychological distress, sexual knowledge, attitudes, fantasies, experiences, body image, satisfaction, and sexual function were assessed with the Derogatis Sexual Functioning Inventory and the Sexual History Form to determine associations with distraction. Between-gender analyses revealed that women reported higher levels of overall and appearance-based distraction than did men, but similar levels of performance-based distraction. Within-gender analyses revealed that women reported as much of one type of distraction as the other, while men reported more performance- than appearance-based distraction. In women, appearance-based distraction was predicted by negative body image, psychological distress, and not being in a relationship, while performance-based distraction was predicted by negative body image, psychological distress, and sexual dissatisfaction. In men, appearance-based distraction was predicted by negative body image, sexual dissatisfaction and not being in a relationship, while performance-based distraction was predicted by negative body image and sexual dissatisfaction. Investigating the content of cognitive distraction may be useful in understanding gender differences in sexual experience and in refining cognitive components of sex therapy.
Friedman, Kelli E; Reichmann, Simona K; Costanzo, Philip R; Zelli, Arnaldo; Ashmore, Jamile A; Musante, Gerard J
2005-05-01
This study evaluated the relation among weight-based stigmatization, ideological beliefs about weight, and psychological functioning in an obese, treatment-seeking sample. Ninety-three obese, treatment-seeking adults (24 men and 69 women) completed a battery of self-report questionnaires measuring psychological adjustment, attitudes about weight, belief in the controllability of weight, and the frequency of weight-based stigmatization. Weight-based stigmatization was a common experience for participants. Frequency of stigmatizing experiences was positively associated with depression, general psychiatric symptoms, and body image disturbance, and negatively associated with self-esteem. Further, participants' own negative attitudes about weight problems were associated with their psychological distress and moderated the relation between the experience of stigmatization and body image. Weight-based stigmatization is a common experience for obese individuals seeking weight loss treatment and appears to contribute to poor mental health adjustment. The negative effects of these experiences are particularly damaging for those who hold strong antifat beliefs.
Impact of Internet Images: Impression-Formation Effects of University Web Site Images
ERIC Educational Resources Information Center
Ramasubramanian, Srividya; Gyure, James F.; Mursi, Nasreen M.
2002-01-01
Institutions of higher education are increasingly becoming dependent on Web-based marketing to reach out to their target audiences. The current empirical study examines the types of impressions formed by prospective students based on exposure to different university Web site images. A between-subjects experiment was conducted using four identical…
Li, Changqing; Zhao, Hongzhi; Anderson, Bonnie; Jiang, Huabei
2006-03-01
We describe a compact diffuse optical tomography system specifically designed for breast imaging. The system consists of 64 silicon photodiode detectors, 64 excitation points, and 10 diode lasers in the near-infrared region, allowing multispectral, three-dimensional optical imaging of breast tissue. We also detail the system performance and optimization through a calibration procedure. The system is evaluated using tissue-like phantom experiments and an in vivo clinic experiment. Quantitative two-dimensional (2D) and three-dimensional (3D) images of absorption and reduced scattering coefficients are obtained from these experiments. The ten-wavelength spectra of the extracted reduced scattering coefficient enable quantitative morphological images to be reconstructed with this system. From the in vivo clinic experiment, functional images including deoxyhemoglobin, oxyhemoglobin, and water concentration are recovered and tumors are detected with correct size and position compared with the mammography.
Image Recommendation Algorithm Using Feature-Based Collaborative Filtering
NASA Astrophysics Data System (ADS)
Kim, Deok-Hwan
As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.
Structure and Soot Properties of Nonbuoyant Ethylene/Air Laminar Jet Diffusion Flames. Appendix I
NASA Technical Reports Server (NTRS)
Urban, D. L.; Yuan, Z.-G.; Sunderland, P. B.; Linteris, G. T.; Voss, J. E.; Lin, K.-C.; Dai, Z.; Sun, K.; Faeth, G. M.; Ross, Howard D. (Technical Monitor)
2000-01-01
The structure and soot properties of round, soot-emitting, nonbuoyant, laminar jet diffusion flames are described, based on long-duration (175-230/s) experiments at microgravity carried out on orbit In the Space Shuttle Columbia. Experiments] conditions included ethylene-fueled flames burning in still air at nominal pressures of 50 and 100 kPa and an ambient temperature of 300 K with luminous Annie lengths of 49-64 mm. Measurements included luminous flame shapes using color video imaging, soot concentration (volume fraction) distributions using deconvoluted laser extinction imaging, soot temperature distributions using deconvoluted multiline emission imaging, gas temperature distributions at fuel-lean (plume) conditions using thermocouple probes, not structure distributions using thermophoretic sampling and analysis by transmission electron microscopy, and flame radiation using a radiometer. The present flames were larger, and emitted soot men readily, than comparable observed during ground-based microgravity experiments due to closer approach to steady conditions resulting from the longer test times and the reduced gravitational disturbances of the space-based experiments.
Research and Analysis of Image Processing Technologies Based on DotNet Framework
NASA Astrophysics Data System (ADS)
Ya-Lin, Song; Chen-Xi, Bai
Microsoft.Net is a kind of most popular program development tool. This paper gave a detailed analysis concluded about some image processing technologies of the advantages and disadvantages by .Net processed image while the same algorithm is used in Programming experiments. The result shows that the two best efficient methods are unsafe pointer and Direct 3D, and Direct 3D used to 3D simulation development, and the others are useful in some fields while these technologies are poor efficiency and not suited to real-time processing. The experiment results in paper will help some projects about image processing and simulation based DotNet and it has strong practicability.
Midcourse Space Experiment Data Certification and Technology Transfer. Supplement 1
NASA Technical Reports Server (NTRS)
Pollock, David B.
1998-01-01
The University of Alabama in Huntsville contributes to the Technical Management of the Midcourse Space Experiment Program, to the Certification of the Level 2 data produced by the Midcourse Space Experiment's suite of in-orbit imaging radiometers, imaging spectro-radiometers and an interferometer and to the Transfer of the Midcourse Space Experiment Technology to other Government Programs. The Technical Management of the Midcourse Space Experiment Program is expected to continue through out the spacecraft's useful life time. The Transfer of Midcourse Space Experiment Technology to other government elements is expected to be on a demand basis by the United States Government and other organizations. The University, of Alabama Huntsville' contribution specifically supports the Principal Investigator's Executive Committee, the Deputy Principal Investigator for Data Certification and Technology Transfer team, the nine Ultraviolet Visible Imagers and Spectrographic Imagers (UVISI) and the Pointing and Alignment of all eleven of the science instruments. The science instruments effectively cover the 0.1 to 28 micron spectral region. The Midcourse Space Experiment spacecraft, launched April 24, 1996, is expected to have a 5 year useful lifetime. The cryogenically cooled IR sensor, SPIRIT III, performed through February, 1997 when its cryogen expired. A pre-launch, ground based calibration of the instruments provided a basis for the pre-launch certification of the Level 2 data base these instruments produce. With the spacecraft in-orbit the certification of the instrument's Level 2 data base was extended to the in-orbit environment.
Remote Sensing Image Quality Assessment Experiment with Post-Processing
NASA Astrophysics Data System (ADS)
Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.
2018-04-01
This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.
NASA Astrophysics Data System (ADS)
Wihardi, Y.; Setiawan, W.; Nugraha, E.
2018-01-01
On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.
Adaptive noise Wiener filter for scanning electron microscope imaging system.
Sim, K S; Teh, V; Nia, M E
2016-01-01
Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. © Wiley Periodicals, Inc.
Monotonicity-based electrical impedance tomography for lung imaging
NASA Astrophysics Data System (ADS)
Zhou, Liangdong; Harrach, Bastian; Seo, Jin Keun
2018-04-01
This paper presents a monotonicity-based spatiotemporal conductivity imaging method for continuous regional lung monitoring using electrical impedance tomography (EIT). The EIT data (i.e. the boundary current-voltage data) can be decomposed into pulmonary, cardiac and other parts using their different periodic natures. The time-differential current-voltage operator corresponding to the lung ventilation can be viewed as either semi-positive or semi-negative definite owing to monotonic conductivity changes within the lung regions. We used these monotonicity constraints to improve the quality of lung EIT imaging. We tested the proposed methods in numerical simulations, phantom experiments and human experiments.
NASA Technical Reports Server (NTRS)
1975-01-01
Image data processing system (IDAPS) developed to satisfy the image processing requirements of the Skylab S-056 experiment is described. The S-056 experiment was designed to obtain high-resolution photographs of the sun in the far ultraviolet, or soft X-ray, portion of the electromagnetic spectrum. Thirty-five thousand photographs were obtained by the three flights of the program; and, faced with such a massive volume of imagery, the designers of the experiment decided to develop a computer-based system which would reduce the image processing workload. The purpose of the IDAPS User Manual is to give the IDAPS user the necessary information and instructions to effectively utilize the system.
NASA Astrophysics Data System (ADS)
Garcia-Yeguas, A.; Ibañez, J. M.; Rietbrock, A.; Tom-Teidevs, G.
2008-12-01
An active seismic experiment to study the internal structure of Teide Volcano was carried out on Tenerife, a volcanic island in Spain's Canary Islands. The main objective of the TOM-TEIDEVS experiment is to obtain a 3-dimensional structural image of Teide Volcano using seismic tomography and seismic reflection/refraction imaging techniques. At present, knowledge of the deeper structure of Teide and Tenerife is very limited, with proposed structural models mainly based on sparse geophysical and geological data. This multinational experiment which involves institutes from Spain, Italy, the United Kingdom, Ireland, and Mexico will generate a unique high resolution structural image of the active volcano edifice and will further our understanding of volcanic processes.
Hattab, Georges; Schlüter, Jan-Philip; Becker, Anke; Nattkemper, Tim W.
2017-01-01
In order to understand gene function in bacterial life cycles, time lapse bioimaging is applied in combination with different marker protocols in so called microfluidics chambers (i.e., a multi-well plate). In one experiment, a series of T images is recorded for one visual field, with a pixel resolution of 60 nm/px. Any (semi-)automatic analysis of the data is hampered by a strong image noise, low contrast and, last but not least, considerable irregular shifts during the acquisition. Image registration corrects such shifts enabling next steps of the analysis (e.g., feature extraction or tracking). Image alignment faces two obstacles in this microscopic context: (a) highly dynamic structural changes in the sample (i.e., colony growth) and (b) an individual data set-specific sample environment which makes the application of landmarks-based alignments almost impossible. We present a computational image registration solution, we refer to as ViCAR: (Vi)sual (C)ues based (A)daptive (R)egistration, for such microfluidics experiments, consisting of (1) the detection of particular polygons (outlined and segmented ones, referred to as visual cues), (2) the adaptive retrieval of three coordinates throughout different sets of frames, and finally (3) an image registration based on the relation of these points correcting both rotation and translation. We tested ViCAR with different data sets and have found that it provides an effective spatial alignment thereby paving the way to extract temporal features pertinent to each resulting bacterial colony. By using ViCAR, we achieved an image registration with 99.9% of image closeness, based on the average rmsd of 4.10−2 pixels, and superior results compared to a state of the art algorithm. PMID:28620411
Hepatic CT image query using Gabor features
NASA Astrophysics Data System (ADS)
Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange
2004-07-01
A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.
Design Analysis of a Space Based Chromotomographic Hyperspectral Imaging Experiment
2010-03-01
Tilt Platforms S-340 Platform Recommended Models Mirror Aluminum Aluminum S-340.Ax Invar Zerodur glass S-340.ix Titanium BK7 glass S-340.Tx Steel S-340...composed of a telescope, two grating spectrometers, calibration lamps, and focal plane electronics and cooling system. The telescope is a three mirror ...advanced hyperspectral imager for coastal bathymetry is that the experiment will closely mirror that of the proposed space-based chromotomographic hy
Object-based connectedness facilitates matching.
Koning, Arno; van Lier, Rob
2003-10-01
In two matching tasks, participants had to match two images of object pairs. Image-based (IB) connectedness refers to connectedness between the objects in an image. Object-based (OB) connectedness refers to connectedness between the interpreted objects. In Experiment 1, a monocular depth cue (shadow) was used to distinguish different relation types between object pairs. Three relation types were created: IB/OB-connected objects, IB/OB-disconnected objects, and IB-connected/OB-disconnected objects. It was found that IB/OB-connected objects were matched faster than IB/OB-disconnected objects. Objects that were IB-connected/OB-disconnected were matched equally to IB/OB-disconnected objects. In Experiment 2, stereoscopic presentation was used. With relation types comparable to those in Experiment 1, it was again found that OB connectedness determined speed of matching, rather than IB connectedness. We conclude that matching of projections of three-dimensional objects depends more on OB connectedness than on IB connectedness.
Jamaludin, Juliza; Rahim, Ruzairi Abdul; Fazul Rahiman, Mohd Hafiz; Mohd Rohani, Jemmy
2018-04-01
Optical tomography (OPT) is a method to capture a cross-sectional image based on the data obtained by sensors, distributed around the periphery of the analyzed system. This system is based on the measurement of the final light attenuation or absorption of radiation after crossing the measured objects. The number of sensor views will affect the results of image reconstruction, where the high number of sensor views per projection will give a high image quality. This research presents an application of charge-coupled device linear sensor and laser diode in an OPT system. Experiments in detecting solid and transparent objects in crystal clear water were conducted. Two numbers of sensors views, 160 and 320 views are evaluated in this research in reconstructing the images. The image reconstruction algorithms used were filtered images of linear back projection algorithms. Analysis on comparing the simulation and experiments image results shows that, with 320 image views giving less area error than 160 views. This suggests that high image view resulted in the high resolution of image reconstruction.
Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.
Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J
2018-05-01
We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.
Enriching text with images and colored light
NASA Astrophysics Data System (ADS)
Sekulovski, Dragan; Geleijnse, Gijs; Kater, Bram; Korst, Jan; Pauws, Steffen; Clout, Ramon
2008-01-01
We present an unsupervised method to enrich textual applications with relevant images and colors. The images are collected by querying large image repositories and subsequently the colors are computed using image processing. A prototype system based on this method is presented where the method is applied to song lyrics. In combination with a lyrics synchronization algorithm the system produces a rich multimedia experience. In order to identify terms within the text that may be associated with images and colors, we select noun phrases using a part of speech tagger. Large image repositories are queried with these terms. Per term representative colors are extracted using the collected images. Hereto, we either use a histogram-based or a mean shift-based algorithm. The representative color extraction uses the non-uniform distribution of the colors found in the large repositories. The images that are ranked best by the search engine are displayed on a screen, while the extracted representative colors are rendered on controllable lighting devices in the living room. We evaluate our method by comparing the computed colors to standard color representations of a set of English color terms. A second evaluation focuses on the distance in color between a queried term in English and its translation in a foreign language. Based on results from three sets of terms, a measure of suitability of a term for color extraction based on KL Divergence is proposed. Finally, we compare the performance of the algorithm using either the automatically indexed repository of Google Images and the manually annotated Flickr.com. Based on the results of these experiments, we conclude that using the presented method we can compute the relevant color for a term using a large image repository and image processing.
Image Quality Assessment Based on Local Linear Information and Distortion-Specific Compensation.
Wang, Hanli; Fu, Jie; Lin, Weisi; Hu, Sudeng; Kuo, C-C Jay; Zuo, Lingxuan
2016-12-14
Image Quality Assessment (IQA) is a fundamental yet constantly developing task for computer vision and image processing. Most IQA evaluation mechanisms are based on the pertinence of subjective and objective estimation. Each image distortion type has its own property correlated with human perception. However, this intrinsic property may not be fully exploited by existing IQA methods. In this paper, we make two main contributions to the IQA field. First, a novel IQA method is developed based on a local linear model that examines the distortion between the reference and the distorted images for better alignment with human visual experience. Second, a distortion-specific compensation strategy is proposed to offset the negative effect on IQA modeling caused by different image distortion types. These score offsets are learned from several known distortion types. Furthermore, for an image with an unknown distortion type, a Convolutional Neural Network (CNN) based method is proposed to compute the score offset automatically. Finally, an integrated IQA metric is proposed by combining the aforementioned two ideas. Extensive experiments are performed to verify the proposed IQA metric, which demonstrate that the local linear model is useful in human perception modeling, especially for individual image distortion, and the overall IQA method outperforms several state-of-the-art IQA approaches.
Verification technology of remote sensing camera satellite imaging simulation based on ray tracing
NASA Astrophysics Data System (ADS)
Gu, Qiongqiong; Chen, Xiaomei; Yang, Deyun
2017-08-01
Remote sensing satellite camera imaging simulation technology is broadly used to evaluate the satellite imaging quality and to test the data application system. But the simulation precision is hard to examine. In this paper, we propose an experimental simulation verification method, which is based on the test parameter variation comparison. According to the simulation model based on ray-tracing, the experiment is to verify the model precision by changing the types of devices, which are corresponding the parameters of the model. The experimental results show that the similarity between the imaging model based on ray tracing and the experimental image is 91.4%, which can simulate the remote sensing satellite imaging system very well.
Stanciu, Stefan G; Xu, Shuoyu; Peng, Qiwen; Yan, Jie; Stanciu, George A; Welsch, Roy E; So, Peter T C; Csucs, Gabor; Yu, Hanry
2014-04-10
The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.
Stanciu, Stefan G.; Xu, Shuoyu; Peng, Qiwen; Yan, Jie; Stanciu, George A.; Welsch, Roy E.; So, Peter T. C.; Csucs, Gabor; Yu, Hanry
2014-01-01
The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework. PMID:24717650
NASA Astrophysics Data System (ADS)
Stanciu, Stefan G.; Xu, Shuoyu; Peng, Qiwen; Yan, Jie; Stanciu, George A.; Welsch, Roy E.; So, Peter T. C.; Csucs, Gabor; Yu, Hanry
2014-04-01
The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.
An atlas-based multimodal registration method for 2D images with discrepancy structures.
Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng
2018-06-04
An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.
NASA Astrophysics Data System (ADS)
Okawa, Shinpei; Hirasawa, Takeshi; Kushibiki, Toshihiro; Ishihara, Miya
2015-03-01
Quantification of the optical properties of the tissues and blood by noninvasive photoacoustic (PA) imaging may provide useful information for screening and early diagnosis of diseases. Linearized 2D image reconstruction algorithm based on PA wave equation and the photon diffusion equation (PDE) can reconstruct the image with computational cost smaller than a method based on 3D radiative transfer equation. However, the reconstructed image is affected by the differences between the actual and assumed light propagations. A quantitative capability of a linearized 2D image reconstruction was investigated and discussed by the numerical simulations and the phantom experiment in this study. The numerical simulations with the 3D Monte Carlo (MC) simulation and the 2D finite element calculation of the PDE were carried out. The phantom experiment was also conducted. In the phantom experiment, the PA pressures were acquired by a probe which had an optical fiber for illumination and the ring shaped P(VDF-TrFE) ultrasound transducer. The measured object was made of Intralipid and Indocyanine green. In the numerical simulations, it was shown that the linearized image reconstruction method recovered the absorption coefficients with alleviating the dependency of the PA amplitude on the depth of the photon absorber. The linearized image reconstruction method worked effectively under the light propagation calculated by 3D MC simulation, although some errors occurred. The phantom experiments validated the result of the numerical simulations.
Usage of CT data in biomechanical research
NASA Astrophysics Data System (ADS)
Safonov, Roman A.; Golyadkina, Anastasiya A.; Kirillova, Irina V.; Kossovich, Leonid Y.
2017-02-01
Object of study: The investigation is focused on development of personalized medicine. The determination of mechanical properties of bone tissues based on in vivo data was considered. Methods: CT, MRI, natural experiments on versatile test machine Instron 5944, numerical experiments using Python programs. Results: The medical diagnostics methods, which allows determination of mechanical properties of bone tissues based on in vivo data. The series of experiments to define the values of mechanical parameters of bone tissues. For one and the same sample, computed tomography (CT), magnetic resonance imaging (MRI), ultrasonic investigations and mechanical experiments on single-column test machine Instron 5944 were carried out. The computer program for comparison of CT and MRI images was created. The grayscale values in the same points of the samples were determined on both CT and MRI images. The Haunsfield grayscale values were used to determine rigidity (Young module) and tensile strength of the samples. The obtained data was compared to natural experiments results for verification.
Psychophysical studies of the performance of an image database retrieval system
NASA Astrophysics Data System (ADS)
Papathomas, Thomas V.; Conway, Tiffany E.; Cox, Ingemar J.; Ghosn, Joumana; Miller, Matt L.; Minka, Thomas P.; Yianilos, Peter N.
1998-07-01
We describe psychophysical experiments conducted to study PicHunter, a content-based image retrieval (CBIR) system. Experiment 1 studies the importance of using (a) semantic information, (2) memory of earlier input and (3) relative, rather than absolute, judgements of image similarity. The target testing paradigm is used in which a user must search for an image identical to a target. We find that the best performance comes from a version of PicHunter that uses only semantic cues, with memory and relative similarity judgements. Second best is use of both pictorial and semantic cues, with memory and relative similarity judgements. Most reports of CBIR systems provide only qualitative measures of performance based on how similar retrieved images are to a target. Experiment 2 puts PicHunter into this context with a more rigorous test. We first establish a baseline for our database by measuring the time required to find an image that is similar to a target when the images are presented in random order. Although PicHunter's performance is measurably better than this, the test is weak because even random presentation of images yields reasonably short search times. This casts doubt on the strength of results given in other reports where no baseline is established.
Simulations of multi-contrast x-ray imaging using near-field speckles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zdora, Marie-Christine; Diamond Light Source, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, United Kingdom and Department of Physics & Astronomy, University College London, London, WC1E 6BT; Thibault, Pierre
2016-01-28
X-ray dark-field and phase-contrast imaging using near-field speckles is a novel technique that overcomes limitations inherent in conventional absorption x-ray imaging, i.e. poor contrast for features with similar density. Speckle-based imaging yields a wealth of information with a simple setup tolerant to polychromatic and divergent beams, and simple data acquisition and analysis procedures. Here, we present a simulation software used to model the image formation with the speckle-based technique, and we compare simulated results on a phantom sample with experimental synchrotron data. Thorough simulation of a speckle-based imaging experiment will help for better understanding and optimising the technique itself.
Research based on the SoPC platform of feature-based image registration
NASA Astrophysics Data System (ADS)
Shi, Yue-dong; Wang, Zhi-hui
2015-12-01
This paper focuses on the study of implementing feature-based image registration by System on a Programmable Chip (SoPC) hardware platform. We solidify the image registration algorithm on the FPGA chip, in which embedded soft core processor Nios II can speed up the image processing system. In this way, we can make image registration technology get rid of the PC. And, consequently, this kind of technology will be got an extensive use. The experiment result indicates that our system shows stable performance, particularly in terms of matching processing which noise immunity is good. And feature points of images show a reasonable distribution.
NASA Astrophysics Data System (ADS)
Liu, Jing; Chen, Wei; Wang, Zujun; Xue, Yuanyuan; Yao, Zhibin; He, Baoping; Ma, Wuying; Jin, Junshan; Sheng, Jiangkun; Dong, Guantao
2017-06-01
This paper presents an investigation of total ionizing dose (TID) induced image lag sources in pinned photodiodes (PPD) CMOS image sensors based on radiation experiments and TCAD simulation. The radiation experiments have been carried out at the Cobalt -60 gamma-ray source. The experimental results show the image lag degradation is more and more serious with increasing TID. Combining with the TCAD simulation results, we can confirm that the junction of PPD and transfer gate (TG) is an important region forming image lag during irradiation. These simulations demonstrate that TID can generate a potential pocket leading to incomplete transfer.
Remote sensing fusion based on guided image filtering
NASA Astrophysics Data System (ADS)
Zhao, Wenfei; Dai, Qinling; Wang, Leiguang
2015-12-01
In this paper, we propose a novel remote sensing fusion approach based on guided image filtering. The fused images can well preserve the spectral features of the original multispectral (MS) images, meanwhile, enhance the spatial details information. Four quality assessment indexes are also introduced to evaluate the fusion effect when compared with other fusion methods. Experiments carried out on Gaofen-2, QuickBird, WorldView-2 and Landsat-8 images. And the results show an excellent performance of the proposed method.
Assessing product image quality for online shopping
NASA Astrophysics Data System (ADS)
Goswami, Anjan; Chung, Sung H.; Chittar, Naren; Islam, Atiq
2012-01-01
Assessing product-image quality is important in the context of online shopping. A high quality image that conveys more information about a product can boost the buyer's confidence and can get more attention. However, the notion of image quality for product-images is not the same as that in other domains. The perception of quality of product-images depends not only on various photographic quality features but also on various high level features such as clarity of the foreground or goodness of the background etc. In this paper, we define a notion of product-image quality based on various such features. We conduct a crowd-sourced experiment to collect user judgments on thousands of eBay's images. We formulate a multi-class classification problem for modeling image quality by classifying images into good, fair and poor quality based on the guided perceptual notions from the judges. We also conduct experiments with regression using average crowd-sourced human judgments as target. We compute a pseudo-regression score with expected average of predicted classes and also compute a score from the regression technique. We design many experiments with various sampling and voting schemes with crowd-sourced data and construct various experimental image quality models. Most of our models have reasonable accuracies (greater or equal to 70%) on test data set. We observe that our computed image quality score has a high (0.66) rank correlation with average votes from the crowd sourced human judgments.
Predicting plant biomass accumulation from image-derived parameters
Chen, Dijun; Shi, Rongli; Pape, Jean-Michel; Neumann, Kerstin; Graner, Andreas; Chen, Ming; Klukas, Christian
2018-01-01
Abstract Background Image-based high-throughput phenotyping technologies have been rapidly developed in plant science recently, and they provide a great potential to gain more valuable information than traditionally destructive methods. Predicting plant biomass is regarded as a key purpose for plant breeders and ecologists. However, it is a great challenge to find a predictive biomass model across experiments. Results In the present study, we constructed 4 predictive models to examine the quantitative relationship between image-based features and plant biomass accumulation. Our methodology has been applied to 3 consecutive barley (Hordeum vulgare) experiments with control and stress treatments. The results proved that plant biomass can be accurately predicted from image-based parameters using a random forest model. The high prediction accuracy based on this model will contribute to relieving the phenotyping bottleneck in biomass measurement in breeding applications. The prediction performance is still relatively high across experiments under similar conditions. The relative contribution of individual features for predicting biomass was further quantified, revealing new insights into the phenotypic determinants of the plant biomass outcome. Furthermore, methods could also be used to determine the most important image-based features related to plant biomass accumulation, which would be promising for subsequent genetic mapping to uncover the genetic basis of biomass. Conclusions We have developed quantitative models to accurately predict plant biomass accumulation from image data. We anticipate that the analysis results will be useful to advance our views of the phenotypic determinants of plant biomass outcome, and the statistical methods can be broadly used for other plant species. PMID:29346559
Visual improvement for bad handwriting based on Monte-Carlo method
NASA Astrophysics Data System (ADS)
Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua
2014-03-01
A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.
Highlighting in Early Childhood: Learning Biases Through Attentional Shifting.
Burling, Joseph M; Yoshida, Hanako
2017-02-01
The literature on human and animal learning suggests that individuals attend to and act on cues differently based on the order in which they were learned. Recent studies have proposed that one specific type of learning outcome, the highlighting effect, can serve as a framework for understanding a number of early cognitive milestones. However, little is known how this learning effect itself emerges among children, whose memory and attention are much more limited compared to adults. Two experiments were conducted using different versions of the general highlighting paradigm: Experiment 1 tested 3 to 6 year olds with a newly developed image-based version of the paradigm, which was designed specifically to test young children. Experiment 2 tested the validity of an image-based implementation of the highlighting paradigm with adult participants. The results from Experiment 1 provide evidence for the highlighting effect among children 3-6 years old, and they suggest age-related differences in dividing attention among multiple cues during learning. Experiment 2 replicated results from previous studies by showing robust biases for both image-based and text-based versions of the highlighting task. This study suggests that sensitivity to learning order emerges early through the process of cued attention, and the role of the highlighting effect in early language learning is discussed. Copyright © 2016 Cognitive Science Society, Inc.
a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data
NASA Astrophysics Data System (ADS)
Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.
2017-09-01
The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial resolution images image by image. Simulated experiment and remote sensing image downscaling experiment were conducted. In simulated experiment, the 30 meters class map dataset Globeland30 was adopted to investigate the effect on avoid the underdetermined problem in downscaling procedure and a comparison between spiral and window was conducted. Further, the MODIS NDVI and Landsat image data was adopted to generate the 30m time series NDVI in remote sensing image downscaling experiment. Simulated experiment results showed that the proposed method had a robust performance in downscaling pixel in heterogeneous region and indicated that it was superior to the traditional window-based methods. The high resolution time series generated may be a benefit to the mapping and updating of land cover data.
3D super resolution range-gated imaging for canopy reconstruction and measurement
NASA Astrophysics Data System (ADS)
Huang, Hantao; Wang, Xinwei; Sun, Liang; Lei, Pingshun; Fan, Songtao; Zhou, Yan
2018-01-01
In this paper, we proposed a method of canopy reconstruction and measurement based on 3D super resolution range-gated imaging. In this method, high resolution 2D intensity images are grasped by active gate imaging, and 3D images of canopy are reconstructed by triangular-range-intensity correlation algorithm at the same time. A range-gated laser imaging system(RGLIS) is established based on 808 nm diode laser and gated intensified charge-coupled device (ICCD) camera with 1392´1040 pixels. The proof experiments have been performed for potted plants located 75m away and trees located 165m away. The experiments show it that can acquire more than 1 million points per frame, and 3D imaging has the spatial resolution about 0.3mm at the distance of 75m and the distance accuracy about 10 cm. This research is beneficial for high speed acquisition of canopy structure and non-destructive canopy measurement.
Solution of the problem of superposing image and digital map for detection of new objects
NASA Astrophysics Data System (ADS)
Rizaev, I. S.; Miftakhutdinov, D. I.; Takhavova, E. G.
2018-01-01
The problem of superposing the map of the terrain with the image of the terrain is considered. The image of the terrain may be represented in different frequency bands. Further analysis of the results of collation the digital map with the image of the appropriate terrain is described. Also the approach to detection of differences between information represented on the digital map and information of the image of the appropriate area is offered. The algorithm for calculating the values of brightness of the converted image area on the original picture is offered. The calculation is based on using information about the navigation parameters and information according to arranged bench marks. For solving the posed problem the experiments were performed. The results of the experiments are shown in this paper. The presented algorithms are applicable to the ground complex of remote sensing data to assess differences between resulting images and accurate geopositional data. They are also suitable for detecting new objects in the image, based on the analysis of the matching the digital map and the image of corresponding locality.
Image aesthetic quality evaluation using convolution neural network embedded learning
NASA Astrophysics Data System (ADS)
Li, Yu-xin; Pu, Yuan-yuan; Xu, Dan; Qian, Wen-hua; Wang, Li-peng
2017-11-01
A way of embedded learning convolution neural network (ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.
2011-05-01
for the research in the next year. The aims in the next year include further develop- ment of the prior image- based , narrowly collimated CBCT imaging...further investigation planned for the next year. 5 BODY 1 Research Accomplishments 1.1 Implement narrow beam collimation for CBCT ROI imaging I have...noise level to mimic different mAs used in clinical and research modes of the CBCT system. Based upon experiences with the numerical phantom, I designed
Sub-pattern based multi-manifold discriminant analysis for face recognition
NASA Astrophysics Data System (ADS)
Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen
2018-04-01
In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.
NASA Astrophysics Data System (ADS)
Xu, Jie; Wang, Xin; Zhan, Qi; Huang, Shengling; Chen, Yifan; Mu, Baozhong
2016-07-01
This paper presents a novel lobster-eye imaging system for X-ray-backscattering inspection. The system was designed by modifying the Schmidt geometry into a treble-lens structure in order to reduce the resolution difference between the vertical and horizontal directions, as indicated by ray-tracing simulations. The lobster-eye X-ray imaging system is capable of operating over a wide range of photon energies up to 100 keV. In addition, the optics of the lobster-eye X-ray imaging system was tested to verify that they meet the requirements. X-ray-backscattering imaging experiments were performed in which T-shaped polymethyl-methacrylate objects were imaged by the lobster-eye X-ray imaging system based on both the double-lens and treble-lens Schmidt objectives. The results show similar resolution of the treble-lens Schmidt objective in both the vertical and horizontal directions. Moreover, imaging experiments were performed using a second treble-lens Schmidt objective with higher resolution. The results show that for a field of view of over 200 mm and with a 500 mm object distance, this lobster-eye X-ray imaging system based on a treble-lens Schmidt objective offers a spatial resolution of approximately 3 mm.
Global image analysis to determine suitability for text-based image personalization
NASA Astrophysics Data System (ADS)
Ding, Hengzhou; Bala, Raja; Fan, Zhigang; Bouman, Charles A.; Allebach, Jan P.
2012-03-01
Lately, image personalization is becoming an interesting topic. Images with variable elements such as text usually appear much more appealing to the recipients. In this paper, we describe a method to pre-analyze the image and automatically suggest to the user the most suitable regions within an image for text-based personalization. The method is based on input gathered from experiments conducted with professional designers. It has been observed that regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are the best candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Furthermore, based on the smooth and text regions found in the image, we derive an overall metric to rate the image in terms of its suitability for personalization (SFP).
High dynamic range image acquisition based on multiplex cameras
NASA Astrophysics Data System (ADS)
Zeng, Hairui; Sun, Huayan; Zhang, Tinghua
2018-03-01
High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.
Infrared traffic image enhancement algorithm based on dark channel prior and gamma correction
NASA Astrophysics Data System (ADS)
Zheng, Lintao; Shi, Hengliang; Gu, Ming
2017-07-01
The infrared traffic image acquired by the intelligent traffic surveillance equipment has low contrast, little hierarchical differences in perceptions of image and the blurred vision effect. Therefore, infrared traffic image enhancement, being an indispensable key step, is applied to nearly all infrared imaging based traffic engineering applications. In this paper, we propose an infrared traffic image enhancement algorithm that is based on dark channel prior and gamma correction. In existing research dark channel prior, known as a famous image dehazing method, here is used to do infrared image enhancement for the first time. Initially, in the proposed algorithm, the original degraded infrared traffic image is transformed with dark channel prior as the initial enhanced result. A further adjustment based on the gamma curve is needed because initial enhanced result has lower brightness. Comprehensive validation experiments reveal that the proposed algorithm outperforms the current state-of-the-art algorithms.
Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression.
Dong, Zijing; Wang, Fuyixue; Ma, Xiaodong; Zhang, Zhe; Dai, Erpeng; Yuan, Chun; Guo, Hua
2018-03-01
To develop a novel diffusion imaging reconstruction framework based on iterative self-consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with computation acceleration by virtual coil compression. As a general approach for autocalibrating parallel imaging, SPIRiT improves the performance of traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) methods in that the formulation with self-consistency is better conditioned, suggesting SPIRiT to be a better candidate in k-space-based reconstruction. In this study, a general SPIRiT framework is adopted to incorporate both coil sensitivity and phase variation information as virtual coils and then is applied to 2D navigated iEPI diffusion imaging. To reduce the reconstruction time when using a large number of coils and shots, a novel shot-coil compression method is proposed for computation acceleration in Cartesian sampling. Simulations and in vivo experiments were conducted to evaluate the performance of the proposed method. Compared with the conventional coil compression, the shot-coil compression achieved higher compression rates with reduced errors. The simulation and in vivo experiments demonstrate that the SPIRiT-based reconstruction outperformed the existing method, realigned GRAPPA, and provided superior images with reduced artifacts. The SPIRiT-based reconstruction with virtual coil compression is a reliable method for high-resolution iEPI diffusion imaging. Magn Reson Med 79:1525-1531, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
A hybrid multimodal non-rigid registration of MR images based on diffeomorphic demons.
Lu, Huanxiang; Cattin, Philippe C; Reyes, Mauricio
2010-01-01
In this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.
Edge detection for optical synthetic aperture based on deep neural network
NASA Astrophysics Data System (ADS)
Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin
2017-09-01
Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.
Wang, Jin; Zhang, Chen; Wang, Yuanyuan
2017-05-30
In photoacoustic tomography (PAT), total variation (TV) based iteration algorithm is reported to have a good performance in PAT image reconstruction. However, classical TV based algorithm fails to preserve the edges and texture details of the image because it is not sensitive to the direction of the image. Therefore, it is of great significance to develop a new PAT reconstruction algorithm to effectively solve the drawback of TV. In this paper, a directional total variation with adaptive directivity (DDTV) model-based PAT image reconstruction algorithm, which weightedly sums the image gradients based on the spatially varying directivity pattern of the image is proposed to overcome the shortcomings of TV. The orientation field of the image is adaptively estimated through a gradient-based approach. The image gradients are weighted at every pixel based on both its anisotropic direction and another parameter, which evaluates the estimated orientation field reliability. An efficient algorithm is derived to solve the iteration problem associated with DDTV and possessing directivity of the image adaptively updated for each iteration step. Several texture images with various directivity patterns are chosen as the phantoms for the numerical simulations. The 180-, 90- and 30-view circular scans are conducted. Results obtained show that the DDTV-based PAT reconstructed algorithm outperforms the filtered back-projection method (FBP) and TV algorithms in the quality of reconstructed images with the peak signal-to-noise rations (PSNR) exceeding those of TV and FBP by about 10 and 18 dB, respectively, for all cases. The Shepp-Logan phantom is studied with further discussion of multimode scanning, convergence speed, robustness and universality aspects. In-vitro experiments are performed for both the sparse-view circular scanning and linear scanning. The results further prove the effectiveness of the DDTV, which shows better results than that of the TV with sharper image edges and clearer texture details. Both numerical simulation and in vitro experiments confirm that the DDTV provides a significant quality improvement of PAT reconstructed images for various directivity patterns.
CMOS image sensor-based implantable glucose sensor using glucose-responsive fluorescent hydrogel.
Tokuda, Takashi; Takahashi, Masayuki; Uejima, Kazuhiro; Masuda, Keita; Kawamura, Toshikazu; Ohta, Yasumi; Motoyama, Mayumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Okitsu, Teru; Takeuchi, Shoji; Ohta, Jun
2014-11-01
A CMOS image sensor-based implantable glucose sensor based on an optical-sensing scheme is proposed and experimentally verified. A glucose-responsive fluorescent hydrogel is used as the mediator in the measurement scheme. The wired implantable glucose sensor was realized by integrating a CMOS image sensor, hydrogel, UV light emitting diodes, and an optical filter on a flexible polyimide substrate. Feasibility of the glucose sensor was verified by both in vitro and in vivo experiments.
NASA Astrophysics Data System (ADS)
Bondareva, A. P.; Cheremkhin, P. A.; Evtikhiev, N. N.; Krasnov, V. V.; Starikov, S. N.
Scheme of optical image encryption with digital information input and dynamic encryption key based on two liquid crystal spatial light modulators and operating with spatially-incoherent monochromatic illumination is experimentally implemented. Results of experiments on images optical encryption and numerical decryption are presented. Satisfactory decryption error of 0.20÷0.27 is achieved.
Mission Specialist Hawley works with the SWUIS experiment
2013-11-18
STS093-350-022 (22-27 July 1999) --- Astronaut Steven A. Hawley, mission specialist, works with the Southwest Ultraviolet Imaging System (SWUIS) experiment onboard the Earth-orbiting Space Shuttle Columbia. The SWUIS is based around a Maksutov-design Ultraviolet (UV) telescope and a UV-sensitive, image-intensified Charge-Coupled Device (CCD) camera that frames at video frame rates.
An image mosaic method based on corner
NASA Astrophysics Data System (ADS)
Jiang, Zetao; Nie, Heting
2015-08-01
In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.
Image Mosaic Method Based on SIFT Features of Line Segment
Zhu, Jun; Ren, Mingwu
2014-01-01
This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326
Nighttime images fusion based on Laplacian pyramid
NASA Astrophysics Data System (ADS)
Wu, Cong; Zhan, Jinhao; Jin, Jicheng
2018-02-01
This paper expounds method of the average weighted fusion, image pyramid fusion, the wavelet transform and apply these methods on the fusion of multiple exposures nighttime images. Through calculating information entropy and cross entropy of fusion images, we can evaluate the effect of different fusion. Experiments showed that Laplacian pyramid image fusion algorithm is suitable for processing nighttime images fusion, it can reduce the halo while preserving image details.
An effective method on pornographic images realtime recognition
NASA Astrophysics Data System (ADS)
Wang, Baosong; Lv, Xueqiang; Wang, Tao; Wang, Chengrui
2013-03-01
In this paper, skin detection, texture filtering and face detection are used to extract feature on an image library, training them with the decision tree arithmetic to create some rules as a decision tree classifier to distinguish an unknown image. Experiment based on more than twenty thousand images, the precision rate can get 76.21% when testing on 13025 pornographic images and elapsed time is less than 0.2s. This experiment shows it has a good popularity. Among the steps mentioned above, proposing a new skin detection model which called irregular polygon region skin detection model based on YCbCr color space. This skin detection model can lower the false detection rate on skin detection. A new method called sequence region labeling on binary connected area can calculate features on connected area, it is faster and needs less memory than other recursive methods.
Tag-Based Social Image Search: Toward Relevant and Diverse Results
NASA Astrophysics Data System (ADS)
Yang, Kuiyuan; Wang, Meng; Hua, Xian-Sheng; Zhang, Hong-Jiang
Recent years have witnessed a great success of social media websites. Tag-based image search is an important approach to access the image content of interest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the content of images and their associated tags. First, it estimates the relevance scores of images with respect to the query term based on both visual information of images and semantic information of associated tags. Then semantic similarities of social images are estimated based on their tags. Based on the relevance scores and the similarities, the ranking list is generated by a greedy ordering algorithm which optimizes Average Diverse Precision (ADP), a novel measure that is extended from the conventional Average Precision (AP). Comprehensive experiments and user studies demonstrate the effectiveness of the approach.
Imaging learning and memory: classical conditioning.
Schreurs, B G; Alkon, D L
2001-12-15
The search for the biological basis of learning and memory has, until recently, been constrained by the limits of technology to classic anatomic and electrophysiologic studies. With the advent of functional imaging, we have begun to delve into what, for many, was a "black box." We review several different types of imaging experiments, including steady state animal experiments that image the functional labeling of fixed tissues, and dynamic human studies based on functional imaging of the intact brain during learning. The data suggest that learning and memory involve a surprising conservation of mechanisms and the integrated networking of a number of structures and processes. Copyright 2001 Wiley-Liss, Inc.
Precise and Efficient Retrieval of Captioned Images: The MARIE Project.
ERIC Educational Resources Information Center
Rowe, Neil C.
1999-01-01
The MARIE project explores knowledge-based information retrieval of captioned images of the kind found in picture libraries and on the Internet. MARIE's five-part approach exploits the idea that images are easier to understand with context, especially descriptive text near them, but it also does image analysis. Experiments show MARIE prototypes…
Gray-scale transform and evaluation for digital x-ray chest images on CRT monitor
NASA Astrophysics Data System (ADS)
Furukawa, Isao; Suzuki, Junji; Ono, Sadayasu; Kitamura, Masayuki; Ando, Yutaka
1997-04-01
In this paper, an experimental evaluation of a super high definition (SHD) imaging system for digital x-ray chest images is presented. The SHD imaging system is proposed as a platform for integrating conventional image media. We are involved in the use of SHD images in the total digitizing of medical records that include chest x-rays and pathological microscopic images, both which demand the highest level of quality among the various types of medical images. SHD images use progressive scanning and have a spatial resolution of 2000 by 2000 pixels or more and a temporal resolution (frame rate) of 60 frames/sec or more. For displaying medical x-ray images on a CRT, we derived gray scale transform characteristics based on radiologists' comments during the experiment, and elucidated the relationship between that gray scale transform and the linearization transform for maintaining the linear relationship with the luminance of film on a light box (luminance linear transform). We then carried out viewing experiments based on a five-stage evaluation. Nine radiologists participated in our experiment, and the ten cases evaluated included pulmonary fibrosis, lung cancer, and pneumonia. The experimental results indicated that conventional film images and those on super high definition CRT monitors have nearly the same quality. They also show that the gray scale transform for CRT images decided according to radiologists' comments agrees with the luminance linear transform in the high luminance region. And in the low luminance region, it was found that the gray scale transform had the characteristics of level expansion to increase the number of levels that can be expressed.
NASA Astrophysics Data System (ADS)
Nakagawa, M.; Akano, K.; Kobayashi, T.; Sekiguchi, Y.
2017-09-01
Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.
Objective quality assessment for multiexposure multifocus image fusion.
Hassen, Rania; Wang, Zhou; Salama, Magdy M A
2015-09-01
There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures.
Image based SAR product simulation for analysis
NASA Technical Reports Server (NTRS)
Domik, G.; Leberl, F.
1987-01-01
SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.
Imaging an Active Volcano Edifice at Tenerife Island, Spain
NASA Astrophysics Data System (ADS)
Ibáñez, Jesús M.; Rietbrock, Andreas; García-Yeguas, Araceli
2008-08-01
An active seismic experiment to study the internal structure of Teide volcano is being carried out on Tenerife, a volcanic island in Spain's Canary Islands archipelago. The main objective of the Tomography at Teide Volcano Spain (TOM-TEIDEVS) experiment, begun in January 2007, is to obtain a three-dimensional (3-D) structural image of Teide volcano using seismic tomography and seismic reflection/refraction imaging techniques. At present, knowledge of the deeper structure of Teide and Tenerife is very limited, with proposed structural models based mainly on sparse geophysical and geological data. The multinational experiment-involving institutes from Spain, the United Kingdom, Italy, Ireland, and Mexico-will generate a unique high-resolution structural image of the active volcano edifice and will further our understanding of volcanic processes.
Ground-based full-sky imaging polarimeter based on liquid crystal variable retarders.
Zhang, Ying; Zhao, Huijie; Song, Ping; Shi, Shaoguang; Xu, Wujian; Liang, Xiao
2014-04-07
A ground-based full-sky imaging polarimeter based on liquid crystal variable retarders (LCVRs) is proposed in this paper. Our proposed method can be used to realize the rapid detection of the skylight polarization information with hemisphere field-of-view for the visual band. The characteristics of the incidence angle of light on the LCVR are investigated, based on the electrically controlled birefringence. Then, the imaging polarimeter with hemisphere field-of-view is designed. Furthermore, the polarization calibration method with the field-of-view multiplexing and piecewise linear fitting is proposed, based on the rotation symmetry of the polarimeter. The polarization calibration of the polarimeter is implemented with the hemisphere field-of-view. This imaging polarimeter is investigated by the experiment of detecting the skylight image. The consistency between the obtained experimental distribution of polarization angle with that due to Rayleigh scattering model is 90%, which confirms the effectivity of our proposed imaging polarimeter.
NASA Astrophysics Data System (ADS)
Hu, Jinyan; Li, Li; Yang, Yunfeng
2017-06-01
The hierarchical and successive approximate registration method of non-rigid medical image based on the thin-plate splines is proposed in the paper. There are two major novelties in the proposed method. First, the hierarchical registration based on Wavelet transform is used. The approximate image of Wavelet transform is selected as the registered object. Second, the successive approximation registration method is used to accomplish the non-rigid medical images registration, i.e. the local regions of the couple images are registered roughly based on the thin-plate splines, then, the current rough registration result is selected as the object to be registered in the following registration procedure. Experiments show that the proposed method is effective in the registration process of the non-rigid medical images.
Automated camera-phone experience with the frequency of imaging necessary to capture diet.
Arab, Lenore; Winter, Ashley
2010-08-01
Camera-enabled cell phones provide an opportunity to strengthen dietary recall through automated imaging of foods eaten during a specified period. To explore the frequency of imaging needed to capture all foods eaten, we examined the number of images of individual foods consumed in a pilot study of automated imaging using camera phones set to an image-capture frequency of one snapshot every 10 seconds. Food images were tallied from 10 young adult subjects who wore the phone continuously during the work day and consented to share their images. Based on the number of images received for each eating experience, the pilot data suggest that automated capturing of images at a frequency of once every 10 seconds is adequate for recording foods consumed during regular meals, whereas a greater frequency of imaging is necessary to capture snacks and beverages eaten quickly. 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.
Sociocultural experiences, body image, and indoor tanning among young adult women.
Stapleton, Jerod L; Manne, Sharon L; Greene, Kathryn; Darabos, Katie; Carpenter, Amanda; Hudson, Shawna V; Coups, Elliot J
2017-10-01
The purpose of this survey study was to evaluate a model of body image influences on indoor tanning behavior. Participants were 823 young adult women recruited from a probability-based web panel in the United States. Consistent with our hypothesized model, tanning-related sociocultural experiences were indirectly associated with lifetime indoor tanning use and intentions to tan as mediated through tan surveillance and tan dissatisfaction. Findings suggest the need for targeting body image constructs as mechanisms of behavior change in indoor tanning behavioral interventions.
Knowledge-based imaging-sensor fusion system
NASA Technical Reports Server (NTRS)
Westrom, George
1989-01-01
An imaging system which applies knowledge-based technology to supervise and control both sensor hardware and computation in the imaging system is described. It includes the development of an imaging system breadboard which brings together into one system work that we and others have pursued for LaRC for several years. The goal is to combine Digital Signal Processing (DSP) with Knowledge-Based Processing and also include Neural Net processing. The system is considered a smart camera. Imagine that there is a microgravity experiment on-board Space Station Freedom with a high frame rate, high resolution camera. All the data cannot possibly be acquired from a laboratory on Earth. In fact, only a small fraction of the data will be received. Again, imagine being responsible for some experiments on Mars with the Mars Rover: the data rate is a few kilobits per second for data from several sensors and instruments. Would it not be preferable to have a smart system which would have some human knowledge and yet follow some instructions and attempt to make the best use of the limited bandwidth for transmission. The system concept, current status of the breadboard system and some recent experiments at the Mars-like Amboy Lava Fields in California are discussed.
Unsupervised malaria parasite detection based on phase spectrum.
Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong
2011-01-01
In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method.
CMOS image sensor-based implantable glucose sensor using glucose-responsive fluorescent hydrogel
Tokuda, Takashi; Takahashi, Masayuki; Uejima, Kazuhiro; Masuda, Keita; Kawamura, Toshikazu; Ohta, Yasumi; Motoyama, Mayumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Okitsu, Teru; Takeuchi, Shoji; Ohta, Jun
2014-01-01
A CMOS image sensor-based implantable glucose sensor based on an optical-sensing scheme is proposed and experimentally verified. A glucose-responsive fluorescent hydrogel is used as the mediator in the measurement scheme. The wired implantable glucose sensor was realized by integrating a CMOS image sensor, hydrogel, UV light emitting diodes, and an optical filter on a flexible polyimide substrate. Feasibility of the glucose sensor was verified by both in vitro and in vivo experiments. PMID:25426316
Image denoising based on noise detection
NASA Astrophysics Data System (ADS)
Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen
2018-03-01
Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.
NMR-based diffusion pore imaging.
Laun, Frederik Bernd; Kuder, Tristan Anselm; Wetscherek, Andreas; Stieltjes, Bram; Semmler, Wolfhard
2012-08-01
Nuclear magnetic resonance (NMR) diffusion experiments offer a unique opportunity to study boundaries restricting the diffusion process. In a recent Letter [Phys. Rev. Lett. 107, 048102 (2011)], we introduced the idea and concept that such diffusion experiments can be interpreted as NMR imaging experiments. Consequently, images of closed pores, in which the spins diffuse, can be acquired. In the work presented here, an in-depth description of the diffusion pore imaging technique is provided. Image artifacts due to gradient profiles of finite duration, field inhomogeneities, and surface relaxation are considered. Gradients of finite duration lead to image blurring and edge enhancement artifacts. Field inhomogeneities have benign effects on diffusion pore images, and surface relaxation can lead to a shrinkage and shift of the pore image. The relation between boundary structure and the imaginary part of the diffusion weighted signal is analyzed, and it is shown that information on pore coherence can be obtained without the need to measure the phase of the diffusion weighted signal. Moreover, it is shown that quite arbitrary gradient profiles can be used for diffusion pore imaging. The matrices required for numerical calculations are stated and provided as supplemental material.
Clustering-based spot segmentation of cDNA microarray images.
Uslan, Volkan; Bucak, Ihsan Ömür
2010-01-01
Microarrays are utilized as that they provide useful information about thousands of gene expressions simultaneously. In this study segmentation step of microarray image processing has been implemented. Clustering-based methods, fuzzy c-means and k-means, have been applied for the segmentation step that separates the spots from the background. The experiments show that fuzzy c-means have segmented spots of the microarray image more accurately than the k-means.
Birdcage volume coils and magnetic resonance imaging: a simple experiment for students.
Vincent, Dwight E; Wang, Tianhao; Magyar, Thalia A K; Jacob, Peni I; Buist, Richard; Martin, Melanie
2017-01-01
This article explains some simple experiments that can be used in undergraduate or graduate physics or biomedical engineering laboratory classes to learn how birdcage volume radiofrequency (RF) coils and magnetic resonance imaging (MRI) work. For a clear picture, and to do any quantitative MRI analysis, acquiring images with a high signal-to-noise ratio (SNR) is required. With a given MRI system at a given field strength, the only means to change the SNR using hardware is to change the RF coil used to collect the image. RF coils can be designed in many different ways including birdcage volume RF coil designs. The choice of RF coil to give the best SNR for any MRI study is based on the sample being imaged. The data collected in the simple experiments show that the SNR varies as inverse diameter for the birdcage volume RF coils used in these experiments. The experiments were easily performed by a high school student, an undergraduate student, and a graduate student, in less than 3 h, the time typically allotted for a university laboratory course. The article describes experiments that students in undergraduate or graduate laboratories can perform to observe how birdcage volume RF coils influence MRI measurements. It is designed for students interested in pursuing careers in the imaging field.
2015-11-05
AFRL-AFOSR-VA-TR-2015-0359 Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast Imaging Viktor Gruev...To) 02/15/2011 - 08/15/2015 4. TITLE AND SUBTITLE Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast...investigate alternative spectral imaging architectures based on my previous experience in this research area. I will develop nanowire polarization
D Reconstruction with a Collaborative Approach Based on Smartphones and a Cloud-Based Server
NASA Astrophysics Data System (ADS)
Nocerino, E.; Poiesi, F.; Locher, A.; Tefera, Y. T.; Remondino, F.; Chippendale, P.; Van Gool, L.
2017-11-01
The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone's camera based on their quality and novelty. The smartphone's app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.
Single-pixel imaging based on compressive sensing with spectral-domain optical mixing
NASA Astrophysics Data System (ADS)
Zhu, Zhijing; Chi, Hao; Jin, Tao; Zheng, Shilie; Jin, Xiaofeng; Zhang, Xianmin
2017-11-01
In this letter a single-pixel imaging structure is proposed based on compressive sensing using a spatial light modulator (SLM)-based spectrum shaper. In the approach, an SLM-based spectrum shaper, the pattern of which is a predetermined pseudorandom bit sequence (PRBS), spectrally codes the optical pulse carrying image information. The energy of the spectrally mixed pulse is detected by a single-pixel photodiode and the measurement results are used to reconstruct the image via a sparse recovery algorithm. As the mixing of the image signal and the PRBS is performed in the spectral domain, optical pulse stretching, modulation, compression and synchronization in the time domain are avoided. Experiments are implemented to verify the feasibility of the approach.
ERIC Educational Resources Information Center
Humphreys, Glyn W.; Wulff, Melanie; Yoon, Eun Young; Riddoch, M. Jane
2010-01-01
Two experiments are reported that use patients with visual extinction to examine how visual attention is influenced by action information in images. In Experiment 1 patients saw images of objects that were either correctly or incorrectly colocated for action, with the objects held by hands that were congruent or incongruent with those used…
ERIC Educational Resources Information Center
Huck-Iriart, Cristia´n; De-Candia, Ariel; Rodriguez, Javier; Rinaldi, Carlos
2016-01-01
In this work, we described an image processing procedure for the measurement of surface tension of the air-liquid interface using isothermal capillary action. The experiment, designed for an undergraduate course, is based on the analysis of a series of solutions with diverse surfactant concentrations at different ionic strengths. The objective of…
Research on simulated infrared image utility evaluation using deep representation
NASA Astrophysics Data System (ADS)
Zhang, Ruiheng; Mu, Chengpo; Yang, Yu; Xu, Lixin
2018-01-01
Infrared (IR) image simulation is an important data source for various target recognition systems. However, whether simulated IR images could be used as training data for classifiers depends on the features of fidelity and authenticity of simulated IR images. For evaluation of IR image features, a deep-representation-based algorithm is proposed. Being different from conventional methods, which usually adopt a priori knowledge or manually designed feature, the proposed method can extract essential features and quantitatively evaluate the utility of simulated IR images. First, for data preparation, we employ our IR image simulation system to generate large amounts of IR images. Then, we present the evaluation model of simulated IR image, for which an end-to-end IR feature extraction and target detection model based on deep convolutional neural network is designed. At last, the experiments illustrate that our proposed method outperforms other verification algorithms in evaluating simulated IR images. Cross-validation, variable proportion mixed data validation, and simulation process contrast experiments are carried out to evaluate the utility and objectivity of the images generated by our simulation system. The optimum mixing ratio between simulated and real data is 0.2≤γ≤0.3, which is an effective data augmentation method for real IR images.
Image Enhancement via Subimage Histogram Equalization Based on Mean and Variance
2017-01-01
This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. PMID:29403529
Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.
Pan, Shaoming; Li, Yongkai; Xu, Zhengquan; Chong, Yanwen
2015-01-01
Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.
NASA Astrophysics Data System (ADS)
Gatlin, Todd Adam
Graduate teaching assistants (GTAs) play a prominent role in chemistry laboratory instruction at research based universities. They teach almost all undergraduate chemistry laboratory courses. However, their role in laboratory instruction has often been overlooked in educational research. Interest in chemistry GTAs has been placed on training and their perceived expectations, but less attention has been paid to their experiences or their potential benefits from teaching. This work was designed to investigate GTAs' experiences in and benefits from laboratory instructional environments. This dissertation includes three related studies on GTAs' experiences teaching in general chemistry laboratories. Qualitative methods were used for each study. First, phenomenological analysis was used to explore GTAs' experiences in an expository laboratory program. Post-teaching interviews were the primary data source. GTAs experiences were described in three dimensions: doing, knowing, and transferring. Gains available to GTAs revolved around general teaching skills. However, no gains specifically related to scientific development were found in this laboratory format. Case-study methods were used to explore and illustrate ways GTAs develop a GTA self-image---the way they see themselves as instructors. Two general chemistry laboratory programs that represent two very different instructional frameworks were chosen for the context of this study. The first program used a cooperative project-based approach. The second program used weekly, verification-type activities. End of the semester interviews were collected and served as the primary data source. A follow-up case study of a new cohort of GTAs in the cooperative problem-based laboratory was undertaken to investigate changes in GTAs' self-images over the course of one semester. Pre-semester and post-semester interviews served as the primary data source. Findings suggest that GTAs' construction of their self-image is shaped through the interaction of 1) prior experiences, 2) training, 3) beliefs about the nature of knowledge, 4) beliefs about the nature of laboratory work, and 5) involvement in the laboratory setting. Further GTAs' self-images are malleable and susceptible to change through their laboratory teaching experiences. Overall, this dissertation contributes to chemistry education by providing a model useful for exploring GTAs' development of a self-image in laboratory teaching. This work may assist laboratory instructors and coordinators in reconsidering, when applicable, GTA training and support. This work also holds considerable implications for how teaching experiences are conceptualized as part of the chemistry graduate education experience. Findings suggest that appropriate teaching experiences may contribute towards better preparing graduate students for their journey in becoming scientists.
NASA Astrophysics Data System (ADS)
Rahman, Md M.; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.
2015-03-01
This paper presents a novel approach to biomedical image retrieval by mapping image regions to local concepts and represent images in a weighted entropy-based concept feature space. The term concept refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist user in interactively select a Region-Of-Interest (ROI) and search for similar image ROIs. Further, a spatial verification step is used as a post-processing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval, is validated through experiments on a data set of 450 lung CT images extracted from journal articles from four different collections.
An automated image-collection system for crystallization experiments using SBS standard microplates.
Brostromer, Erik; Nan, Jie; Su, Xiao Dong
2007-02-01
As part of a structural genomics platform in a university laboratory, a low-cost in-house-developed automated imaging system for SBS microplate experiments has been designed and constructed. The imaging system can scan a microplate in 2-6 min for a 96-well plate depending on the plate layout and scanning options. A web-based crystallization database system has been developed, enabling users to follow their crystallization experiments from a web browser. As the system has been designed and built by students and crystallographers using commercially available parts, this report is aimed to serve as a do-it-yourself example for laboratory robotics.
George, Stephanie M; Domire, Zachary J
2017-07-01
As the reliance on computational models to inform experiments and evaluate medical devices grows, the demand for students with modeling experience will grow. In this paper, we report on the 3-yr experience of a National Science Foundation (NSF) funded Research Experiences for Undergraduates (REU) based on the theme simulations, imaging, and modeling in biomechanics. While directly applicable to REU sites, our findings also apply to those creating other types of summer undergraduate research programs. The objective of the paper is to examine if a theme of simulations, imaging, and modeling will improve students' understanding of the important topic of modeling, provide an overall positive research experience, and provide an interdisciplinary experience. The structure of the program and the evaluation plan are described. We report on the results from 25 students over three summers from 2014 to 2016. Overall, students reported significant gains in the knowledge of modeling, research process, and graduate school based on self-reported mastery levels and open-ended qualitative responses. This theme provides students with a skill set that is adaptable to other applications illustrating the interdisciplinary nature of modeling in biomechanics. Another advantage is that students may also be able to continue working on their project following the summer experience through network connections. In conclusion, we have described the successful implementation of the theme simulation, imaging, and modeling for an REU site and the overall positive response of the student participants.
Real-time interactive virtual tour on the World Wide Web (WWW)
NASA Astrophysics Data System (ADS)
Yoon, Sanghyuk; Chen, Hai-jung; Hsu, Tom; Yoon, Ilmi
2003-12-01
Web-based Virtual Tour has become a desirable and demanded application, yet challenging due to the nature of web application's running environment such as limited bandwidth and no guarantee of high computation power on the client side. Image-based rendering approach has attractive advantages over traditional 3D rendering approach in such Web Applications. Traditional approach, such as VRML, requires labor-intensive 3D modeling process, high bandwidth and computation power especially for photo-realistic virtual scenes. QuickTime VR and IPIX as examples of image-based approach, use panoramic photos and the virtual scenes that can be generated from photos directly skipping the modeling process. But, these image-based approaches may require special cameras or effort to take panoramic views and provide only one fixed-point look-around and zooming in-out rather than 'walk around', that is a very important feature to provide immersive experience to virtual tourists. The Web-based Virtual Tour using Tour into the Picture employs pseudo 3D geometry with image-based rendering approach to provide viewers with immersive experience of walking around the virtual space with several snap shots of conventional photos.
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks
Xu, Xin; Gui, Rong; Pu, Fangling
2018-01-01
Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499
Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks.
Wang, Lei; Xu, Xin; Dong, Hao; Gui, Rong; Pu, Fangling
2018-03-03
Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods.
NASA Astrophysics Data System (ADS)
Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun
2018-05-01
This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.
Image dehazing based on non-local saturation
NASA Astrophysics Data System (ADS)
Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting
2018-04-01
In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.
Mountainous Crater Rim on Mars
2013-10-17
This is a screen shot from a high-definition simulated movie of Mojave Crater on Mars, based on images taken by the High Resolution Imaging Science Experiment HiRISE camera on NASA Mars Reconnaissance Orbiter.
Contrast-enhanced optical coherence microangiography with acoustic-actuated microbubbles
NASA Astrophysics Data System (ADS)
Liu, Yu-Hsuan; Zhang, Jia-Wei; Yeh, Chih-Kuang; Wei, Kuo-Chen; Liu, Hao-Li; Tsai, Meng-Tsan
2017-04-01
In this study, we propose to use gas-filled microbubbles (MBs) simultaneously actuated by the acoustic wave to enhance the imaging contrast of optical coherence tomography (OCT)-based angiography. In the phantom experiments, MBs can result in stronger backscattered intensity, enabling to enhance the contrast of OCT intensity image. Moreover, simultaneous application of low-intensity acoustic wave enables to temporally induce local vibration of particles and MBs in the vessels, resulting in time-variant OCT intensity which can be used for enhancing the contrast of OCT intensitybased angiography. Additionally, different acoustic modes and different acoustic powers to actuate MBs are performed and compared to investigate the feasibility of contrast enhancement. Finally, animal experiments are performed. The findings suggest that acoustic-actuated MBs can effectively enhance the imaging contrast of OCT-based angiography and the imaging depth of OCT angiography is also extended.
A Unified Steganalysis Framework
2013-04-01
contains more than 1800 images of different scenes. In the experiments, we used four JPEG based steganography techniques: Out- guess [13], F5 [16], model...also compressed these images again since some of the steganography meth- ods are double compressing the images . Stego- images are generated by embedding...randomly chosen messages (in bits) into 1600 grayscale images using each of the four steganography techniques. A random message length was determined
NASA Astrophysics Data System (ADS)
Williams, Godfried B.
2005-03-01
This paper attempts to demonstrate a novel based idea for transforming statistical image data to text using autoassociative and unsupervised artificial neural network and iconic image maps using the shape and texture genetic algorithm, underlying concepts translating the image data to text. Full details of experiments could be assessed at http://www.uel.ac.uk/seis/applications/.
NASA Astrophysics Data System (ADS)
Huang, Yadong; Gao, Kun; Gong, Chen; Han, Lu; Guo, Yue
2016-03-01
During traditional multi-resolution infrared and visible image fusion processing, the low contrast ratio target may be weakened and become inconspicuous because of the opposite DN values in the source images. So a novel target pseudo-color enhanced image fusion algorithm based on the modified attention model and fast discrete curvelet transformation is proposed. The interesting target regions are extracted from source images by introducing the motion features gained from the modified attention model, and source images are performed the gray fusion via the rules based on physical characteristics of sensors in curvelet domain. The final fusion image is obtained by mapping extracted targets into the gray result with the proper pseudo-color instead. The experiments show that the algorithm can highlight dim targets effectively and improve SNR of fusion image.
Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek
2013-01-01
Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.
A Control System and Streaming DAQ Platform with Image-Based Trigger for X-ray Imaging
NASA Astrophysics Data System (ADS)
Stevanovic, Uros; Caselle, Michele; Cecilia, Angelica; Chilingaryan, Suren; Farago, Tomas; Gasilov, Sergey; Herth, Armin; Kopmann, Andreas; Vogelgesang, Matthias; Balzer, Matthias; Baumbach, Tilo; Weber, Marc
2015-06-01
High-speed X-ray imaging applications play a crucial role for non-destructive investigations of the dynamics in material science and biology. On-line data analysis is necessary for quality assurance and data-driven feedback, leading to a more efficient use of a beam time and increased data quality. In this article we present a smart camera platform with embedded Field Programmable Gate Array (FPGA) processing that is able to stream and process data continuously in real-time. The setup consists of a Complementary Metal-Oxide-Semiconductor (CMOS) sensor, an FPGA readout card, and a readout computer. It is seamlessly integrated in a new custom experiment control system called Concert that provides a more efficient way of operating a beamline by integrating device control, experiment process control, and data analysis. The potential of the embedded processing is demonstrated by implementing an image-based trigger. It records the temporal evolution of physical events with increased speed while maintaining the full field of view. The complete data acquisition system, with Concert and the smart camera platform was successfully integrated and used for fast X-ray imaging experiments at KIT's synchrotron radiation facility ANKA.
Hard X-ray Imaging for Measuring Laser Absorption Spatial Profiles on the National Ignition Facility
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dewald, E L; Jones, O S; Landen, O L
2006-04-25
Hard x-ray (''Thin wall'') imaging will be employed on the National Ignition Facility (NIF) to spatially locate laser beam energy deposition regions on the hohlraum walls in indirect drive Inertial Confinement Fusion (ICF) experiments, relevant for ICF symmetry tuning. Based on time resolved imaging of the hard x-ray emission of the laser spots, this method will be used to infer hohlraum wall motion due to x-ray and laser ablation and any beam refraction caused by plasma density gradients. In optimizing this measurement, issues that have to be addressed are hard x-ray visibility during the entire ignition laser pulse with intensitiesmore » ranging from 10{sup 13} to 10{sup 15} W/cm{sup 2}, as well as simultaneous visibility of the inner and the outer laser drive cones. In this work we will compare the hard x-ray emission calculated by LASNEX and analytical modeling with thin wall imaging data recorded previously on Omega and during the first hohlraum experiments on NIF. Based on these calculations and comparisons the thin wall imaging will be optimized for ICF/NIF experiments.« less
GAO, L.; HAGEN, N.; TKACZYK, T.S.
2012-01-01
Summary We implement a filterless illumination scheme on a hyperspectral fluorescence microscope to achieve full-range spectral imaging. The microscope employs polarisation filtering, spatial filtering and spectral unmixing filtering to replace the role of traditional filters. Quantitative comparisons between full-spectrum and filter-based microscopy are provided in the context of signal dynamic range and accuracy of measured fluorophores’ emission spectra. To show potential applications, a five-colour cell immunofluorescence imaging experiment is theoretically simulated. Simulation results indicate that the use of proposed full-spectrum imaging technique may result in three times improvement in signal dynamic range compared to that can be achieved in the filter-based imaging. PMID:22356127
Compressed domain indexing of losslessly compressed images
NASA Astrophysics Data System (ADS)
Schaefer, Gerald
2001-12-01
Image retrieval and image compression have been pursued separately in the past. Only little research has been done on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to uncompress them first. In this paper methods for image retrieval in the compressed domain of losslessly compressed images are introduced. While most image compression techniques are lossy, i.e. discard visually less significant information, lossless techniques are still required in fields like medical imaging or in situations where images must not be changed due to legal reasons. The algorithms in this paper are based on predictive coding methods where a pixel is encoded based on the pixel values of its (already encoded) neighborhood. The first method is based on an understanding that predictively coded data is itself indexable and represents a textural description of the image. The second method operates directly on the entropy encoded data by comparing codebooks of images. Experiments show good image retrieval results for both approaches.
Narayan, Nikhil S; Marziliano, Pina
2015-08-01
Automatic detection and segmentation of the common carotid artery in transverse ultrasound (US) images of the thyroid gland play a vital role in the success of US guided intervention procedures. We propose in this paper a novel method to accurately detect, segment and track the carotid in 2D and 2D+t US images of the thyroid gland using concepts based on tissue echogenicity and ultrasound image formation. We first segment the hypoechoic anatomical regions of interest using local phase and energy in the input image. We then make use of a Hessian based blob like analysis to detect the carotid within the segmented hypoechoic regions. The carotid artery is segmented by making use of least squares ellipse fit for the edge points around the detected carotid candidate. Experiments performed on a multivendor dataset of 41 images show that the proposed algorithm can segment the carotid artery with high sensitivity (99.6 ±m 0.2%) and specificity (92.9 ±m 0.1%). Further experiments on a public database containing 971 images of the carotid artery showed that the proposed algorithm can achieve a detection accuracy of 95.2% with a 2% increase in performance when compared to the state-of-the-art method.
Psychoanalytic Bases for One's Image of God: Fact or Artifact?
ERIC Educational Resources Information Center
Buri, John R.
As a result of Freud's seminal postulations of the psychoanalytic bases for one's God-concept, it is a frequently accepted hypothesis that an individual's image of God is largely a reflection of experiences with and feelings toward one's own father. While such speculations as to an individual's phenomenological conceptions of God have an…
Incorporating an Image-Based, Multimodal Pedagogy into Global Citizenship Education
ERIC Educational Resources Information Center
Kang, Rui; Mehranian, Yeprem; Hyatt, Charles
2017-01-01
Drawing on theories and practices in literacy education and in particular, the concepts of semiotics and transmediation, we explored the possibility of arts-based experiences such as Augusto Boal's Image Theatre in facilitating transformation of thinking in the context of global citizenship education. The objectives of this research were twofold.…
NASA Astrophysics Data System (ADS)
Min, Junhong; Carlini, Lina; Unser, Michael; Manley, Suliana; Ye, Jong Chul
2015-09-01
Localization microscopy such as STORM/PALM can achieve a nanometer scale spatial resolution by iteratively localizing fluorescence molecules. It was shown that imaging of densely activated molecules can accelerate temporal resolution which was considered as major limitation of localization microscopy. However, this higher density imaging needs to incorporate advanced localization algorithms to deal with overlapping point spread functions (PSFs). In order to address this technical challenges, previously we developed a localization algorithm called FALCON1, 2 using a quasi-continuous localization model with sparsity prior on image space. It was demonstrated in both 2D/3D live cell imaging. However, it has several disadvantages to be further improved. Here, we proposed a new localization algorithm using annihilating filter-based low rank Hankel structured matrix approach (ALOHA). According to ALOHA principle, sparsity in image domain implies the existence of rank-deficient Hankel structured matrix in Fourier space. Thanks to this fundamental duality, our new algorithm can perform data-adaptive PSF estimation and deconvolution of Fourier spectrum, followed by truly grid-free localization using spectral estimation technique. Furthermore, all these optimizations are conducted on Fourier space only. We validated the performance of the new method with numerical experiments and live cell imaging experiment. The results confirmed that it has the higher localization performances in both experiments in terms of accuracy and detection rate.
Visualizing Chemistry with Infrared Imaging
ERIC Educational Resources Information Center
Xie, Charles
2011-01-01
Almost all chemical processes release or absorb heat. The heat flow in a chemical system reflects the process it is undergoing. By showing the temperature distribution dynamically, infrared (IR) imaging provides a salient visualization of the process. This paper presents a set of simple experiments based on IR imaging to demonstrate its enormous…
NASA Astrophysics Data System (ADS)
Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.
2018-04-01
A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.
Automated Analysis of siRNA Screens of Virus Infected Cells Based on Immunofluorescence Microscopy
NASA Astrophysics Data System (ADS)
Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl
We present an image analysis approach as part of a high-throughput microscopy screening system based on cell arrays for the identification of genes involved in Hepatitis C and Dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in cells, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behavior of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.
Distance-based over-segmentation for single-frame RGB-D images
NASA Astrophysics Data System (ADS)
Fang, Zhuoqun; Wu, Chengdong; Chen, Dongyue; Jia, Tong; Yu, Xiaosheng; Zhang, Shihong; Qi, Erzhao
2017-11-01
Over-segmentation, known as super-pixels, is a widely used preprocessing step in segmentation algorithms. Oversegmentation algorithm segments an image into regions of perceptually similar pixels, but performs badly based on only color image in the indoor environments. Fortunately, RGB-D images can improve the performances on the images of indoor scene. In order to segment RGB-D images into super-pixels effectively, we propose a novel algorithm, DBOS (Distance-Based Over-Segmentation), which realizes full coverage of super-pixels on the image. DBOS fills the holes in depth images to fully utilize the depth information, and applies SLIC-like frameworks for fast running. Additionally, depth features such as plane projection distance are extracted to compute distance which is the core of SLIC-like frameworks. Experiments on RGB-D images of NYU Depth V2 dataset demonstrate that DBOS outperforms state-ofthe-art methods in quality while maintaining speeds comparable to them.
Otero, Jorge; Guerrero, Hector; Gonzalez, Laura; Puig-Vidal, Manel
2012-01-01
The time required to image large samples is an important limiting factor in SPM-based systems. In multiprobe setups, especially when working with biological samples, this drawback can make impossible to conduct certain experiments. In this work, we present a feedfordward controller based on bang-bang and adaptive controls. The controls are based in the difference between the maximum speeds that can be used for imaging depending on the flatness of the sample zone. Topographic images of Escherichia coli bacteria samples were acquired using the implemented controllers. Results show that to go faster in the flat zones, rather than using a constant scanning speed for the whole image, speeds up the imaging process of large samples by up to a 4× factor. PMID:22368491
Same-Day Imaging Using Small Proteins: Clinical Experience and Translational Prospects in Oncology.
Krasniqi, Ahmet; D'Huyvetter, Matthias; Devoogdt, Nick; Frejd, Fredrik Y; Sörensen, Jens; Orlova, Anna; Keyaerts, Marleen; Tolmachev, Vladimir
2018-06-01
Imaging of expression of therapeutic targets may enable stratification of patients for targeted treatments. The use of small radiolabeled probes based on the heavy-chain variable region of heavy-chain-only immunoglobulins or nonimmunoglobulin scaffolds permits rapid localization of radiotracers in tumors and rapid clearance from normal tissues. This makes high-contrast imaging possible on the day of injection. This mini review focuses on small proteins for radionuclide-based imaging that would allow same-day imaging, with the emphasis on clinical applications and promising preclinical developments within the field of oncology. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.
MEMS-based system and image processing strategy for epiretinal prosthesis.
Xia, Peng; Hu, Jie; Qi, Jin; Gu, Chaochen; Peng, Yinghong
2015-01-01
Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.
NASA Astrophysics Data System (ADS)
Guan, Jinge; Ren, Wei; Cheng, Yaoyu
2018-04-01
We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.
Mechanical Damage Detection of Indonesia Local Citrus Based on Fluorescence Imaging
NASA Astrophysics Data System (ADS)
Siregar, T. H.; Ahmad, U.; Sutrisno; Maddu, A.
2018-05-01
Citrus experienced physical damage in peel will produce essential oils that contain polymethoxylated flavone. Polymethoxylated flavone is fluorescence substance; thus can be detected by fluorescence imaging. This study aims to study the fluorescence spectra characteristic and to determine the damage region in citrus peel based on fluorescence image. Pulung citrus from Batu district, East Java, as a famous citrus production area in Indonesia, was used in the experiment. It was observed that the image processing could detect the mechanical damage region. Fluorescence imaging can be used to classify the citrus into two categories, sound and defect citruses.
Optical image hiding based on chaotic vibration of deformable moiré grating
NASA Astrophysics Data System (ADS)
Lu, Guangqing; Saunoriene, Loreta; Aleksiene, Sandra; Ragulskis, Minvydas
2018-03-01
Image hiding technique based on chaotic vibration of deformable moiré grating is presented in this paper. The embedded secret digital image is leaked in a form of a pattern of time-averaged moiré fringes when the deformable cover grating vibrates according to a chaotic law of motion with a predefined set of parameters. Computational experiments are used to demonstrate the features and the applicability of the proposed scheme.
Topological charge number multiplexing for JTC multiple-image encryption
NASA Astrophysics Data System (ADS)
Chen, Qi; Shen, Xueju; Dou, Shuaifeng; Lin, Chao; Wang, Long
2018-04-01
We propose a method of topological charge number multiplexing based on the JTC encryption system to achieve multiple-image encryption. Using this method, multi-image can be encrypted into single ciphertext, and the original images can be recovered according to the authority level. The number of encrypted images is increased, moreover, the quality of decrypted images is improved. Results of computer simulation and initial experiment identify the validity of our proposed method.
A new image segmentation method based on multifractal detrended moving average analysis
NASA Astrophysics Data System (ADS)
Shi, Wen; Zou, Rui-biao; Wang, Fang; Su, Le
2015-08-01
In order to segment and delineate some regions of interest in an image, we propose a novel algorithm based on the multifractal detrended moving average analysis (MF-DMA). In this method, the generalized Hurst exponent h(q) is calculated for every pixel firstly and considered as the local feature of a surface. And then a multifractal detrended moving average spectrum (MF-DMS) D(h(q)) is defined by the idea of box-counting dimension method. Therefore, we call the new image segmentation method MF-DMS-based algorithm. The performance of the MF-DMS-based method is tested by two image segmentation experiments of rapeseed leaf image of potassium deficiency and magnesium deficiency under three cases, namely, backward (θ = 0), centered (θ = 0.5) and forward (θ = 1) with different q values. The comparison experiments are conducted between the MF-DMS method and other two multifractal segmentation methods, namely, the popular MFS-based and latest MF-DFS-based methods. The results show that our MF-DMS-based method is superior to the latter two methods. The best segmentation result for the rapeseed leaf image of potassium deficiency and magnesium deficiency is from the same parameter combination of θ = 0.5 and D(h(- 10)) when using the MF-DMS-based method. An interesting finding is that the D(h(- 10)) outperforms other parameters for both the MF-DMS-based method with centered case and MF-DFS-based algorithms. By comparing the multifractal nature between nutrient deficiency and non-nutrient deficiency areas determined by the segmentation results, an important finding is that the gray value's fluctuation in nutrient deficiency area is much severer than that in non-nutrient deficiency area.
a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas
NASA Astrophysics Data System (ADS)
Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.
2015-12-01
In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Smith, William L.; Bingham, Gail E.; Huppi, Ronald J.; Revercomb, Henry E.; Zollinger, Lori J.; Larar, Allen M.; Liu, Xu; Tansock, Joseph J.; Reisse, Robert A.;
2007-01-01
The geosynchronous-imaging Fourier transform spectrometer (GIFTS) engineering demonstration unit (EDU) is an imaging infrared spectrometer designed for atmospheric soundings. It measures the infrared spectrum in two spectral bands (14.6 to 8.8 microns, 6.0 to 4.4 microns) using two 128 x 128 detector arrays with a spectral resolution of 0.57 cm(exp -1) with a scan duration of approximately 11 seconds. From a geosynchronous orbit, the instrument will have the capability of taking successive measurements of such data to scan desired regions of the globe, from which atmospheric status, cloud parameters, wind field profiles, and other derived products can be retrieved. The GIFTS EDU provides a flexible and accurate testbed for the new challenges of the emerging hyperspectral era. The EDU ground-based measurement experiment, held in Logan, Utah during September 2006, demonstrated its extensive capabilities and potential for geosynchronous and other applications (e.g., Earth observing environmental measurements). This paper addresses the experiment objectives and overall performance of the sensor system with a focus on the GIFTS EDU imaging capability and proof of the GIFTS measurement concept.
Short-term solar flare prediction using image-case-based reasoning
NASA Astrophysics Data System (ADS)
Liu, Jin-Fu; Li, Fei; Zhang, Huai-Peng; Yu, Da-Ren
2017-10-01
Solar flares strongly influence space weather and human activities, and their prediction is highly complex. The existing solutions such as data based approaches and model based approaches have a common shortcoming which is the lack of human engagement in the forecasting process. An image-case-based reasoning method is introduced to achieve this goal. The image case library is composed of SOHO/MDI longitudinal magnetograms, the images from which exhibit the maximum horizontal gradient, the length of the neutral line and the number of singular points that are extracted for retrieving similar image cases. Genetic optimization algorithms are employed for optimizing the weight assignment for image features and the number of similar image cases retrieved. Similar image cases and prediction results derived by majority voting for these similar image cases are output and shown to the forecaster in order to integrate his/her experience with the final prediction results. Experimental results demonstrate that the case-based reasoning approach has slightly better performance than other methods, and is more efficient with forecasts improved by humans.
Enhance wound healing monitoring through a thermal imaging based smartphone app
NASA Astrophysics Data System (ADS)
Yi, Steven; Lu, Minta; Yee, Adam; Harmon, John; Meng, Frank; Hinduja, Saurabh
2018-03-01
In this paper, we present a thermal imaging based app to augment traditional appearance based wound growth monitoring. Accurate diagnose and track of wound healing enables physicians to effectively assess, document, and individualize the treatment plan given to each wound patient. Currently, wounds are primarily examined by physicians through visual appearance and wound area. However, visual information alone cannot present a complete picture on a wound's condition. In this paper, we use a smartphone attached thermal imager and evaluate its effectiveness on augmenting visual appearance based wound diagnosis. Instead of only monitoring wound temperature changes on a wound, our app presents physicians a comprehensive measurements including relative temperature, wound healing thermal index, and wound blood flow. Through the rat wound experiments and by monitoring the integrated thermal measurements over 3 weeks of time frame, our app is able to show the underlying healing process through the blood flow. The implied significance of our app design and experiment includes: (a) It is possible to use a low cost smartphone attached thermal imager for added value on wound assessment, tracking, and treatment; and (b) Thermal mobile app can be used for remote wound healing assessment for mobile health based solution.
Fletcher, E; Carmichael, O; Decarli, C
2012-01-01
We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer's disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.
Fletcher, E.; Carmichael, O.; DeCarli, C.
2013-01-01
We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer’s disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions. PMID:23365843
NASA Astrophysics Data System (ADS)
Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.
2014-03-01
We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.
Image Location Estimation by Salient Region Matching.
Qian, Xueming; Zhao, Yisi; Han, Junwei
2015-11-01
Nowadays, locations of images have been widely used in many application scenarios for large geo-tagged image corpora. As to images which are not geographically tagged, we estimate their locations with the help of the large geo-tagged image set by content-based image retrieval. In this paper, we exploit spatial information of useful visual words to improve image location estimation (or content-based image retrieval performances). We proposed to generate visual word groups by mean-shift clustering. To improve the retrieval performance, spatial constraint is utilized to code the relative position of visual words. We proposed to generate a position descriptor for each visual word and build fast indexing structure for visual word groups. Experiments show the effectiveness of our proposed approach.
BCC skin cancer diagnosis based on texture analysis techniques
NASA Astrophysics Data System (ADS)
Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; McKenzie, Frederic D.
2011-03-01
In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.
Compact Microscope Imaging System Developed
NASA Technical Reports Server (NTRS)
McDowell, Mark
2001-01-01
The Compact Microscope Imaging System (CMIS) is a diagnostic tool with intelligent controls for use in space, industrial, medical, and security applications. The CMIS can be used in situ with a minimum amount of user intervention. This system, which was developed at the NASA Glenn Research Center, can scan, find areas of interest, focus, and acquire images automatically. Large numbers of multiple cell experiments require microscopy for in situ observations; this is only feasible with compact microscope systems. CMIS is a miniature machine vision system that combines intelligent image processing with remote control capabilities. The software also has a user-friendly interface that can be used independently of the hardware for post-experiment analysis. CMIS has potential commercial uses in the automated online inspection of precision parts, medical imaging, security industry (examination of currency in automated teller machines and fingerprint identification in secure entry locks), environmental industry (automated examination of soil/water samples), biomedical field (automated blood/cell analysis), and microscopy community. CMIS will improve research in several ways: It will expand the capabilities of MSD experiments utilizing microscope technology. It may be used in lunar and Martian experiments (Rover Robot). Because of its reduced size, it will enable experiments that were not feasible previously. It may be incorporated into existing shuttle orbiter and space station experiments, including glove-box-sized experiments as well as ground-based experiments.
Recent Progress in Optical Biosensors Based on Smartphone Platforms
Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda
2017-01-01
With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms. PMID:29068375
Recent Progress in Optical Biosensors Based on Smartphone Platforms.
Geng, Zhaoxin; Zhang, Xiong; Fan, Zhiyuan; Lv, Xiaoqing; Su, Yue; Chen, Hongda
2017-10-25
With a rapid improvement of smartphone hardware and software, especially complementary metal oxide semiconductor (CMOS) cameras, many optical biosensors based on smartphone platforms have been presented, which have pushed the development of the point-of-care testing (POCT). Imaging-based and spectrometry-based detection techniques have been widely explored via different approaches. Combined with the smartphone, imaging-based and spectrometry-based methods are currently used to investigate a wide range of molecular properties in chemical and biological science for biosensing and diagnostics. Imaging techniques based on smartphone-based microscopes are utilized to capture microscale analysts, while spectrometry-based techniques are used to probe reactions or changes of molecules. Here, we critically review the most recent progress in imaging-based and spectrometry-based smartphone-integrated platforms that have been developed for chemical experiments and biological diagnosis. We focus on the analytical performance and the complexity for implementation of the platforms.
Computer Assisted Thermography And Its Application In Ovulation Detection
NASA Astrophysics Data System (ADS)
Rao, K. H.; Shah, A. V.
1984-08-01
Hardware and software of a computer-assisted image analyzing system used for infrared images in medical applications are discussed. The application of computer-assisted thermography (CAT) as a complementary diagnostic tool in centralized diagnostic management is proposed. The authors adopted 'Computer Assisted Thermography' to study physiological changes in the breasts related to the hormones characterizing the menstrual cycle of a woman. Based on clinical experi-ments followed by thermal image analysis, they suggest that 'differential skin temperature (DST)1 be measured to detect the fertility interval in the menstrual cycle of a woman.
Image Acquisition in Real Time
NASA Technical Reports Server (NTRS)
2003-01-01
In 1995, Carlos Jorquera left NASA s Jet Propulsion Laboratory (JPL) to focus on erasing the growing void between high-performance cameras and the requisite software to capture and process the resulting digital images. Since his departure from NASA, Jorquera s efforts have not only satisfied the private industry's cravings for faster, more flexible, and more favorable software applications, but have blossomed into a successful entrepreneurship that is making its mark with improvements in fields such as medicine, weather forecasting, and X-ray inspection. Formerly a JPL engineer who constructed imaging systems for spacecraft and ground-based astronomy projects, Jorquera is the founder and president of the three-person firm, Boulder Imaging Inc., based in Louisville, Colorado. Joining Jorquera to round out the Boulder Imaging staff are Chief Operations Engineer Susan Downey, who also gained experience at JPL working on space-bound projects including Galileo and the Hubble Space Telescope, and Vice President of Engineering and Machine Vision Specialist Jie Zhu Kulbida, who has extensive industrial and research and development experience within the private sector.
Dabbs, Gretchen R; Bytheway, Joan A; Connor, Melissa
2017-09-01
When in forensic casework or empirical research in-person assessment of human decomposition is not possible, the sensible substitution is color photographic images. To date, no research has confirmed the utility of color photographic images as a proxy for in situ observation of the level of decomposition. Sixteen observers scored photographs of 13 human cadavers in varying decomposition stages (PMI 2-186 days) using the Total Body Score system (total n = 929 observations). The on-site TBS was compared with recorded observations from digital color images using a paired samples t-test. The average difference between on-site and photographic observations was -0.20 (t = -1.679, df = 928, p = 0.094). Individually, only two observers, both students with <1 year of experience, demonstrated TBS statistically significantly different than the on-site value, suggesting that with experience, observations of human decomposition based on digital images can be substituted for assessments based on observation of the corpse in situ, when necessary. © 2017 American Academy of Forensic Sciences.
Similarity analysis between quantum images
NASA Astrophysics Data System (ADS)
Zhou, Ri-Gui; Liu, XingAo; Zhu, Changming; Wei, Lai; Zhang, Xiafen; Ian, Hou
2018-06-01
Similarity analyses between quantum images are so essential in quantum image processing that it provides fundamental research for the other fields, such as quantum image matching, quantum pattern recognition. In this paper, a quantum scheme based on a novel quantum image representation and quantum amplitude amplification algorithm is proposed. At the end of the paper, three examples and simulation experiments show that the measurement result must be 0 when two images are same, and the measurement result has high probability of being 1 when two images are different.
Microfluidics-based, time-resolved mechanical phenotyping of cells using high-speed imaging
NASA Astrophysics Data System (ADS)
Belotti, Yuri; Conneely, Michael; Huang, Tianjun; McKenna, Stephen; Nabi, Ghulam; McGloin, David
2017-07-01
We demonstrate a single channel hydrodynamic stretching microfluidic device that relies on high-speed imaging to allow repeated dynamic cell deformation measurements. Experiments on prostate cancer cells suggest richer data than current approaches.
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.
NASA Technical Reports Server (NTRS)
Urban, D. L.; Yuan, Z.-G.; Sunderland, P. B.; Linteris, G. T.; Voss, J. E.; Lin, K.-C.; Dai, Z.; Sun, K.; Faeth, G. M.; Ross, Howard D. (Technical Monitor)
2001-01-01
The structure and soot properties of round, soot-emitting, nonbuoyant, laminar jet diffusion flames are described, based on long-duration (175-230-s) experiments at microgravity carried out on orbit in the Space Shuttle Columbia. Experimental conditions included ethylene-fueled flames burning in still air at nominal pressures of 50 and 100 kPa and an ambient temperature of 300 K with luminous flame lengths of 49-64 mm Measurements included luminous flame shapes using color video imaging soot concentration (volume fraction) distributions using deconvoluted laser extinction imaging, soot temperature distributions using deconvoluted multiline emission imaging, gas temperature distributions at fuel-lean (plume) conditions using thermocouple probes, soot structure distributions using thermophoretic sampling and analysis by transmission electron microscopy, and flame radiation using a radiometer.The present flames were larger, and emitted soot more readily, than comparable flames observed during ground-based microgravity experiments due to closer approach to steady conditions resulting from the longer test times and the reduced gravitational disturbances of the space-based experiments.
Zhou, Yong; Hu, Ye; Zeng, Nan; Ji, Yanhong; Dai, Xiangsong; Li, Peng; Ma, Hui; He, Yonghong
2011-01-01
We present a noninvasive method of detecting substance concentration in the aqueous humor based on dual-wavelength iris imaging technology. Two light sources, one centered within (392 nm) and the other centered outside (850 nm) of an absorption band of Pirenoxine Sodium, a common type of drugs in eye disease treatment, were used for dual-wavelength iris imaging measurement. After passing through the aqueous humor twice, the back-scattering light was detected by a charge-coupled device (CCD). The detected images were then used to calculate the concentration of Pirenoxine Sodium. In eye model experiment, a resolution of 0.6525 ppm was achieved. Meanwhile, at least 4 ppm can be distinguished in in vivo experiment. These results demonstrated that our method can measure Pirenoxine Sodium concentration in the aqueous humor and its potential ability to monitor other materials’ concentration in the aqueous humor. PMID:21339869
Fine-grained visual marine vessel classification for coastal surveillance and defense applications
NASA Astrophysics Data System (ADS)
Solmaz, Berkan; Gundogdu, Erhan; Karaman, Kaan; Yücesoy, Veysel; Koç, Aykut
2017-10-01
The need for capabilities of automated visual content analysis has substantially increased due to presence of large number of images captured by surveillance cameras. With a focus on development of practical methods for extracting effective visual data representations, deep neural network based representations have received great attention due to their success in visual categorization of generic images. For fine-grained image categorization, a closely related yet a more challenging research problem compared to generic image categorization due to high visual similarities within subgroups, diverse applications were developed such as classifying images of vehicles, birds, food and plants. Here, we propose the use of deep neural network based representations for categorizing and identifying marine vessels for defense and security applications. First, we gather a large number of marine vessel images via online sources grouping them into four coarse categories; naval, civil, commercial and service vessels. Next, we subgroup naval vessels into fine categories such as corvettes, frigates and submarines. For distinguishing images, we extract state-of-the-art deep visual representations and train support-vector-machines. Furthermore, we fine tune deep representations for marine vessel images. Experiments address two scenarios, classification and verification of naval marine vessels. Classification experiment aims coarse categorization, as well as learning models of fine categories. Verification experiment embroils identification of specific naval vessels by revealing if a pair of images belongs to identical marine vessels by the help of learnt deep representations. Obtaining promising performance, we believe these presented capabilities would be essential components of future coastal and on-board surveillance systems.
Yuan, Tiezhu; Wang, Hongqiang; Cheng, Yongqiang; Qin, Yuliang
2017-01-01
Radar imaging based on electromagnetic vortex can achieve azimuth resolution without relative motion. The present paper investigates this imaging technique with the use of a single receiving antenna through theoretical analysis and experimental results. Compared with the use of multiple receiving antennas, the echoes from a single receiver cannot be used directly for image reconstruction using Fourier method. The reason is revealed by using the point spread function. An additional phase is compensated for each mode before imaging process based on the array parameters and the elevation of the targets. A proof-of-concept imaging system based on a circular phased array is created, and imaging experiments of corner-reflector targets are performed in an anechoic chamber. The azimuthal image is reconstructed by the use of Fourier transform and spectral estimation methods. The azimuth resolution of the two methods is analyzed and compared through experimental data. The experimental results verify the principle of azimuth resolution and the proposed phase compensation method. PMID:28335487
Fung, Kar-Ming; Hassell, Lewis A; Talbert, Michael L; Wiechmann, Allan F; Chaser, Brad E; Ramey, Joel
2012-01-01
Examination of glass slides is of paramount importance in pathology training. Until the introduction of digitized whole slide images that could be accessed through computer networks, the sharing of pathology slides was a major logistic issue in pathology education and practice. With the help of whole slide images, our department has developed several online pathology education websites. Based on a modular architecture, this program provides online access to whole slide images, still images, case studies, quizzes and didactic text at different levels. Together with traditional lectures and hands-on experiences, it forms the back bone of our histology and pathology education system for residents and medical students. The use of digitized whole slide images has a.lso greatly improved the communication between clinicians and pathologist in our institute.
Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella
2018-01-17
Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat 'brighter' than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.
NASA Astrophysics Data System (ADS)
Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella
2018-01-01
Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat ‘brighter’ than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.
Speckle-learning-based object recognition through scattering media.
Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun
2015-12-28
We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.
From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.
Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R
2014-10-01
Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.
Floating aerial 3D display based on the freeform-mirror and the improved integral imaging system
NASA Astrophysics Data System (ADS)
Yu, Xunbo; Sang, Xinzhu; Gao, Xin; Yang, Shenwu; Liu, Boyang; Chen, Duo; Yan, Binbin; Yu, Chongxiu
2018-09-01
A floating aerial three-dimensional (3D) display based on the freeform-mirror and the improved integral imaging system is demonstrated. In the traditional integral imaging (II), the distortion originating from lens aberration warps elemental images and degrades the visual effect severely. To correct the distortion of the observed pixels and to improve the image quality, a directional diffuser screen (DDS) is introduced. However, the improved integral imaging system can hardly present realistic images with the large off-screen depth, which limits floating aerial visual experience. To display the 3D image in the free space, the off-axis reflection system with the freeform-mirror is designed. By combining the improved II and the designed freeform optical element, the floating aerial 3D image is presented.
NASA Astrophysics Data System (ADS)
Ba Dinh, Khuong; Le, Hoang Vu; Hannaford, Peter; Van Dao, Lap
2017-08-01
A table-top coherent diffractive imaging experiment on a sample with biological-like characteristics using a focused narrow-bandwidth high harmonic source around 30 nm is performed. An approach involving a beam stop and a new reconstruction algorithm to enhance the quality of reconstructed the image is described.
Yi, Huangjian; Chen, Duofang; Li, Wei; Zhu, Shouping; Wang, Xiaorui; Liang, Jimin; Tian, Jie
2013-05-01
Fluorescence molecular tomography (FMT) is an important imaging technique of optical imaging. The major challenge of the reconstruction method for FMT is the ill-posed and underdetermined nature of the inverse problem. In past years, various regularization methods have been employed for fluorescence target reconstruction. A comparative study between the reconstruction algorithms based on l1-norm and l2-norm for two imaging models of FMT is presented. The first imaging model is adopted by most researchers, where the fluorescent target is of small size to mimic small tissue with fluorescent substance, as demonstrated by the early detection of a tumor. The second model is the reconstruction of distribution of the fluorescent substance in organs, which is essential to drug pharmacokinetics. Apart from numerical experiments, in vivo experiments were conducted on a dual-modality FMT/micro-computed tomography imaging system. The experimental results indicated that l1-norm regularization is more suitable for reconstructing the small fluorescent target, while l2-norm regularization performs better for the reconstruction of the distribution of fluorescent substance.
Ben-Eliezer, Noam; Solomon, Eddy; Harel, Elad; Nevo, Nava; Frydman, Lucio
2012-12-01
An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches. 2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions. In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50 % reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts. The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.
Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.
Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D
2013-05-30
The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.
Beyond where it started: a look at the "Healing Images" experience.
Goodsmith, Lauren
2007-01-01
In March 2004, the Baltimore-based nonprofit organization Advocates for Survivors of Torture and Trauma (ASTT) initiated a photography-based therapeutic programme for clients. Developed by a professional photographer/teacher in collaboration with a psychologist, the programme has the goal of enabling clients to engage in creative self-exploration within a supportive, group setting. Since its inception, thirty survivors of conflict-related trauma and torture from five different countries have taken part in the programme, known as "Healing Images", using digital cameras to gather individually-chosen images that are subsequently shared and discussed within the group. These images include depictions of the natural and manmade environments in which clients find themselves; people, places and objects that offer comfort; and self-portraits that reflect the reality of the life of a refugee in the United States. This description of the "Healing Images" programme is based on comments gathered through discussion with participants and through interviews. Additional information was gathered from observation of early workshop sessions, review of numerous client photographs and captions, and pertinent organizational materials. A fundamental benefit of the programme was that it offered a mutually supportive group environment that diminished clients' feelings of psychological and physical isolation. Participants gained deep satisfaction from learning the technical skills related to use of the cameras, from the empowering experience of framing and creating specific images, and from exploring the personal significance of these images. Programme activities sparked a process of self-expression that participants valued on the level of personal discovery and growth. Some clients also welcomed opportunities to share their work publicly, as a means of raising awareness of the experience of survivors.
Video Extrapolation Method Based on Time-Varying Energy Optimization and CIP.
Sakaino, Hidetomo
2016-09-01
Video extrapolation/prediction methods are often used to synthesize new videos from images. For fluid-like images and dynamic textures as well as moving rigid objects, most state-of-the-art video extrapolation methods use non-physics-based models that learn orthogonal bases from a number of images but at high computation cost. Unfortunately, data truncation can cause image degradation, i.e., blur, artifact, and insufficient motion changes. To extrapolate videos that more strictly follow physical rules, this paper proposes a physics-based method that needs only a few images and is truncation-free. We utilize physics-based equations with image intensity and velocity: optical flow, Navier-Stokes, continuity, and advection equations. These allow us to use partial difference equations to deal with the local image feature changes. Image degradation during extrapolation is minimized by updating model parameters, where a novel time-varying energy balancer model that uses energy based image features, i.e., texture, velocity, and edge. Moreover, the advection equation is discretized by high-order constrained interpolation profile for lower quantization error than can be achieved by the previous finite difference method in long-term videos. Experiments show that the proposed energy based video extrapolation method outperforms the state-of-the-art video extrapolation methods in terms of image quality and computation cost.
A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks
Wang, Changjian; Liu, Xiaohui; Jin, Shiyao
2018-01-01
Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment. PMID:29955227
An Image Encryption Algorithm Based on Information Hiding
NASA Astrophysics Data System (ADS)
Ge, Xin; Lu, Bin; Liu, Fenlin; Gong, Daofu
Aiming at resolving the conflict between security and efficiency in the design of chaotic image encryption algorithms, an image encryption algorithm based on information hiding is proposed based on the “one-time pad” idea. A random parameter is introduced to ensure a different keystream for each encryption, which has the characteristics of “one-time pad”, improving the security of the algorithm rapidly without significant increase in algorithm complexity. The random parameter is embedded into the ciphered image with information hiding technology, which avoids negotiation for its transport and makes the application of the algorithm easier. Algorithm analysis and experiments show that the algorithm is secure against chosen plaintext attack, differential attack and divide-and-conquer attack, and has good statistical properties in ciphered images.
An improved feature extraction algorithm based on KAZE for multi-spectral image
NASA Astrophysics Data System (ADS)
Yang, Jianping; Li, Jun
2018-02-01
Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.
A High Performance Pulsatile Pump for Aortic Flow Experiments in 3-Dimensional Models.
Chaudhury, Rafeed A; Atlasman, Victor; Pathangey, Girish; Pracht, Nicholas; Adrian, Ronald J; Frakes, David H
2016-06-01
Aortic pathologies such as coarctation, dissection, and aneurysm represent a particularly emergent class of cardiovascular diseases. Computational simulations of aortic flows are growing increasingly important as tools for gaining understanding of these pathologies, as well as for planning their surgical repair. In vitro experiments are required to validate the simulations against real world data, and the experiments require a pulsatile flow pump system that can provide physiologic flow conditions characteristic of the aorta. We designed a newly capable piston-based pulsatile flow pump system that can generate high volume flow rates (850 mL/s), replicate physiologic waveforms, and pump high viscosity fluids against large impedances. The system is also compatible with a broad range of fluid types, and is operable in magnetic resonance imaging environments. Performance of the system was validated using image processing-based analysis of piston motion as well as particle image velocimetry. The new system represents a more capable pumping solution for aortic flow experiments than other available designs, and can be manufactured at a relatively low cost.
NASA Astrophysics Data System (ADS)
Luo, S. N.; Jensen, B. J.; Hooks, D. E.; Fezzaa, K.; Ramos, K. J.; Yeager, J. D.; Kwiatkowski, K.; Shimada, T.
2012-07-01
The highly transient nature of shock loading and pronounced microstructure effects on dynamic materials response call for in situ, temporally and spatially resolved, x-ray-based diagnostics. Third-generation synchrotron x-ray sources are advantageous for x-ray phase contrast imaging (PCI) and diffraction under dynamic loading, due to their high photon fluxes, high coherency, and high pulse repetition rates. The feasibility of bulk-scale gas gun shock experiments with dynamic x-ray PCI and diffraction measurements was investigated at the beamline 32ID-B of the Advanced Photon Source. The x-ray beam characteristics, experimental setup, x-ray diagnostics, and static and dynamic test results are described. We demonstrate ultrafast, multiframe, single-pulse PCI measurements with unprecedented temporal (<100 ps) and spatial (˜2 μm) resolutions for bulk-scale shock experiments, as well as single-pulse dynamic Laue diffraction. The results not only substantiate the potential of synchrotron-based experiments for addressing a variety of shock physics problems, but also allow us to identify the technical challenges related to image detection, x-ray source, and dynamic loading.
Remote sensing image denoising application by generalized morphological component analysis
NASA Astrophysics Data System (ADS)
Yu, Chong; Chen, Xiong
2014-12-01
In this paper, we introduced a remote sensing image denoising method based on generalized morphological component analysis (GMCA). This novel algorithm is the further extension of morphological component analysis (MCA) algorithm to the blind source separation framework. The iterative thresholding strategy adopted by GMCA algorithm firstly works on the most significant features in the image, and then progressively incorporates smaller features to finely tune the parameters of whole model. Mathematical analysis of the computational complexity of GMCA algorithm is provided. Several comparison experiments with state-of-the-art denoising algorithms are reported. In order to make quantitative assessment of algorithms in experiments, Peak Signal to Noise Ratio (PSNR) index and Structural Similarity (SSIM) index are calculated to assess the denoising effect from the gray-level fidelity aspect and the structure-level fidelity aspect, respectively. Quantitative analysis on experiment results, which is consistent with the visual effect illustrated by denoised images, has proven that the introduced GMCA algorithm possesses a marvelous remote sensing image denoising effectiveness and ability. It is even hard to distinguish the original noiseless image from the recovered image by adopting GMCA algorithm through visual effect.
NASA Technical Reports Server (NTRS)
1972-01-01
The IDAPS (Image Data Processing System) is a user-oriented, computer-based, language and control system, which provides a framework or standard for implementing image data processing applications, simplifies set-up of image processing runs so that the system may be used without a working knowledge of computer programming or operation, streamlines operation of the image processing facility, and allows multiple applications to be run in sequence without operator interaction. The control system loads the operators, interprets the input, constructs the necessary parameters for each application, and cells the application. The overlay feature of the IBSYS loader (IBLDR) provides the means of running multiple operators which would otherwise overflow core storage.
A spectrum fractal feature classification algorithm for agriculture crops with hyper spectrum image
NASA Astrophysics Data System (ADS)
Su, Junying
2011-11-01
A fractal dimension feature analysis method in spectrum domain for hyper spectrum image is proposed for agriculture crops classification. Firstly, a fractal dimension calculation algorithm in spectrum domain is presented together with the fast fractal dimension value calculation algorithm using the step measurement method. Secondly, the hyper spectrum image classification algorithm and flowchart is presented based on fractal dimension feature analysis in spectrum domain. Finally, the experiment result of the agricultural crops classification with FCL1 hyper spectrum image set with the proposed method and SAM (spectral angle mapper). The experiment results show it can obtain better classification result than the traditional SAM feature analysis which can fulfill use the spectrum information of hyper spectrum image to realize precision agricultural crops classification.
AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING
Sharif, Behzad; Bresler, Yoram
2013-01-01
We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159
NASA Astrophysics Data System (ADS)
Bultreys, Tom; Boone, Marijn A.; Boone, Matthieu N.; De Schryver, Thomas; Masschaele, Bert; Van Hoorebeke, Luc; Cnudde, Veerle
2016-09-01
Over the past decade, the wide-spread implementation of laboratory-based X-ray micro-computed tomography (micro-CT) scanners has revolutionized both the experimental and numerical research on pore-scale transport in geological materials. The availability of these scanners has opened up the possibility to image a rock's pore space in 3D almost routinely to many researchers. While challenges do persist in this field, we treat the next frontier in laboratory-based micro-CT scanning: in-situ, time-resolved imaging of dynamic processes. Extremely fast (even sub-second) micro-CT imaging has become possible at synchrotron facilities over the last few years, however, the restricted accessibility of synchrotrons limits the amount of experiments which can be performed. The much smaller X-ray flux in laboratory-based systems bounds the time resolution which can be attained at these facilities. Nevertheless, progress is being made to improve the quality of measurements performed on the sub-minute time scale. We illustrate this by presenting cutting-edge pore scale experiments visualizing two-phase flow and solute transport in real-time with a lab-based environmental micro-CT set-up. To outline the current state of this young field and its relevance to pore-scale transport research, we critically examine its current bottlenecks and their possible solutions, both on the hardware and the software level. Further developments in laboratory-based, time-resolved imaging could prove greatly beneficial to our understanding of transport behavior in geological materials and to the improvement of pore-scale modeling by providing valuable validation.
Automatic cataloguing and characterization of Earth science data using SE-trees
NASA Technical Reports Server (NTRS)
Rymon, Ron; Short, Nicholas M., Jr.
1994-01-01
In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.
Feasibility study for wax deposition imaging in oil pipelines by PGNAA technique.
Cheng, Can; Jia, Wenbao; Hei, Daqian; Wei, Zhiyong; Wang, Hongtao
2017-10-01
Wax deposition in pipelines is a crucial problem in the oil industry. A method based on the prompt gamma-ray neutron activation analysis technique was applied to reconstruct the image of wax deposition in oil pipelines. The 2.223MeV hydrogen capture gamma rays were used to reconstruct the wax deposition image. To validate the method, both MCNP simulation and experiments were performed for wax deposited with a maximum thickness of 20cm. The performance of the method was simulated using the MCNP code. The experiment was conducted with a 252 Cf neutron source and a LaBr 3 : Ce detector. A good correspondence between the simulations and the experiments was observed. The results obtained indicate that the present approach is efficient for wax deposition imaging in oil pipelines. Copyright © 2017 Elsevier Ltd. All rights reserved.
Advanced Diagnostic System on Earth Observing One
NASA Technical Reports Server (NTRS)
Hayden, Sandra C.; Sweet, Adam J.; Christa, Scott E.; Tran, Daniel; Shulman, Seth
2004-01-01
In this infusion experiment, the Livingstone 2 (L2) model-based diagnosis engine, developed by the Computational Sciences division at NASA Ames Research Center, has been uploaded to the Earth Observing One (EO-1) satellite. L2 is integrated with the Autonomous Sciencecraft Experiment (ASE) which provides an on-board planning capability and a software bridge to the spacecraft's 1773 data bus. Using a model of the spacecraft subsystems, L2 predicts nominal state transitions initiated by control commands, monitors the spacecraft sensors, and, in the case of failure, isolates the fault based on the discrepant observations. Fault detection and isolation is done by determining a set of component modes, including most likely failures, which satisfy the current observations. All mode transitions and diagnoses are telemetered to the ground for analysis. The initial L2 model is scoped to EO-1's imaging instruments and solid state recorder. Diagnostic scenarios for EO-1's nominal imaging timeline are demonstrated by injecting simulated faults on-board the spacecraft. The solid state recorder stores the science images and also hosts: the experiment software. The main objective of the experiment is to mature the L2 technology to Technology Readiness Level (TRL) 7. Experiment results are presented, as well as a discussion of the challenging technical issues encountered. Future extensions may explore coordination with the planner, and model-based ground operations.
NASA Astrophysics Data System (ADS)
Zhou, Yi; Li, Qi
2017-01-01
A dual-axis reflective continuous-wave terahertz (THz) confocal scanning polarization imaging system was adopted. THz polarization imaging experiments on gaps on film and metallic letters "BeLLE" were carried out. Imaging results indicate that the THz polarization imaging is sensitive to the tilted gap or wide flat gap, suggesting the THz polarization imaging is able to detect edges and stains. An image fusion method based on the digital image processing was proposed to ameliorate the imaging quality of metallic letters "BeLLE." Objective and subjective evaluation both prove that this method can improve the imaging quality.
Towards building high performance medical image management system for clinical trials
NASA Astrophysics Data System (ADS)
Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel
2011-03-01
Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Jie; Wang, Xin, E-mail: wangx@tongji.edu.cn, E-mail: mubz@tongji.edu.cn; Zhan, Qi
This paper presents a novel lobster-eye imaging system for X-ray-backscattering inspection. The system was designed by modifying the Schmidt geometry into a treble-lens structure in order to reduce the resolution difference between the vertical and horizontal directions, as indicated by ray-tracing simulations. The lobster-eye X-ray imaging system is capable of operating over a wide range of photon energies up to 100 keV. In addition, the optics of the lobster-eye X-ray imaging system was tested to verify that they meet the requirements. X-ray-backscattering imaging experiments were performed in which T-shaped polymethyl-methacrylate objects were imaged by the lobster-eye X-ray imaging system basedmore » on both the double-lens and treble-lens Schmidt objectives. The results show similar resolution of the treble-lens Schmidt objective in both the vertical and horizontal directions. Moreover, imaging experiments were performed using a second treble-lens Schmidt objective with higher resolution. The results show that for a field of view of over 200 mm and with a 500 mm object distance, this lobster-eye X-ray imaging system based on a treble-lens Schmidt objective offers a spatial resolution of approximately 3 mm.« less
NASA Astrophysics Data System (ADS)
Suzuki, Yuki; Fung, George S. K.; Shen, Zeyang; Otake, Yoshito; Lee, Okkyun; Ciuffo, Luisa; Ashikaga, Hiroshi; Sato, Yoshinobu; Taguchi, Katsuyuki
2017-03-01
Cardiac motion (or functional) analysis has shown promise not only for non-invasive diagnosis of cardiovascular diseases but also for prediction of cardiac future events. Current imaging modalities has limitations that could degrade the accuracy of the analysis indices. In this paper, we present a projection-based motion estimation method for x-ray CT that estimates cardiac motion with high spatio-temporal resolution using projection data and a reference 3D volume image. The experiment using a synthesized digital phantom showed promising results for motion analysis.
A Subdivision-Based Representation for Vector Image Editing.
Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou
2012-11-01
Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.
Chen, Qiang; Chen, Yunhao; Jiang, Weiguo
2016-07-30
In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.
Oetjen, Janina; Lachmund, Delf; Palmer, Andrew; Alexandrov, Theodore; Becker, Michael; Boskamp, Tobias; Maass, Peter
2016-09-01
A standardized workflow for matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging MS) is a prerequisite for the routine use of this promising technology in clinical applications. We present an approach to develop standard operating procedures for MALDI imaging MS sample preparation of formalin-fixed and paraffin-embedded (FFPE) tissue sections based on a novel quantitative measure of dataset quality. To cover many parts of the complex workflow and simultaneously test several parameters, experiments were planned according to a fractional factorial design of experiments (DoE). The effect of ten different experiment parameters was investigated in two distinct DoE sets, each consisting of eight experiments. FFPE rat brain sections were used as standard material because of low biological variance. The mean peak intensity and a recently proposed spatial complexity measure were calculated for a list of 26 predefined peptides obtained by in silico digestion of five different proteins and served as quality criteria. A five-way analysis of variance (ANOVA) was applied on the final scores to retrieve a ranking of experiment parameters with increasing impact on data variance. Graphical abstract MALDI imaging experiments were planned according to fractional factorial design of experiments for the parameters under study. Selected peptide images were evaluated by the chosen quality metric (structure and intensity for a given peak list), and the calculated values were used as an input for the ANOVA. The parameters with the highest impact on the quality were deduced and SOPs recommended.
NASA Astrophysics Data System (ADS)
Solli, Martin; Lenz, Reiner
In this paper we describe how to include high level semantic information, such as aesthetics and emotions, into Content Based Image Retrieval. We present a color-based emotion-related image descriptor that can be used for describing the emotional content of images. The color emotion metric used is derived from psychophysical experiments and based on three variables: activity, weight and heat. It was originally designed for single-colors, but recent research has shown that the same emotion estimates can be applied in the retrieval of multi-colored images. Here we describe a new approach, based on the assumption that perceived color emotions in images are mainly affected by homogenous regions, defined by the emotion metric, and transitions between regions. RGB coordinates are converted to emotion coordinates, and for each emotion channel, statistical measurements of gradient magnitudes within a stack of low-pass filtered images are used for finding interest points corresponding to homogeneous regions and transitions between regions. Emotion characteristics are derived for patches surrounding each interest point, and saved in a bag-of-emotions, that, for instance, can be used for retrieving images based on emotional content.
Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu
2014-03-20
A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.
Experience with Delay-Tolerant Networking from Orbit
NASA Technical Reports Server (NTRS)
Ivancic, W.; Eddy, W. M.; Stewart, D.; Wood, L.; Northam, J.; Jackson, C.
2010-01-01
We describe the first use from space of the Bundle Protocol for Delay-Tolerant Networking (DTN) and lessons learned from experiments made and experience gained with this protocol. The Disaster Monitoring Constellation (DMC), constructed by Surrey Satellite Technology Ltd (SSTL), is a multiple-satellite Earth-imaging low-Earth-orbit sensor network in which recorded image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a disruption-tolerant network. Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is technically advanced in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation s UK-DMC satellite. Earth images are downloaded from the satellites using a custom IP-based high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with the use of DTNRG bundle concepts onboard the UK-DMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. Our practical experience with the first successful use of the DTNRG Bundle Protocol in a space environment gives us insights into the design of the Bundle Protocol and enables us to identify issues that must be addressed before wider deployment of the Bundle Protocol. Published in 2010 by John Wiley & Sons, Ltd. KEY WORDS: Internet; UK-DMC; satellite; Delay-Tolerant Networking (DTN); Bundle Protocol
Research of flaw image collecting and processing technology based on multi-baseline stereo imaging
NASA Astrophysics Data System (ADS)
Yao, Yong; Zhao, Jiguang; Pang, Xiaoyan
2008-03-01
Aiming at the practical situations such as accurate optimal design, complex algorithms and precise technical demands of gun bore flaw image collecting, the design frame of a 3-D image collecting and processing system based on multi-baseline stereo imaging was presented in this paper. This system mainly including computer, electrical control box, stepping motor and CCD camera and it can realize function of image collection, stereo matching, 3-D information reconstruction and after-treatments etc. Proved by theoretical analysis and experiment results, images collected by this system were precise and it can slake efficiently the uncertainty problem produced by universally veins or repeated veins. In the same time, this system has faster measure speed and upper measure precision.
Geng, Xiaonan; Li, Qiang; Tsui, Pohsiang; Wang, Chiaoyin; Liu, Haoli
2013-09-01
To evaluate the reliability of diagnostic ultrasound-based temperature and elasticity imaging during radiofrequency ablation (RFA) through ex vivo experiments. Procine liver samples (n=7) were employed for RFA experiments with exposures of different power intensities (10 and 50w). The RFA process was monitored by a diagnostic ultrasound imager and the information were postoperatively captured for further temperature and elasticity image analysis. Infrared thermometry was concurrently applied to provide temperature change calibration during the RFA process. Results from this study demonstrated that temperature imaging was valid under 10 W RF exposure (r=0.95), but the ablation zone was no longer consistent with the reference infrared temperature distribution under high RF exposures. The elasticity change could well reflect the ablation zone under a 50 W exposure, whereas under low exposures, the thermal lesion could not be well detected due to the limited range of temperature elevation and incomplete tissue necrosis. Diagnostic ultrasound-based temperature and elastography is valid for monitoring thr RFA process. Temperature estimation can well reflect mild-power RF ablation dynamics, whereas the elastic-change estimation can can well predict the tissue necrosis. This study provide advances toward using diagnostic ultrasound to monitor RFA or other thermal-based interventions.
NASA Astrophysics Data System (ADS)
Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.
2012-03-01
C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.
Translational-circular scanning for magneto-acoustic tomography with current injection.
Wang, Shigang; Ma, Ren; Zhang, Shunqi; Yin, Tao; Liu, Zhipeng
2016-01-27
Magneto-acoustic tomography with current injection involves using electrical impedance imaging technology. To explore the potential applications in imaging biological tissue and enhance image quality, a new scan mode for the transducer is proposed that is based on translational and circular scanning to record acoustic signals from sources. An imaging algorithm to analyze these signals is developed in respect to this alternative scanning scheme. Numerical simulations and physical experiments were conducted to evaluate the effectiveness of this scheme. An experiment using a graphite sheet as a tissue-mimicking phantom medium was conducted to verify simulation results. A pulsed voltage signal was applied across the sample, and acoustic signals were recorded as the transducer performed stepped translational or circular scans. The imaging algorithm was used to obtain an acoustic-source image based on the signals. In simulations, the acoustic-source image is correlated with the conductivity at the sample boundaries of the sample, but image results change depending on distance and angular aspect of the transducer. In general, as angle and distance decreases, the image quality improves. Moreover, experimental data confirmed the correlation. The acoustic-source images resulting from the alternative scanning mode has yielded the outline of a phantom medium. This scan mode enables improvements to be made in the sensitivity of the detecting unit and a change to a transducer array that would improve the efficiency and accuracy of acoustic-source images.
Munn, Zachary; Jordan, Zoe
When presenting to an imaging department, the person who is to be imaged is often in a vulnerable state, and out of their comfort zone. It is the role of the medical imaging technician to produce a high quality image and facilitate patient care throughout the imaging process. Qualitative research is necessary to better inform the medical imaging technician and to help them to understand the experience of the person being imaged. Some issues that have been identified in the literature include fear, claustrophobia, dehumanisation, and an uncomfortable or unusual experience. There is now a small but worthwhile qualitative literature base focusing on the patient experience in high technology imaging. There is no current qualitative synthesis of the literature on the patient experience in high technology imaging. It is therefore timely and worthwhile to produce a systematic review to identify and summarise the existent literature exploring the patient experience of high technology imaging. To identify the patient experience of high technology medical imaging. Studies that were of a qualitative design that explored the phenomenon of interest, the patient experience of high technology medical imaging. Participants included anyone who had undergone one of these procedures. The search strategy aimed to find both published and unpublished studies, and was conducted over a period from June - September 2010. No time limits were imposed on this search strategy. A three-step search strategy was utilised in this review. All studies that met the criteria were selected for retrieval. They were then assessed by two independent reviewers for methodological validity prior to inclusion in the review using standardised critical appraisal instruments from the Joanna Briggs Institute Qualitative Assessment and Review Instrument. Data was extracted from papers included in the review using the standardised data extraction tool from the Joanna Briggs Institute Qualitative Assessment and Review Instrument. Research findings were pooled using the Qualitative Assessment and Review Instrument. Following the search and critical appraisal processes, 15 studies were identified that were deemed of suitable quality to be included in the review. From these 15 studies, 127 findings were extracted, forming 33 categories and 11 synthesised findings. These synthesised findings related to the patient experience, the emotions they felt (whether negative or positive), the need for support and information, and highlighted the importance of imaging to the patient. The synthesised findings in this review highlight the diverse, unique and challenging ways in which people experience imaging with MRI and CT scanners. All health professionals involved in imaging need to be aware of the different ways each patient may experience imaging, and provide them with ongoing support and information. The implications for practice are derived directly from the results of the meta-synthesis, and each of the 11 synthesised findings. There is still scope for further high methodological qualitative studies to be conducted in this field, particularly in the field of nuclear medicine imaging and Positron Emission Tomography. Further studies may be conducted in certain patient groups, and in certain age ranges. No studies were found assessing the experience of children undergoing high technology imaging.
Development of a CCD based solar speckle imaging system
NASA Astrophysics Data System (ADS)
Nisenson, Peter; Stachnik, Robert V.; Noyes, Robert W.
1986-02-01
A program to develop software and hardware for the purpose of obtaining high angular resolution images of the solar surface is described. The program included the procurement of a Charge Coupled Devices imaging system; an extensive laboratory and remote site testing of the camera system; the development of a software package for speckle image reconstruction which was eventually installed and tested at the Sacramento Peak Observatory; and experiments of the CCD system (coupled to an image intensifier) for low light level, narrow spectral band solar imaging.
Cui, Yang; Hanley, Luke
2015-06-01
ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.
Cui, Yang; Hanley, Luke
2015-01-01
ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science. PMID:26133872
NASA Astrophysics Data System (ADS)
Cui, Yang; Hanley, Luke
2015-06-01
ChiMS is an open-source data acquisition and control software program written within LabVIEW for high speed imaging and depth profiling mass spectrometers. ChiMS can also transfer large datasets from a digitizer to computer memory at high repetition rate, save data to hard disk at high throughput, and perform high speed data processing. The data acquisition mode generally simulates a digital oscilloscope, but with peripheral devices integrated for control as well as advanced data sorting and processing capabilities. Customized user-designed experiments can be easily written based on several included templates. ChiMS is additionally well suited to non-laser based mass spectrometers imaging and various other experiments in laser physics, physical chemistry, and surface science.
NASA Astrophysics Data System (ADS)
Chen, Hao; Zhang, Xinggan; Bai, Yechao; Tang, Lan
2017-01-01
In inverse synthetic aperture radar (ISAR) imaging, the migration through resolution cells (MTRCs) will occur when the rotation angle of the moving target is large, thereby degrading image resolution. To solve this problem, an ISAR imaging method based on segmented preprocessing is proposed. In this method, the echoes of large rotating target are divided into several small segments, and every segment can generate a low-resolution image without MTRCs. Then, each low-resolution image is rotated back to the original position. After image registration and phase compensation, a high-resolution image can be obtained. Simulation and real experiments show that the proposed algorithm can deal with the radar system with different range and cross-range resolutions and significantly compensate the MTRCs.
Chen, Zhaoxue; Chen, Hao
2014-01-01
A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.
Fast Acquisition and Reconstruction of Optical Coherence Tomography Images via Sparse Representation
Li, Shutao; McNabb, Ryan P.; Nie, Qing; Kuo, Anthony N.; Toth, Cynthia A.; Izatt, Joseph A.; Farsiu, Sina
2014-01-01
In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods. PMID:23846467
Image-based diagnostic aid for interstitial lung disease with secondary data integration
NASA Astrophysics Data System (ADS)
Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine
2007-03-01
Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns. These features show good discriminative properties for the separation of five classes of visual observations.
An adaptive block-based fusion method with LUE-SSIM for multi-focus images
NASA Astrophysics Data System (ADS)
Zheng, Jianing; Guo, Yongcai; Huang, Yukun
2016-09-01
Because of the lenses' limited depth of field, digital cameras are incapable of acquiring an all-in-focus image of objects at varying distances in a scene. Multi-focus image fusion technique can effectively solve this problem. Aiming at the block-based multi-focus image fusion methods, the problem that blocking-artifacts often occurs. An Adaptive block-based fusion method based on lifting undistorted-edge structural similarity (LUE-SSIM) is put forward. In this method, image quality metrics LUE-SSIM is firstly proposed, which utilizes the characteristics of human visual system (HVS) and structural similarity (SSIM) to make the metrics consistent with the human visual perception. Particle swarm optimization(PSO) algorithm which selects LUE-SSIM as the object function is used for optimizing the block size to construct the fused image. Experimental results on LIVE image database shows that LUE-SSIM outperform SSIM on Gaussian defocus blur images quality assessment. Besides, multi-focus image fusion experiment is carried out to verify our proposed image fusion method in terms of visual and quantitative evaluation. The results show that the proposed method performs better than some other block-based methods, especially in reducing the blocking-artifact of the fused image. And our method can effectively preserve the undistorted-edge details in focus region of the source images.
Medical Image Authentication Using DPT Watermarking: A Preliminary Attempt
NASA Astrophysics Data System (ADS)
Wong, M. L. Dennis; Goh, Antionette W.-T.; Chua, Hong Siang
Secure authentication of digital medical image content provides great value to the e-Health community and medical insurance industries. Fragile Watermarking has been proposed to provide the mechanism to authenticate digital medical image securely. Transform Domain based Watermarking are typically slower than spatial domain watermarking owing to the overhead in calculation of coefficients. In this paper, we propose a new Discrete Pascal Transform based watermarking technique. Preliminary experiment result shows authentication capability. Possible improvements on the proposed scheme are also presented before conclusions.
Advanced image based methods for structural integrity monitoring: Review and prospects
NASA Astrophysics Data System (ADS)
Farahani, Behzad V.; Sousa, Pedro José; Barros, Francisco; Tavares, Paulo J.; Moreira, Pedro M. G. P.
2018-02-01
There is a growing trend in engineering to develop methods for structural integrity monitoring and characterization of in-service mechanical behaviour of components. The fast growth in recent years of image processing techniques and image-based sensing for experimental mechanics, brought about a paradigm change in phenomena sensing. Hence, several widely applicable optical approaches are playing a significant role in support of experiment. The current review manuscript describes advanced image based methods for structural integrity monitoring, and focuses on methods such as Digital Image Correlation (DIC), Thermoelastic Stress Analysis (TSA), Electronic Speckle Pattern Interferometry (ESPI) and Speckle Pattern Shearing Interferometry (Shearography). These non-contact full-field techniques rely on intensive image processing methods to measure mechanical behaviour, and evolve even as reviews such as this are being written, which justifies a special effort to keep abreast of this progress.
Experimental teaching and training system based on volume holographic storage
NASA Astrophysics Data System (ADS)
Jiang, Zhuqing; Wang, Zhe; Sun, Chan; Cui, Yutong; Wan, Yuhong; Zou, Rufei
2017-08-01
The experiment of volume holographic storage for teaching and training the practical ability of senior students in Applied Physics is introduced. The students can learn to use advanced optoelectronic devices and the automatic control means via this experiment, and further understand the theoretical knowledge of optical information processing and photonics disciplines that have been studied in some courses. In the experiment, multiplexing holographic recording and readout is based on Bragg selectivity of volume holographic grating, in which Bragg diffraction angle is dependent on grating-recording angel. By using different interference angle between reference and object beams, the holograms can be recorded into photorefractive crystal, and then the object images can be read out from these holograms via angular addressing by using the original reference beam. In this system, the experimental data acquisition and the control of the optoelectronic devices, such as the shutter on-off, image loaded in SLM and image acquisition of a CCD sensor, are automatically realized by using LabVIEW programming.
Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) Level 1B2 V006 Announcement
Atmospheric Science Data Center
2018-05-22
The NASA Langley Atmospheric Science Data Center (ASDC) and Jet Propulsion Laboratory (JPL) announce the public ... SpectroPolarimetric Imager (AirMSPI) Level 1B2 V006 data for all targets acquired for flight campaigns: Radar Definition ... Experiment (RADEX) flight campaign was based out of Joint Base Lewis-McChord, Washington. The campaign focused on characterizing new ...
Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R
2015-10-01
This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.
Neumann, M; Breton, E; Cuvillon, L; Pan, L; Lorenz, C H; de Mathelin, M
2012-01-01
In this paper, an original workflow is presented for MR image plane alignment based on tracking in real-time MR images. A test device consisting of two resonant micro-coils and a passive marker is proposed for detection using image-based algorithms. Micro-coils allow for automated initialization of the object detection in dedicated low flip angle projection images; then the passive marker is tracked in clinical real-time MR images, with alternation between two oblique orthogonal image planes along the test device axis; in case the passive marker is lost in real-time images, the workflow is reinitialized. The proposed workflow was designed to minimize dedicated acquisition time to a single dedicated acquisition in the ideal case (no reinitialization required). First experiments have shown promising results for test-device tracking precision, with a mean position error of 0.79 mm and a mean orientation error of 0.24°.
Rahman, Md. Mahmudur; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.
2015-01-01
Abstract. This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature. PMID:26730398
NASA Astrophysics Data System (ADS)
Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong
2017-12-01
Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.
How to Design and Present Texts to Cultivate Balanced Regional Images in Geography Education
ERIC Educational Resources Information Center
Lee, Dong-Min; Ryu, Jaemyong
2013-01-01
This article examines possibilities associated with the cultivation of balanced regional images via the use of simple methods. Two experiments based on the primacy effect and the painting picture rule, or visual depiction of regions, were conducted. The results show significant differences in the formation of regional images. More specifically,…
Fung, Kar-Ming; Hassell, Lewis A.; Talbert, Michael L.; Wiechmann, Allan F.; Chaser, Brad E.; Ramey, Joel
2012-01-01
Examination of glass slides is of paramount importance in pathology training. Until the introduction of digitized whole slide images that could be accessed through computer networks, the sharing of pathology slides was a major logistic issue in pathology education and practice. With the help of whole slide images, our department has developed several online pathology education websites. Based on a modular architecture, this program provides online access to whole slide images, still images, case studies, quizzes and didactic text at different levels. Together with traditional lectures and hands-on experiences, it forms the back bone of our histology and pathology education system for residents and medical students. The use of digitized whole slide images has a.lso greatly improved the communication between clinicians and pathologist in our institute. PMID:21965282
Robust image matching via ORB feature and VFC for mismatch removal
NASA Astrophysics Data System (ADS)
Ma, Tao; Fu, Wenxing; Fang, Bin; Hu, Fangyu; Quan, Siwen; Ma, Jie
2018-03-01
Image matching is at the base of many image processing and computer vision problems, such as object recognition or structure from motion. Current methods rely on good feature descriptors and mismatch removal strategies for detection and matching. In this paper, we proposed a robust image match approach based on ORB feature and VFC for mismatch removal. ORB (Oriented FAST and Rotated BRIEF) is an outstanding feature, it has the same performance as SIFT with lower cost. VFC (Vector Field Consensus) is a state-of-the-art mismatch removing method. The experiment results demonstrate that our method is efficient and robust.
Dückelmann, A M; Bamberg, C; Michaelis, S A M; Lange, J; Nonnenmacher, A; Dudenhausen, J W; Kalache, K D
2010-02-01
To assess whether ultrasound experience or fetal head station affects the reliability of measurement of fetal head descent using the angle of progression on intrapartum ultrasound images obtained by a single experienced operator, and to determine reliability of measurements when images were acquired by different operators with variable ultrasound experience. One experienced obstetrician performed 44 transperineal ultrasound examinations of women at term and in prolonged second stage of labor with the fetus in the occipitoanterior position. Three midwives without ultrasound experience, three obstetricians with < 5 years' experience and three obstetricians with > 10 years' experience measured fetal head descent based on the angle of progression in the images obtained. The angle of progression was measured by two obstetricians in independent ultrasound examinations of 24 laboring women at term with the fetus in the cephalic position to allow assessment of the reliability of image acquisition. Intraclass correlation coefficients (ICCs) with 95% confidence interval (CI) were used to evaluate interobserver reliability and Bland-Altman analysis was used to assess interobserver agreement. In total, 444 measurements were performed and compared. Interobserver reliability with respect to offline image analysis was substantial (overall ICC, 0.72; 95% CI, 0.63-0.81). ICCs were 0.82 (95% CI, 0.70-0.89), 0.81 (95% CI, 0.71-0.88) and 0.61 (95% CI, 0.43-074) for observers with > 10 years', < 5 years' and no ultrasound experience, respectively. There were no significant differences between ICCs among observer groups according to ultrasound experience. Fetal head station did not affect reliability. Bland-Altman analysis indicated reasonable agreement between measurements obtained by two different operators with > 10 years' and < 5 years' ultrasound experience (bias, -1.09 degrees ; 95% limits of agreement, -8.76 to 6.58). The reliability of measurement of the angle of progression following separate image acquisition by two experienced operators was similar to the reliability of offline image analysis (ICC, 0.86; 95% CI, 0.70-0.93). Measurement of the angle of progression on transperineal ultrasound imaging is reliable regardless of fetal head station or the clinician's level of ultrasound experience.
Adaptive polarization image fusion based on regional energy dynamic weighted average
NASA Astrophysics Data System (ADS)
Zhao, Yong-Qiang; Pan, Quan; Zhang, Hong-Cai
2005-11-01
According to the principle of polarization imaging and the relation between Stokes parameters and the degree of linear polarization, there are much redundant and complementary information in polarized images. Since man-made objects and natural objects can be easily distinguished in images of degree of linear polarization and images of Stokes parameters contain rich detailed information of the scene, the clutters in the images can be removed efficiently while the detailed information can be maintained by combining these images. An algorithm of adaptive polarization image fusion based on regional energy dynamic weighted average is proposed in this paper to combine these images. Through an experiment and simulations, most clutters are removed by this algorithm. The fusion method is used for different light conditions in simulation, and the influence of lighting conditions on the fusion results is analyzed.
An improved three-dimensional non-scanning laser imaging system based on digital micromirror device
NASA Astrophysics Data System (ADS)
Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.
2018-01-01
Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.
Development of a Machine-Vision System for Recording of Force Calibration Data
NASA Astrophysics Data System (ADS)
Heamawatanachai, Sumet; Chaemthet, Kittipong; Changpan, Tawat
This paper presents the development of a new system for recording of force calibration data using machine vision technology. Real time camera and computer system were used to capture images of the reading from the instruments during calibration. Then, the measurement images were transformed and translated to numerical data using optical character recognition (OCR) technique. These numerical data along with raw images were automatically saved to memories as the calibration database files. With this new system, the human error of recording would be eliminated. The verification experiments were done by using this system for recording the measurement results from an amplifier (DMP 40) with load cell (HBM-Z30-10kN). The NIMT's 100-kN deadweight force standard machine (DWM-100kN) was used to generate test forces. The experiments setup were done in 3 categories; 1) dynamics condition (record during load changing), 2) statics condition (record during fix load), and 3) full calibration experiments in accordance with ISO 376:2011. The captured images from dynamics condition experiment gave >94% without overlapping of number. The results from statics condition experiment were >98% images without overlapping. All measurement images without overlapping were translated to number by the developed program with 100% accuracy. The full calibration experiments also gave 100% accurate results. Moreover, in case of incorrect translation of any result, it is also possible to trace back to the raw calibration image to check and correct it. Therefore, this machine-vision-based system and program should be appropriate for recording of force calibration data.
Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage
NASA Astrophysics Data System (ADS)
Liu, Tianshuai; Rong, Junyan; Gao, Peng; Zhang, Wenli; Liu, Wenlei; Zhang, Yuanke; Lu, Hongbing
2018-02-01
With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process. To improve the imaging quality of CB-XLCT, an imaging model that adopts an excitation model of nanophosphors based on x-ray absorption dosage is proposed in this study. To solve the ill-posed inverse problem, a reconstruction algorithm that combines the adaptive Tikhonov regularization method with the imaging model is implemented for CB-XLCT reconstruction. Numerical simulations and phantom experiments indicate that compared with the traditional forward model based on x-ray intensity, the proposed dose-based model could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy, and image contrast. In addition, the proposed model behaves better in distinguishing closer targets, demonstrating its advantage in improving spatial resolution.
Disparity modification in stereoscopic images for emotional enhancement
NASA Astrophysics Data System (ADS)
Kawai, Takashi; Atsuta, Daiki; Kim, Sanghyun; Häkkinen, Jukka
2015-03-01
This paper describes an experiment that focuses on disparity changes in emotional scenes of stereoscopic (3D) images, in which an examination of the effects on pleasant and arousal was carried out by adding binocular disparity to 2D images that evoke specific emotions, and applying disparity modification based on the disparity analysis of prominent 3D movies. From the results of the experiment, it was found that pleasant and arousal was increased by expanding 3D space to a certain level. In addition, pleasant gradually decreased and arousal gradually increased by expansion of 3D space above a certain level.
Chen, C; Li, H; Zhou, X; Wong, S T C
2008-05-01
Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.
[Research on fast implementation method of image Gaussian RBF interpolation based on CUDA].
Chen, Hao; Yu, Haizhong
2014-04-01
Image interpolation is often required during medical image processing and analysis. Although interpolation method based on Gaussian radial basis function (GRBF) has high precision, the long calculation time still limits its application in field of image interpolation. To overcome this problem, a method of two-dimensional and three-dimensional medical image GRBF interpolation based on computing unified device architecture (CUDA) is proposed in this paper. According to single instruction multiple threads (SIMT) executive model of CUDA, various optimizing measures such as coalesced access and shared memory are adopted in this study. To eliminate the edge distortion of image interpolation, natural suture algorithm is utilized in overlapping regions while adopting data space strategy of separating 2D images into blocks or dividing 3D images into sub-volumes. Keeping a high interpolation precision, the 2D and 3D medical image GRBF interpolation achieved great acceleration in each basic computing step. The experiments showed that the operative efficiency of image GRBF interpolation based on CUDA platform was obviously improved compared with CPU calculation. The present method is of a considerable reference value in the application field of image interpolation.
Klepacz, Naomi A; Nash, Robert A; Egan, M Bernadette; Hodgkins, Charo E; Raats, Monique M
2016-08-01
Images on food and dietary supplement packaging might lead people to infer (appropriately or inappropriately) certain health benefits of those products. Research on this issue largely involves direct questions, which could (a) elicit inferences that would not be made unprompted, and (b) fail to capture inferences made implicitly. Using a novel memory-based method, in the present research, we explored whether packaging imagery elicits health inferences without prompting, and the extent to which these inferences are made implicitly. In 3 experiments, participants saw fictional product packages accompanied by written claims. Some packages contained an image that implied a health-related function (e.g., a brain), and some contained no image. Participants studied these packages and claims, and subsequently their memory for seen and unseen claims were tested. When a health image was featured on a package, participants often subsequently recognized health claims that-despite being implied by the image-were not truly presented. In Experiment 2, these recognition errors persisted despite an explicit warning against treating the images as informative. In Experiment 3, these findings were replicated in a large consumer sample from 5 European countries, and with a cued-recall test. These findings confirm that images can act as health claims, by leading people to infer health benefits without prompting. These inferences appear often to be implicit, and could therefore be highly pervasive. The data underscore the importance of regulating imagery on product packaging; memory-based methods represent innovative ways to measure how leading (or misleading) specific images can be. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
a Probability-Based Statistical Method to Extract Water Body of TM Images with Missing Information
NASA Astrophysics Data System (ADS)
Lian, Shizhong; Chen, Jiangping; Luo, Minghai
2016-06-01
Water information cannot be accurately extracted using TM images because true information is lost in some images because of blocking clouds and missing data stripes, thereby water information cannot be accurately extracted. Water is continuously distributed in natural conditions; thus, this paper proposed a new method of water body extraction based on probability statistics to improve the accuracy of water information extraction of TM images with missing information. Different disturbing information of clouds and missing data stripes are simulated. Water information is extracted using global histogram matching, local histogram matching, and the probability-based statistical method in the simulated images. Experiments show that smaller Areal Error and higher Boundary Recall can be obtained using this method compared with the conventional methods.
Image annotation based on positive-negative instances learning
NASA Astrophysics Data System (ADS)
Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping
2017-07-01
Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.
NASA Astrophysics Data System (ADS)
Gabai, Haniel; Baranes-Zeevi, Maya; Zilberman, Meital; Shaked, Natan T.
2013-04-01
We propose an off-axis interferometric imaging system as a simple and unique modality for continuous, non-contact and non-invasive wide-field imaging and characterization of drug release from its polymeric device used in biomedicine. In contrast to the current gold-standard methods in this field, usually based on chromatographic and spectroscopic techniques, our method requires no user intervention during the experiment, and only one test-tube is prepared. We experimentally demonstrate imaging and characterization of drug release from soy-based protein matrix, used as skin equivalent for wound dressing with controlled anesthetic, Bupivacaine drug release. Our preliminary results demonstrate the high potential of our method as a simple and low-cost modality for wide-field imaging and characterization of drug release from drug delivery devices.
New segmentation-based tone mapping algorithm for high dynamic range image
NASA Astrophysics Data System (ADS)
Duan, Weiwei; Guo, Huinan; Zhou, Zuofeng; Huang, Huimin; Cao, Jianzhong
2017-07-01
The traditional tone mapping algorithm for the display of high dynamic range (HDR) image has the drawback of losing the impression of brightness, contrast and color information. To overcome this phenomenon, we propose a new tone mapping algorithm based on dividing the image into different exposure regions in this paper. Firstly, the over-exposure region is determined using the Local Binary Pattern information of HDR image. Then, based on the peak and average gray of the histogram, the under-exposure and normal-exposure region of HDR image are selected separately. Finally, the different exposure regions are mapped by differentiated tone mapping methods to get the final result. The experiment results show that the proposed algorithm achieve the better performance both in visual quality and objective contrast criterion than other algorithms.
Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao
2017-01-01
To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181
Gloss uniformity measurement update for ISO/IEC 19751
NASA Astrophysics Data System (ADS)
Ng, Yee S.; Cui, Chengwu; Kuo, Chunghui; Maggard, Eric; Mashtare, Dale; Morris, Peter
2005-01-01
To address the standardization issues of perceptually based image quality for printing systems, ISO/IEC JTC1/SC28, the standardization committee for office equipment chartered the W1.1 project with the responsibility of drafting a proposal for an international standard for the evaluation of printed image quality1. An ISO draft Standard2, ISO/WD 19751-1, Office Equipment - Appearance-based image quality standards for printers - Part 1: Overview, Procedure and Common Methods, 2004 describes the overview of this multi-part appearance-based image quality standard. One of the ISO 19751 multi-part Standard"s tasks is to address the appearance-based gloss and gloss uniformity issues (in ISO 19751-2). This paper summarizes the current status and technical progress since the last two updates3, 4. In particular, we will be discussion our attempt to include 75 degree gloss (G75) objective measurement5 in differential gloss and within-page gloss uniformity. The result for a round-robin experiment involving objective measurement of differential gloss using G60 and G75 gloss measurement geometry is described. The results for two perceptual-based round-robin experiments relating to haze effect on the perception of gloss, and gloss artifacts (gloss streaks/bands, gloss graininess/mottle) are discussed.
Gloss uniformity measurement update for ISO/IEC 19751
NASA Astrophysics Data System (ADS)
Ng, Yee S.; Cui, Chengwu; Kuo, Chunghui; Maggard, Eric; Mashtare, Dale; Morris, Peter
2004-10-01
To address the standardization issues of perceptually based image quality for printing systems, ISO/IEC JTC1/SC28, the standardization committee for office equipment chartered the W1.1 project with the responsibility of drafting a proposal for an international standard for the evaluation of printed image quality1. An ISO draft Standard2, ISO/WD 19751-1, Office Equipment - Appearance-based image quality standards for printers - Part 1: Overview, Procedure and Common Methods, 2004 describes the overview of this multi-part appearance-based image quality standard. One of the ISO 19751 multi-part Standard"s tasks is to address the appearance-based gloss and gloss uniformity issues (in ISO 19751-2). This paper summarizes the current status and technical progress since the last two updates3, 4. In particular, we will be discussion our attempt to include 75 degree gloss (G75) objective measurement5 in differential gloss and within-page gloss uniformity. The result for a round-robin experiment involving objective measurement of differential gloss using G60 and G75 gloss measurement geometry is described. The results for two perceptual-based round-robin experiments relating to haze effect on the perception of gloss, and gloss artifacts (gloss streaks/bands, gloss graininess/mottle) are discussed.
Experiment research on infrared targets signature in mid and long IR spectral bands
NASA Astrophysics Data System (ADS)
Wang, Chensheng; Hong, Pu; Lei, Bo; Yue, Song; Zhang, Zhijie; Ren, Tingting
2013-09-01
Since the infrared imaging system has played a significant role in the military self-defense system and fire control system, the radiation signature of IR target becomes an important topic in IR imaging application technology. IR target signature can be applied in target identification, especially for small and dim targets, as well as the target IR thermal design. To research and analyze the targets IR signature systematically, a practical and experimental project is processed under different backgrounds and conditions. An infrared radiation acquisition system based on a MWIR cooled thermal imager and a LWIR cooled thermal imager is developed to capture the digital infrared images. Furthermore, some instruments are introduced to provide other parameters. According to the original image data and the related parameters in a certain scene, the IR signature of interested target scene can be calculated. Different background and targets are measured with this approach, and a comparison experiment analysis shall be presented in this paper as an example. This practical experiment has proved the validation of this research work, and it is useful in detection performance evaluation and further target identification research.
Adaptive Optical System for Retina Imaging Approaches Clinic Applications
NASA Astrophysics Data System (ADS)
Ling, N.; Zhang, Y.; Rao, X.; Wang, C.; Hu, Y.; Jiang, W.; Jiang, C.
We presented "A small adaptive optical system on table for human retinal imaging" at the 3rd Workshop on Adaptive Optics for Industry and Medicine. In this system, a 19 element small deformable mirror was used as wavefront correction element. High resolution images of photo receptors and capillaries of human retina were obtained. In recent two years, at the base of this system a new adaptive optical system for human retina imaging has been developed. The wavefront correction element is a newly developed 37 element deformable mirror. Some modifications have been adopted for easy operation. Experiments for different imaging wavelengths and axial positions were conducted. Mosaic pictures of photoreceptors and capillaries were obtained. 100 normal and abnormal eyes of different ages have been inspected.The first report in the world concerning the most detailed capillary distribution images cover ±3° by ± 3° field around the fovea has been demonstrated. Some preliminary very early diagnosis experiment has been tried in laboratory. This system is being planned to move to the hospital for clinic experiments.
Fuzzy Matching Based on Gray-scale Difference for Quantum Images
NASA Astrophysics Data System (ADS)
Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia
2018-05-01
Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.
Wavefront sensorless adaptive optics ophthalmoscopy in the human eye
Hofer, Heidi; Sredar, Nripun; Queener, Hope; Li, Chaohong; Porter, Jason
2011-01-01
Wavefront sensor noise and fidelity place a fundamental limit on achievable image quality in current adaptive optics ophthalmoscopes. Additionally, the wavefront sensor ‘beacon’ can interfere with visual experiments. We demonstrate real-time (25 Hz), wavefront sensorless adaptive optics imaging in the living human eye with image quality rivaling that of wavefront sensor based control in the same system. A stochastic parallel gradient descent algorithm directly optimized the mean intensity in retinal image frames acquired with a confocal adaptive optics scanning laser ophthalmoscope (AOSLO). When imaging through natural, undilated pupils, both control methods resulted in comparable mean image intensities. However, when imaging through dilated pupils, image intensity was generally higher following wavefront sensor-based control. Despite the typically reduced intensity, image contrast was higher, on average, with sensorless control. Wavefront sensorless control is a viable option for imaging the living human eye and future refinements of this technique may result in even greater optical gains. PMID:21934779
A learning tool for optical and microwave satellite image processing and analysis
NASA Astrophysics Data System (ADS)
Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.
2016-04-01
This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.
Image-guided ex-vivo targeting accuracy using a laparoscopic tissue localization system
NASA Astrophysics Data System (ADS)
Bieszczad, Jerry; Friets, Eric; Knaus, Darin; Rauth, Thomas; Herline, Alan; Miga, Michael; Galloway, Robert; Kynor, David
2007-03-01
In image-guided surgery, discrete fiducials are used to determine a spatial registration between the location of surgical tools in the operating theater and the location of targeted subsurface lesions and critical anatomic features depicted in preoperative tomographic image data. However, the lack of readily localized anatomic landmarks has greatly hindered the use of image-guided surgery in minimally invasive abdominal procedures. To address these needs, we have previously described a laser-based system for localization of internal surface anatomy using conventional laparoscopes. During a procedure, this system generates a digitized, three-dimensional representation of visible anatomic surfaces in the abdominal cavity. This paper presents the results of an experiment utilizing an ex-vivo bovine liver to assess subsurface targeting accuracy achieved using our system. During the experiment, several radiopaque targets were inserted into the liver parenchyma. The location of each target was recorded using an optically-tracked insertion probe. The liver surface was digitized using our system, and registered with the liver surface extracted from post-procedure CT images. This surface-based registration was then used to transform the position of the inserted targets into the CT image volume. The target registration error (TRE) achieved using our surface-based registration (given a suitable registration algorithm initialization) was 2.4 mm +/- 1.0 mm. A comparable TRE (2.6 mm +/- 1.7 mm) was obtained using a registration based on traditional fiducial markers placed on the surface of the same liver. These results indicate the potential of fiducial-free, surface-to-surface registration for image-guided lesion targeting in minimally invasive abdominal surgery.
Celler, Anna; Piwowarska-Bilska, Hanna; Shcherbinin, Sergey; Uribe, Carlos; Mikolajczak, Renata; Birkenfeld, Bozena
2014-01-01
Dead-time (DT) effects rarely cause problems in diagnostic single-photon emission computed tomography (SPECT) studies; however, in post-radionuclide-therapy imaging, DT can be substantial. Therefore, corrections may be necessary if quantitative images are used in image-based dosimetry or for evaluation of therapy outcomes. This task is particularly challenging if low-energy collimators are used. Our goal was to design a simple method to determine the dead-time correction factor (DTCF) without the need for phantom experiments and complex calculations. Planar and SPECT/CT scans of a water phantom containing a 70 ml bottle filled with lutetium-177 (Lu) were acquired over 60 days. Two small Lu markers were used in all scans. The DTCF based on the ratio of observed to true count rates measured over the entire spectrum and using photopeak primary photons only was estimated for phantom (DT present) and marker (no DT) scans. In addition, variations in counts in SPECT projections (potentially caused by varying bremsstrahlung and scatter) were investigated. For count rates that were about two-fold higher than typically seen in post-therapy Lu scans, the maximum DTCF reached a level of about 17%. The DTCF values determined directly from the phantom experiments using the total energy spectrum and photopeak counts only were equal to 13 and 16%, respectively. They were closely matched by those from the proposed marker-based method, which uses only two energy windows and measures photopeak primary photons (15-17%). A simple, marker-based method allowing for determination of the DTCF in high-activity Lu imaging studies has been proposed and validated using phantom experiments.
Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng
2015-07-28
Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.
Coronagraphic Imaging of Debris Disks from a High Altitude Balloon Platform
NASA Technical Reports Server (NTRS)
Unwin, Stephen; Traub, Wesley; Bryden, Geoffrey; Brugarolas, Paul; Chen, Pin; Guyon, Olivier; Hillenbrand, Lynne; Kasdin, Jeremy; Krist, John; Macintosh, Bruce;
2012-01-01
Debris disks around nearby stars are tracers of the planet formation process, and they are a key element of our understanding of the formation and evolution of extrasolar planetary systems. With multi-color images of a significant number of disks, we can probe important questions: can we learn about planetary system evolution; what materials are the disks made of; and can they reveal the presence of planets? Most disks are known to exist only through their infrared flux excesses as measured by the Spitzer Space Telescope, and through images measured by Herschel. The brightest, most extended disks have been imaged with HST, and a few, such as Fomalhaut, can be observed using ground-based telescopes. But the number of good images is still very small, and there are none of disks with densities as low as the disk associated with the asteroid belt and Edgeworth-Kuiper belt in our own Solar System. Direct imaging of disks is a major observational challenge, demanding high angular resolution and extremely high dynamic range close to the parent star. The ultimate experiment requires a space-based platform, but demonstrating much of the needed technology, mitigating the technical risks of a space-based coronagrap, and performing valuable measurements of circumstellar debris disks, can be done from a high-altitude balloon platform. In this paper we present a balloon-borne telescope experiment based on the Zodiac II design that would undertake compelling studies of a sample of debris disks.
Determination of skeleton and sign map for phase obtaining from a single ESPI image
NASA Astrophysics Data System (ADS)
Yang, Xia; Yu, Qifeng; Fu, Sihua
2009-06-01
A robust method of determining the sign map and skeletons for ESPI images is introduced in this paper. ESPI images have high speckle noise which makes it difficult to obtain the fringe information, especially from a single image. To overcome the effects of high speckle noise, local directional computing windows are designed according to the fringe directions. Then by calculating the gradients from the filtered image in directional windows, sign map and good skeletons can be determined robustly. Based on the sign map, single image phase-extracting methods such as quadrature transform can be improved. And based on skeletons, fringe phases can be obtained directly by normalization methods. Experiments show that this new method is robust and effective for extracting phase from a single ESPI fringe image.
Wörz, Stefan; Rohr, Karl
2006-01-01
We introduce an elastic registration approach which is based on a physical deformation model and uses Gaussian elastic body splines (GEBS). We formulate an extended energy functional related to the Navier equation under Gaussian forces which also includes landmark localization uncertainties. These uncertainties are characterized by weight matrices representing anisotropic errors. Since the approach is based on a physical deformation model, cross-effects in elastic deformations can be taken into account. Moreover, we have a free parameter to control the locality of the transformation for improved registration of local geometric image differences. We demonstrate the applicability of our scheme based on 3D CT images from the Truth Cube experiment, 2D MR images of the brain, as well as 2D gel electrophoresis images. It turns out that the new scheme achieves more accurate results compared to previous approaches.
Crack image segmentation based on improved DBC method
NASA Astrophysics Data System (ADS)
Cao, Ting; Yang, Nan; Wang, Fengping; Gao, Ting; Wang, Weixing
2017-11-01
With the development of computer vision technology, crack detection based on digital image segmentation method arouses global attentions among researchers and transportation ministries. Since the crack always exhibits the random shape and complex texture, it is still a challenge to accomplish reliable crack detection results. Therefore, a novel crack image segmentation method based on fractal DBC (differential box counting) is introduced in this paper. The proposed method can estimate every pixel fractal feature based on neighborhood information which can consider the contribution from all possible direction in the related block. The block moves just one pixel every time so that it could cover all the pixels in the crack image. Unlike the classic DBC method which only describes fractal feature for the related region, this novel method can effectively achieve crack image segmentation according to the fractal feature of every pixel. The experiment proves the proposed method can achieve satisfactory results in crack detection.
Fundamental limits of reconstruction-based superresolution algorithms under local translation.
Lin, Zhouchen; Shum, Heung-Yeung
2004-01-01
Superresolution is a technique that can produce images of a higher resolution than that of the originally captured ones. Nevertheless, improvement in resolution using such a technique is very limited in practice. This makes it significant to study the problem: "Do fundamental limits exist for superresolution?" In this paper, we focus on a major class of superresolution algorithms, called the reconstruction-based algorithms, which compute high-resolution images by simulating the image formation process. Assuming local translation among low-resolution images, this paper is the first attempt to determine the explicit limits of reconstruction-based algorithms, under both real and synthetic conditions. Based on the perturbation theory of linear systems, we obtain the superresolution limits from the conditioning analysis of the coefficient matrix. Moreover, we determine the number of low-resolution images that are sufficient to achieve the limit. Both real and synthetic experiments are carried out to verify our analysis.
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.
Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian
2017-01-01
It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159
Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian
2017-03-01
It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.
Star tracking method based on multiexposure imaging for intensified star trackers.
Yu, Wenbo; Jiang, Jie; Zhang, Guangjun
2017-07-20
The requirements for the dynamic performance of star trackers are rapidly increasing with the development of space exploration technologies. However, insufficient knowledge of the angular acceleration has largely decreased the performance of the existing star tracking methods, and star trackers may even fail to track under highly dynamic conditions. This study proposes a star tracking method based on multiexposure imaging for intensified star trackers. The accurate estimation model of the complete motion parameters, including the angular velocity and angular acceleration, is established according to the working characteristic of multiexposure imaging. The estimation of the complete motion parameters is utilized to generate the predictive star image accurately. Therefore, the correct matching and tracking between stars in the real and predictive star images can be reliably accomplished under highly dynamic conditions. Simulations with specific dynamic conditions are conducted to verify the feasibility and effectiveness of the proposed method. Experiments with real starry night sky observation are also conducted for further verification. Simulations and experiments demonstrate that the proposed method is effective and shows excellent performance under highly dynamic conditions.
Transfer and conversion of images based on EIT in atom vapor.
Cao, Mingtao; Zhang, Liyun; Yu, Ya; Ye, Fengjuan; Wei, Dong; Guo, Wenge; Zhang, Shougang; Gao, Hong; Li, Fuli
2014-05-01
Transfer and conversion of images between different wavelengths or polarization has significant applications in optical communication and quantum information processing. We demonstrated the transfer of images based on electromagnetically induced transparency (EIT) in a rubidium vapor cell. In experiments, a 2D image generated by a spatial light modulator is used as a coupling field, and a plane wave served as a signal field. We found that the image carried by coupling field could be transferred to that carried by signal field, and the spatial patterns of transferred image are much better than that of the initial image. It also could be much smaller than that determined by the diffraction limit of the optical system. We also studied the subdiffraction propagation for the transferred image. Our results may have applications in quantum interference lithography and coherent Raman spectroscopy.
Combined photoacoustic and magneto-acoustic imaging.
Qu, Min; Mallidi, Srivalleesha; Mehrmohammadi, Mohammad; Ma, Li Leo; Johnston, Keith P; Sokolov, Konstantin; Emelianov, Stanislav
2009-01-01
Ultrasound is a widely used modality with excellent spatial resolution, low cost, portability, reliability and safety. In clinical practice and in the biomedical field, molecular ultrasound-based imaging techniques are desired to visualize tissue pathologies, such as cancer. In this paper, we present an advanced imaging technique - combined photoacoustic and magneto-acoustic imaging - capable of visualizing the anatomical, functional and biomechanical properties of tissues or organs. The experiments to test the combined imaging technique were performed using dual, nanoparticle-based contrast agents that exhibit the desired optical and magnetic properties. The results of our study demonstrate the feasibility of the combined photoacoustic and magneto-acoustic imaging that takes the advantages of each imaging techniques and provides high sensitivity, reliable contrast and good penetrating depth. Therefore, the developed imaging technique can be used in wide range of biomedical and clinical application.
Design of polarization imaging system based on CIS and FPGA
NASA Astrophysics Data System (ADS)
Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding
2008-02-01
As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wardaya, P. D., E-mail: pongga.wardaya@utp.edu.my; Noh, K. A. B. M., E-mail: pongga.wardaya@utp.edu.my; Yusoff, W. I. B. W., E-mail: pongga.wardaya@utp.edu.my
This paper discusses a new approach for investigating the seismic wave velocity of rock, specifically carbonates, as affected by their pore structures. While the conventional routine of seismic velocity measurement highly depends on the extensive laboratory experiment, the proposed approach utilizes the digital rock physics view which lies on the numerical experiment. Thus, instead of using core sample, we use the thin section image of carbonate rock to measure the effective seismic wave velocity when travelling on it. In the numerical experiment, thin section images act as the medium on which wave propagation will be simulated. For the modeling, anmore » advanced technique based on artificial neural network was employed for building the velocity and density profile, replacing image's RGB pixel value with the seismic velocity and density of each rock constituent. Then, ultrasonic wave was simulated to propagate in the thin section image by using finite difference time domain method, based on assumption of an acoustic-isotropic medium. Effective velocities were drawn from the recorded signal and being compared to the velocity modeling from Wyllie time average model and Kuster-Toksoz rock physics model. To perform the modeling, image analysis routines were undertaken for quantifying the pore aspect ratio that is assumed to represent the rocks pore structure. In addition, porosity and mineral fraction required for velocity modeling were also quantified by using integrated neural network and image analysis technique. It was found that the Kuster-Toksoz gives the closer prediction to the measured velocity as compared to the Wyllie time average model. We also conclude that Wyllie time average that does not incorporate the pore structure parameter deviates significantly for samples having more than 40% porosity. Utilizing this approach we found a good agreement between numerical experiment and theoretically derived rock physics model for estimating the effective seismic wave velocity of rock.« less
Imaging spectrometer using a liquid crystal tunable filter
NASA Astrophysics Data System (ADS)
Chrien, Thomas G.; Chovit, Christopher; Miller, Peter J.
1993-09-01
A demonstration imaging spectrometer using a liquid crystal tunable filter (LCTF) was built and tested on a hot air balloon platform. The LCTF is a tunable polarization interference or Lyot filter. The LCTF enables a small, light weight, low power, band sequential imaging spectrometer design. An overview of the prototype system is given along with a description of balloon experiment results. System model performance predictions are given for a future LCTF based imaging spectrometer design. System design considerations of LCTF imaging spectrometers are discussed.
Planetary instrument definition and development program: 'Miniature Monochromatic Imager'
NASA Technical Reports Server (NTRS)
Broadfoot, A. L.
1991-01-01
The miniature monochromatic imager (MMI) development work became the basis for the preparation of several instruments which were built and flown on the shuttle STS-39 as well as being used in ground based experiments. The following subject areas are covered: (1) applications of the ICCD to airglow and auroral measurements and (2) a panchromatic spectrograph with supporting monochromatic imagers.
Not looking yourself: The cost of self-selecting photographs for identity verification.
White, David; Burton, Amy L; Kemp, Richard I
2016-05-01
Photo-identification is based on the premise that photographs are representative of facial appearance. However, previous studies show that ratings of likeness vary across different photographs of the same face, suggesting that some images capture identity better than others. Two experiments were designed to examine the relationship between likeness judgments and face matching accuracy. In Experiment 1, we compared unfamiliar face matching accuracy for self-selected and other-selected high-likeness images. Surprisingly, images selected by previously unfamiliar viewers - after very limited exposure to a target face - were more accurately matched than self-selected images chosen by the target identity themselves. Results also revealed extremely low inter-rater agreement in ratings of likeness across participants, suggesting that perceptions of image resemblance are inherently unstable. In Experiment 2, we test whether the cost of self-selection can be explained by this general disagreement in likeness judgments between individual raters. We find that averaging across rankings by multiple raters produces image selections that provide superior identification accuracy. However, benefit of other-selection persisted for single raters, suggesting that inaccurate representations of self interfere with our ability to judge which images faithfully represent our current appearance. © 2015 The British Psychological Society.
Direct magnetic field estimation based on echo planar raw data.
Testud, Frederik; Splitthoff, Daniel Nicolas; Speck, Oliver; Hennig, Jürgen; Zaitsev, Maxim
2010-07-01
Gradient recalled echo echo planar imaging is widely used in functional magnetic resonance imaging. The fast data acquisition is, however, very sensitive to field inhomogeneities which manifest themselves as artifacts in the images. Typically used correction methods have the common deficit that the data for the correction are acquired only once at the beginning of the experiment, assuming the field inhomogeneity distribution B(0) does not change over the course of the experiment. In this paper, methods to extract the magnetic field distribution from the acquired k-space data or from the reconstructed phase image of a gradient echo planar sequence are compared and extended. A common derivation for the presented approaches provides a solid theoretical basis, enables a fair comparison and demonstrates the equivalence of the k-space and the image phase based approaches. The image phase analysis is extended here to calculate the local gradient in the readout direction and improvements are introduced to the echo shift analysis, referred to here as "k-space filtering analysis." The described methods are compared to experimentally acquired B(0) maps in phantoms and in vivo. The k-space filtering analysis presented in this work demonstrated to be the most sensitive method to detect field inhomogeneities.
Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning
NASA Astrophysics Data System (ADS)
Li, Jun-Bao; Liu, Jing; Pan, Jeng-Shyang; Yao, Hongxun
2017-06-01
Magnetic Resonance Super-resolution Imaging Measurement (MRIM) is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.
Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana
2015-11-01
Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.
Are power calculations useful? A multicentre neuroimaging study
Suckling, John; Henty, Julian; Ecker, Christine; Deoni, Sean C; Lombardo, Michael V; Baron-Cohen, Simon; Jezzard, Peter; Barnes, Anna; Chakrabarti, Bhismadev; Ooi, Cinly; Lai, Meng-Chuan; Williams, Steven C; Murphy, Declan GM; Bullmore, Edward
2014-01-01
There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources. PMID:24644267
SAR image change detection using watershed and spectral clustering
NASA Astrophysics Data System (ADS)
Niu, Ruican; Jiao, L. C.; Wang, Guiting; Feng, Jie
2011-12-01
A new method of change detection in SAR images based on spectral clustering is presented in this paper. Spectral clustering is employed to extract change information from a pair images acquired on the same geographical area at different time. Watershed transform is applied to initially segment the big image into non-overlapped local regions, leading to reduce the complexity. Experiments results and system analysis confirm the effectiveness of the proposed algorithm.
Phase imaging in brain using SWIFT
NASA Astrophysics Data System (ADS)
Lehto, Lauri Juhani; Garwood, Michael; Gröhn, Olli; Corum, Curtis Andrew
2015-03-01
The majority of MRI phase imaging is based on gradient recalled echo (GRE) sequences. This work studies phase contrast behavior due to small off-resonance frequency offsets in brain using SWIFT, a FID-based sequence with nearly zero acquisition delay. 1D simulations and a phantom study were conducted to describe the behavior of phase accumulation in SWIFT. Imaging experiments of known brain phase contrast properties were conducted in a perfused rat brain comparing GRE and SWIFT. Additionally, a human brain sample was imaged. It is demonstrated how SWIFT phase is orientation dependent and correlates well with GRE, linking SWIFT phase to similar off-resonance sources as GRE. The acquisition time is shown to be analogous to TE for phase accumulation time. Using experiments with and without a magnetization transfer preparation, the likely effect of myelin water pool contribution is seen as a phase increase for all acquisition times. Due to the phase accumulation during acquisition, SWIFT phase contrast can be sensitized to small frequency differences between white and gray matter using low acquisition bandwidths.
Chen, Qiang; Chen, Yunhao; Jiang, Weiguo
2016-01-01
In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285
Image quality assessment metric for frame accumulated image
NASA Astrophysics Data System (ADS)
Yu, Jianping; Li, Gang; Wang, Shaohui; Lin, Ling
2018-01-01
The medical image quality determines the accuracy of diagnosis, and the gray-scale resolution is an important parameter to measure image quality. But current objective metrics are not very suitable for assessing medical images obtained by frame accumulation technology. Little attention was paid to the gray-scale resolution, basically based on spatial resolution and limited to the 256 level gray scale of the existing display device. Thus, this paper proposes a metric, "mean signal-to-noise ratio" (MSNR) based on signal-to-noise in order to be more reasonable to evaluate frame accumulated medical image quality. We demonstrate its potential application through a series of images under a constant illumination signal. Here, the mean image of enough images was regarded as the reference image. Several groups of images by different frame accumulation and their MSNR were calculated. The results of the experiment show that, compared with other quality assessment methods, the metric is simpler, more effective, and more suitable for assessing frame accumulated images that surpass the gray scale and precision of the original image.
Single-image super-resolution based on Markov random field and contourlet transform
NASA Astrophysics Data System (ADS)
Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai
2011-04-01
Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.
Image-Based Reconstruction and Analysis of Dynamic Scenes in a Landslide Simulation Facility
NASA Astrophysics Data System (ADS)
Scaioni, M.; Crippa, J.; Longoni, L.; Papini, M.; Zanzi, L.
2017-12-01
The application of image processing and photogrammetric techniques to dynamic reconstruction of landslide simulations in a scaled-down facility is described. Simulations are also used here for active-learning purpose: students are helped understand how physical processes happen and which kinds of observations may be obtained from a sensor network. In particular, the use of digital images to obtain multi-temporal information is presented. On one side, using a multi-view sensor set up based on four synchronized GoPro 4 Black® cameras, a 4D (3D spatial position and time) reconstruction of the dynamic scene is obtained through the composition of several 3D models obtained from dense image matching. The final textured 4D model allows one to revisit in dynamic and interactive mode a completed experiment at any time. On the other side, a digital image correlation (DIC) technique has been used to track surface point displacements from the image sequence obtained from the camera in front of the simulation facility. While the 4D model may provide a qualitative description and documentation of the experiment running, DIC analysis output quantitative information such as local point displacements and velocities, to be related to physical processes and to other observations. All the hardware and software equipment adopted for the photogrammetric reconstruction has been based on low-cost and open-source solutions.
The fast iris image clarity evaluation based on Tenengrad and ROI selection
NASA Astrophysics Data System (ADS)
Gao, Shuqin; Han, Min; Cheng, Xu
2018-04-01
In iris recognition system, the clarity of iris image is an important factor that influences recognition effect. In the process of recognition, the blurred image may possibly be rejected by the automatic iris recognition system, which will lead to the failure of identification. Therefore it is necessary to evaluate the iris image definition before recognition. Considered the existing evaluation methods on iris image definition, we proposed a fast algorithm to evaluate the definition of iris image in this paper. In our algorithm, firstly ROI (Region of Interest) is extracted based on the reference point which is determined by using the feature of the light spots within the pupil, then Tenengrad operator is used to evaluate the iris image's definition. Experiment results show that, the iris image definition algorithm proposed in this paper could accurately distinguish the iris images of different clarity, and the algorithm has the merit of low computational complexity and more effectiveness.
Application of visual cryptography for learning in optics and photonics
NASA Astrophysics Data System (ADS)
Mandal, Avikarsha; Wozniak, Peter; Vauderwange, Oliver; Curticapean, Dan
2016-09-01
In the age data digitalization, important applications of optics and photonics based sensors and technology lie in the field of biometrics and image processing. Protecting user data in a safe and secure way is an essential task in this area. However, traditional cryptographic protocols rely heavily on computer aided computation. Secure protocols which rely only on human interactions are usually simpler to understand. In many scenarios development of such protocols are also important for ease of implementation and deployment. Visual cryptography (VC) is an encryption technique on images (or text) in which decryption is done by human visual system. In this technique, an image is encrypted into number of pieces (known as shares). When the printed shares are physically superimposed together, the image can be decrypted with human vision. Modern digital watermarking technologies can be combined with VC for image copyright protection where the shares can be watermarks (small identification) embedded in the image. Similarly, VC can be used for improving security of biometric authentication. This paper presents about design and implementation of a practical laboratory experiment based on the concept of VC for a course in media engineering. Specifically, our contribution deals with integration of VC in different schemes for applications like digital watermarking and biometric authentication in the field of optics and photonics. We describe theoretical concepts and propose our infrastructure for the experiment. Finally, we will evaluate the learning outcome of the experiment, performed by the students.
Quantum image encryption based on restricted geometric and color transformations
NASA Astrophysics Data System (ADS)
Song, Xian-Hua; Wang, Shen; Abd El-Latif, Ahmed A.; Niu, Xia-Mu
2014-08-01
A novel encryption scheme for quantum images based on restricted geometric and color transformations is proposed. The new strategy comprises efficient permutation and diffusion properties for quantum image encryption. The core idea of the permutation stage is to scramble the codes of the pixel positions through restricted geometric transformations. Then, a new quantum diffusion operation is implemented on the permutated quantum image based on restricted color transformations. The encryption keys of the two stages are generated by two sensitive chaotic maps, which can ensure the security of the scheme. The final step, measurement, is built by the probabilistic model. Experiments conducted on statistical analysis demonstrate that significant improvements in the results are in favor of the proposed approach.
Automatic calibration method for plenoptic camera
NASA Astrophysics Data System (ADS)
Luan, Yinsen; He, Xing; Xu, Bing; Yang, Ping; Tang, Guomao
2016-04-01
An automatic calibration method is proposed for a microlens-based plenoptic camera. First, all microlens images on the white image are searched and recognized automatically based on digital morphology. Then, the center points of microlens images are rearranged according to their relative position relationships. Consequently, the microlens images are located, i.e., the plenoptic camera is calibrated without the prior knowledge of camera parameters. Furthermore, this method is appropriate for all types of microlens-based plenoptic cameras, even the multifocus plenoptic camera, the plenoptic camera with arbitrarily arranged microlenses, or the plenoptic camera with different sizes of microlenses. Finally, we verify our method by the raw data of Lytro. The experiments show that our method has higher intelligence than the methods published before.
Visualizing dispersive features in 2D image via minimum gradient method
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Yu; Wang, Yan; Shen, Zhi -Xun
Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less
Visualizing dispersive features in 2D image via minimum gradient method
He, Yu; Wang, Yan; Shen, Zhi -Xun
2017-07-24
Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less
Tracker: Image-Processing and Object-Tracking System Developed
NASA Technical Reports Server (NTRS)
Klimek, Robert B.; Wright, Theodore W.
1999-01-01
Tracker is an object-tracking and image-processing program designed and developed at the NASA Lewis Research Center to help with the analysis of images generated by microgravity combustion and fluid physics experiments. Experiments are often recorded on film or videotape for analysis later. Tracker automates the process of examining each frame of the recorded experiment, performing image-processing operations to bring out the desired detail, and recording the positions of the objects of interest. It can load sequences of images from disk files or acquire images (via a frame grabber) from film transports, videotape, laser disks, or a live camera. Tracker controls the image source to automatically advance to the next frame. It can employ a large array of image-processing operations to enhance the detail of the acquired images and can analyze an arbitrarily large number of objects simultaneously. Several different tracking algorithms are available, including conventional threshold and correlation-based techniques, and more esoteric procedures such as "snake" tracking and automated recognition of character data in the image. The Tracker software was written to be operated by researchers, thus every attempt was made to make the software as user friendly and self-explanatory as possible. Tracker is used by most of the microgravity combustion and fluid physics experiments performed by Lewis, and by visiting researchers. This includes experiments performed on the space shuttles, Mir, sounding rockets, zero-g research airplanes, drop towers, and ground-based laboratories. This software automates the analysis of the flame or liquid s physical parameters such as position, velocity, acceleration, size, shape, intensity characteristics, color, and centroid, as well as a number of other measurements. It can perform these operations on multiple objects simultaneously. Another key feature of Tracker is that it performs optical character recognition (OCR). This feature is useful in extracting numerical instrumentation data that are embedded in images. All the results are saved in files for further data reduction and graphing. There are currently three Tracking Systems (workstations) operating near the laboratories and offices of Lewis Microgravity Science Division researchers. These systems are used independently by students, scientists, and university-based principal investigators. The researchers bring their tapes or films to the workstation and perform the tracking analysis. The resultant data files generated by the tracking process can then be analyzed on the spot, although most of the time researchers prefer to transfer them via the network to their offices for further analysis or plotting. In addition, many researchers have installed Tracker on computers in their office for desktop analysis of digital image sequences, which can be digitized by the Tracking System or some other means. Tracker has not only provided a capability to efficiently and automatically analyze large volumes of data, saving many hours of tedious work, but has also provided new capabilities to extract valuable information and phenomena that was heretofore undetected and unexploited.
A Depth Map Generation Algorithm Based on Saliency Detection for 2D to 3D Conversion
NASA Astrophysics Data System (ADS)
Yang, Yizhong; Hu, Xionglou; Wu, Nengju; Wang, Pengfei; Xu, Dong; Rong, Shen
2017-09-01
In recent years, 3D movies attract people's attention more and more because of their immersive stereoscopic experience. However, 3D movies is still insufficient, so estimating depth information for 2D to 3D conversion from a video is more and more important. In this paper, we present a novel algorithm to estimate depth information from a video via scene classification algorithm. In order to obtain perceptually reliable depth information for viewers, the algorithm classifies them into three categories: landscape type, close-up type, linear perspective type firstly. Then we employ a specific algorithm to divide the landscape type image into many blocks, and assign depth value by similar relative height cue with the image. As to the close-up type image, a saliency-based method is adopted to enhance the foreground in the image and the method combine it with the global depth gradient to generate final depth map. By vanishing line detection, the calculated vanishing point which is regarded as the farthest point to the viewer is assigned with deepest depth value. According to the distance between the other points and the vanishing point, the entire image is assigned with corresponding depth value. Finally, depth image-based rendering is employed to generate stereoscopic virtual views after bilateral filter. Experiments show that the proposed algorithm can achieve realistic 3D effects and yield satisfactory results, while the perception scores of anaglyph images lie between 6.8 and 7.8.
Photoelectrocyclization as an activation mechanism for organelle-specific live-cell imaging probes.
Tran, Mai N; Chenoweth, David M
2015-05-26
Photoactivatable fluorophores are useful tools in live-cell imaging owing to their potential for precise spatial and temporal control. In this report, a new photoactivatable organelle-specific live-cell imaging probe based on a 6π electrocyclization/oxidation mechanism is described. It is shown that this new probe is water-soluble, non-cytotoxic, cell-permeable, and useful for mitochondrial imaging. The probe displays large Stokes shifts in both pre-activated and activated forms, allowing simultaneous use with common dyes and fluorescent proteins. Sequential single-cell activation experiments in dense cellular environments demonstrate high spatial precision and utility in single- or multi-cell labeling experiments. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Image processing system design for microcantilever-based optical readout infrared arrays
NASA Astrophysics Data System (ADS)
Tong, Qiang; Dong, Liquan; Zhao, Yuejin; Gong, Cheng; Liu, Xiaohua; Yu, Xiaomei; Yang, Lei; Liu, Weiyu
2012-12-01
Compared with the traditional infrared imaging technology, the new type of optical-readout uncooled infrared imaging technology based on MEMS has many advantages, such as low cost, small size, producing simple. In addition, the theory proves that the technology's high thermal detection sensitivity. So it has a very broad application prospects in the field of high performance infrared detection. The paper mainly focuses on an image capturing and processing system in the new type of optical-readout uncooled infrared imaging technology based on MEMS. The image capturing and processing system consists of software and hardware. We build our image processing core hardware platform based on TI's high performance DSP chip which is the TMS320DM642, and then design our image capturing board based on the MT9P031. MT9P031 is Micron's company high frame rate, low power consumption CMOS chip. Last we use Intel's company network transceiver devices-LXT971A to design the network output board. The software system is built on the real-time operating system DSP/BIOS. We design our video capture driver program based on TI's class-mini driver and network output program based on the NDK kit for image capturing and processing and transmitting. The experiment shows that the system has the advantages of high capturing resolution and fast processing speed. The speed of the network transmission is up to 100Mbps.
Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu
2017-06-30
This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.
Web Image Search Re-ranking with Click-based Similarity and Typicality.
Yang, Xiaopeng; Mei, Tao; Zhang, Yong Dong; Liu, Jie; Satoh, Shin'ichi
2016-07-20
In image search re-ranking, besides the well known semantic gap, intent gap, which is the gap between the representation of users' query/demand and the real intent of the users, is becoming a major problem restricting the development of image retrieval. To reduce human effects, in this paper, we use image click-through data, which can be viewed as the "implicit feedback" from users, to help overcome the intention gap, and further improve the image search performance. Generally, the hypothesis visually similar images should be close in a ranking list and the strategy images with higher relevance should be ranked higher than others are widely accepted. To obtain satisfying search results, thus, image similarity and the level of relevance typicality are determinate factors correspondingly. However, when measuring image similarity and typicality, conventional re-ranking approaches only consider visual information and initial ranks of images, while overlooking the influence of click-through data. This paper presents a novel re-ranking approach, named spectral clustering re-ranking with click-based similarity and typicality (SCCST). First, to learn an appropriate similarity measurement, we propose click-based multi-feature similarity learning algorithm (CMSL), which conducts metric learning based on clickbased triplets selection, and integrates multiple features into a unified similarity space via multiple kernel learning. Then based on the learnt click-based image similarity measure, we conduct spectral clustering to group visually and semantically similar images into same clusters, and get the final re-rank list by calculating click-based clusters typicality and withinclusters click-based image typicality in descending order. Our experiments conducted on two real-world query-image datasets with diverse representative queries show that our proposed reranking approach can significantly improve initial search results, and outperform several existing re-ranking approaches.
Application Possibility of Smartphone as Payload for Photogrammetric Uav System
NASA Astrophysics Data System (ADS)
Yun, M. H.; Kim, J.; Seo, D.; Lee, J.; Choi, C.
2012-07-01
Smartphone can not only be operated under 3G network environment anytime and anyplace but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study is aimed to assess the possibility of smartphone as a payload for photogrammetric UAV system. Prior to such assessment, a smartphone-based photogrammetric UAV system application was developed, through which real-time image, location and attitude data was obtained using smartphone under both static and dynamic conditions. Subsequently the accuracy assessment on the location and attitude data obtained and sent by this system was conducted. The smartphone images were converted into ortho-images through image triangulation. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration. In case IO parameters were taken into account in the static experiment, the results from triangulation for any smartphone type were within 1.5 pixel (RMSE), which was improved at least by 35% compared to when IO parameters were not taken into account. On the contrary, the improvement effect of considering IO parameters on accuracy in triangulation for smartphone images in dynamic experiment was not significant compared to the static experiment. It was due to the significant impact of vibration and sudden attitude change of UAV on the actuator for automatic focus control within the camera built in smartphone under the dynamic condition. This cause appears to have a negative impact on the image-based DEM generation. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.
Luo, Qiang; Yan, Zhuangzhi; Gu, Dongxing; Cao, Lei
This paper proposed an image interpolation algorithm based on bilinear interpolation and a color correction algorithm based on polynomial regression on FPGA, which focused on the limited number of imaging pixels and color distortion of the ultra-thin electronic endoscope. Simulation experiment results showed that the proposed algorithm realized the real-time display of 1280 x 720@60Hz HD video, and using the X-rite color checker as standard colors, the average color difference was reduced about 30% comparing with that before color correction.
[Research on WiFi-based wireless microscopy on a mobile phone and its application].
Hailan, Jin; Jing, Liu
2012-11-01
We proposed and realized a new device that acquires microscopic image wirelessly based on mobile phone and WiFi system. The mobile terminals could record, display and store the image from the far end via the wireless LAN. Using this system, a series of conceptual experiments on monitoring the microscopic images of common objects and liver cancer cells were successfully demonstrated. This system is expected to have important value in the experimental investigations on wirelessly monitoring the cell culture, and small insect etc.
A design of driving circuit for star sensor imaging camera
NASA Astrophysics Data System (ADS)
Li, Da-wei; Yang, Xiao-xu; Han, Jun-feng; Liu, Zhao-hui
2016-01-01
The star sensor is a high-precision attitude sensitive measuring instruments, which determine spacecraft attitude by detecting different positions on the celestial sphere. Imaging camera is an important portion of star sensor. The purpose of this study is to design a driving circuit based on Kodak CCD sensor. The design of driving circuit based on Kodak KAI-04022 is discussed, and the timing of this CCD sensor is analyzed. By the driving circuit testing laboratory and imaging experiments, it is found that the driving circuits can meet the requirements of Kodak CCD sensor.
Li, Tian-Jiao; Li, Sai; Yuan, Yuan; Liu, Yu-Dong; Xu, Chuan-Long; Shuai, Yong; Tan, He-Ping
2017-04-03
Plenoptic cameras are used for capturing flames in studies of high-temperature phenomena. However, simulations of plenoptic camera models can be used prior to the experiment improve experimental efficiency and reduce cost. In this work, microlens arrays, which are based on the established light field camera model, are optimized into a hexagonal structure with three types of microlenses. With this improved plenoptic camera model, light field imaging of static objects and flame are simulated using the calibrated parameters of the Raytrix camera (R29). The optimized models improve the image resolution, imaging screen utilization, and shooting range of depth of field.
Image restoration by minimizing zero norm of wavelet frame coefficients
NASA Astrophysics Data System (ADS)
Bao, Chenglong; Dong, Bin; Hou, Likun; Shen, Zuowei; Zhang, Xiaoqun; Zhang, Xue
2016-11-01
In this paper, we propose two algorithms, namely the extrapolated proximal iterative hard thresholding (EPIHT) algorithm and the EPIHT algorithm with line-search, for solving the {{\\ell }}0-norm regularized wavelet frame balanced approach for image restoration. Under the theoretical framework of Kurdyka-Łojasiewicz property, we show that the sequences generated by the two algorithms converge to a local minimizer with linear convergence rate. Moreover, extensive numerical experiments on sparse signal reconstruction and wavelet frame based image restoration problems including CT reconstruction, image deblur, demonstrate the improvement of {{\\ell }}0-norm based regularization models over some prevailing ones, as well as the computational efficiency of the proposed algorithms.
Hierarchical clustering method for improved prostate cancer imaging in diffuse optical tomography
NASA Astrophysics Data System (ADS)
Kavuri, Venkaiah C.; Liu, Hanli
2013-03-01
We investigate the feasibility of trans-rectal near infrared (NIR) based diffuse optical tomography (DOT) for early detection of prostate cancer using a transrectal ultrasound (TRUS) compatible imaging probe. For this purpose, we designed a TRUS-compatible, NIR-based image system (780nm), in which the photo diodes were placed on the trans-rectal probe. DC signals were recorded and used for estimating the absorption coefficient. We validated the system using laboratory phantoms. For further improvement, we also developed a hierarchical clustering method (HCM) to improve the accuracy of image reconstruction with limited prior information. We demonstrated the method using computer simulations laboratory phantom experiments.
The Scanning Nanoprobe Beamline Nanoscopium at Synchrotron Soleil
NASA Astrophysics Data System (ADS)
Somogyi, A.; Kewish, C. M.; Polack, F.; Moreno, T.
2011-09-01
The Nanoscopium beamline at Synchrotron Soleil will offer advanced scanning-based hard x-ray imaging techniques in the 5- to 20-keV energy range, for user communities working in the earth, environmental, and life sciences. Two dedicated end stations will exploit x-ray coherence to produce images in which contrast is based on a range of physical processes. In the first experiment hutch, coherent scatter imaging techniques will produce images in which contrast arises from spatial variations in the complex refractive index, and orientation in the nanostructure of samples. In the second experiment hutch, elemental mapping will be carried out at the trace (ppm) level by scanning x-ray fluorescence, speciation mapping by XANES, and phase gradient mapping by scanning differential phase contrast imaging. The beamline aims to reach sub-micrometric, down to 30 nm, spatial resolution. This ˜155-meter-long beamline will share the straight section with a future tomography beamline by using canted undulators having 6.5-mrad separation angle. The optical design of Nanoscopium aims to reduce the effect of instabilities on the probing nanobeam by utilizing an all-horizontal geometry for the reflections of the primary beamline mirrors, which focus onto a slit, creating an over-filled secondary source. Kirkpatrick-Baez mirrors and Fresnel zone plates will be used as focusing devices in the experiment hutches. Nanoscopium is expected to commence user operation in 2013.
Hess, Thomas M.; Popham, Lauren E.; Growney, Claire M.
2017-01-01
Background Previous research (Hess, Popham, Dennis, & Emery, 2013) suggested that age-based positivity effects in memory were attenuated with social stimuli. We examined the degree to which this generalized across arousal levels associated with social images. We also examined variations in approach and avoidance responses to images, and how these were differentially related to memory in younger versus older adults. Methods In Experiment 1, young (22 – 43 years) and older (65 – 85 years) adults recalled positive and negative social scenes that were high or low in arousal. In Experiment 2, young (20 – 40 years) and older (65 – 83 years) adults viewed and recalled the same scenes under instructions designed to alter arousal, and approach and avoidance ratings for each image were recorded. Results In Experiment 1, age differences in recall were confined to high-arousal, negative images, with young adults exhibiting superior memory relative to older adults. There was no evidence of an age-related positivity effect for low arousal social scenes. This result was replicated in Experiment 2, but distancing instructions minimized the age difference in recall for high-arousal, negative images. Approach and avoidance ratings differentially predicted recall across age groups, with stronger associations in the young. Conclusion The results are consistent with emerging evidence demonstrating that valence-based biases associated with aging (e.g., positivity effect) are specific to the context and stimulus characteristics. Differences in prediction of recall responses from approach and avoidance ratings across age groups suggested that the observed effects in memory reflected differences in responses to the characteristics of stimuli. PMID:28230420
Accuracy Considerations in Image-guided Cardiac Interventions: Experience and Lessons Learned
Linte, Cristian A.; Lang, Pencilla; Rettmann, Maryam E.; Cho, Daniel S.; Holmes, David R.; Robb, Richard A.; Peters, Terry M.
2014-01-01
Motivation Medical imaging and its application in interventional guidance has revolutionized the development of minimally invasive surgical procedures leading to reduced patient trauma, fewer risks, and shorter recovery times. However, a frequently posed question with regards to an image guidance system is “how accurate is it?” On one hand, the accuracy challenge can be posed in terms of the tolerable clinical error associated with the procedure; on the other hand, accuracy is bound by the limitations of the system’s components, including modeling, patient registration, and surgical instrument tracking, all of which ultimately impact the overall targeting capabilities of the system. Methods While these processes are not unique to any interventional specialty, this paper discusses them in the context of two different cardiac image-guidance platforms: a model-enhanced ultrasound platform for intracardiac interventions and a prototype system for advanced visualization in image-guided cardiac ablation therapy. Results Pre-operative modeling techniques involving manual, semi-automatic and registration-based segmentation are discussed. The performance and limitations of clinically feasible approaches for patient registration evaluated both in the laboratory and operating room are presented. Our experience with two different magnetic tracking systems for instrument and ultrasound transducer localization is reported. Ultimately, the overall accuracy of the systems is discussed based on both in vitro and preliminary in vivo experience. Conclusion While clinical accuracy is specific to a particular patient and procedure and vastly dependent on the surgeon’s experience, the system’s engineering limitations are critical to determine whether the clinical requirements can be met. PMID:21671097
A memory learning framework for effective image retrieval.
Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang
2005-04-01
Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.
Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei
2016-01-01
Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190
Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei
2016-09-15
Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.
Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction.
Roy, Snehashis; Chou, Yi-Yu; Jog, Amod; Butman, John A; Pham, Dzung L
2016-10-01
Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T 2 -w whole head (including brain, skull, eyes etc) images from T 1 -w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B 0 magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T 2 -w image. We show that our synthetic T 2 -w images can be used as a template in absence of a real T 2 -w image. Our patch based method requires multiple atlases with T 1 and T 2 to be registeLowRes to a given target T 1 . Then for every patch on the target, multiple similar looking matching patches are found on the atlas T 1 images and corresponding patches on the atlas T 2 images are combined to generate a synthetic T 2 of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T 2 images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.
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.
Memory states influence value-based decisions.
Duncan, Katherine D; Shohamy, Daphna
2016-11-01
Using memory to guide decisions allows past experience to improve future outcomes. However, the circumstances that modulate how and when memory influences decisions are not well understood. Here, we report that the use of memories to guide decisions depends on the context in which these decisions are made. We show that decisions made in the context of familiar images are more likely to be influenced by past events than are decisions made in the context of novel images (Experiment 1), that this bias persists even when a temporal gap is introduced between the image presentation and the decision (Experiment 2), and that contextual novelty facilitates value learning whereas familiarity facilitates the retrieval and use of previously learned values (Experiment 3). These effects are consistent with neurobiological and computational models of memory, which propose that familiar images evoke a lingering "retrieval state" that facilitates the recollection of other episodic memories. Together, these experiments highlight the importance of episodic memory for decision-making and provide an example of how computational and neurobiological theories can lead to new insights into how and when different types of memories guide our choices. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Stack, K. M.; Edwards, C. S.; Grotzinger, J. P.; Gupta, S.; Sumner, D. Y.; Calef, F. J.; Edgar, L. A.; Edgett, K. S.; Fraeman, A. A.; Jacob, S. R.; Le Deit, L.; Lewis, K. W.; Rice, M. S.; Rubin, D.; Williams, R. M. E.; Williford, K. H.
2016-12-01
This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity's Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations.
Stack, Kathryn M.; Edwards, Christopher; Grotzinger, J. P.; Gupta, S.; Sumner, D.; Edgar, Lauren; Fraeman, A.; Jacob, S.; LeDeit, L.; Lewis, K.W.; Rice, M.S.; Rubin, D.; Calef, F.; Edgett, K.; Williams, R.M.E.; Williford, K.H.
2016-01-01
This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity’s Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations.
Cone-beam x-ray luminescence computed tomography based on x-ray absorption dosage.
Liu, Tianshuai; Rong, Junyan; Gao, Peng; Zhang, Wenli; Liu, Wenlei; Zhang, Yuanke; Lu, Hongbing
2018-02-01
With the advances of x-ray excitable nanophosphors, x-ray luminescence computed tomography (XLCT) has become a promising hybrid imaging modality. In particular, a cone-beam XLCT (CB-XLCT) system has demonstrated its potential in in vivo imaging with the advantage of fast imaging speed over other XLCT systems. Currently, the imaging models of most XLCT systems assume that nanophosphors emit light based on the intensity distribution of x-ray within the object, not completely reflecting the nature of the x-ray excitation process. To improve the imaging quality of CB-XLCT, an imaging model that adopts an excitation model of nanophosphors based on x-ray absorption dosage is proposed in this study. To solve the ill-posed inverse problem, a reconstruction algorithm that combines the adaptive Tikhonov regularization method with the imaging model is implemented for CB-XLCT reconstruction. Numerical simulations and phantom experiments indicate that compared with the traditional forward model based on x-ray intensity, the proposed dose-based model could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy, and image contrast. In addition, the proposed model behaves better in distinguishing closer targets, demonstrating its advantage in improving spatial resolution. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
NASA Astrophysics Data System (ADS)
Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin
2018-04-01
Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.
Information recovery in propagation-based imaging with decoherence effects
NASA Astrophysics Data System (ADS)
Froese, Heinrich; Lötgering, Lars; Wilhein, Thomas
2017-05-01
During the past decades the optical imaging community witnessed a rapid emergence of novel imaging modalities such as coherent diffraction imaging (CDI), propagation-based imaging and ptychography. These methods have been demonstrated to recover complex-valued scalar wave fields from redundant data without the need for refractive or diffractive optical elements. This renders these techniques suitable for imaging experiments with EUV and x-ray radiation, where the use of lenses is complicated by fabrication, photon efficiency and cost. However, decoherence effects can have detrimental effects on the reconstruction quality of the numerical algorithms involved. Here we demonstrate propagation-based optical phase retrieval from multiple near-field intensities with decoherence effects such as partially coherent illumination, detector point spread, binning and position uncertainties of the detector. Methods for overcoming these systematic experimental errors - based on the decomposition of the data into mutually incoherent modes - are proposed and numerically tested. We believe that the results presented here open up novel algorithmic methods to accelerate detector readout rates and enable subpixel resolution in propagation-based phase retrieval. Further the techniques are straightforward to be extended to methods such as CDI, ptychography and holography.
Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering.
Gong, Maoguo; Zhou, Zhiqiang; Ma, Jingjing
2012-04-01
This paper presents an unsupervised distribution-free change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a novel fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image, wavelet fusion rules based on an average operator and minimum local area energy are chosen to fuse the wavelet coefficients for a low-frequency band and a high-frequency band, respectively. A reformulated fuzzy local-information C-means clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise. Experiments on real SAR images show that the image fusion strategy integrates the advantages of the log-ratio operator and the mean-ratio operator and gains a better performance. The change detection results obtained by the improved fuzzy clustering algorithm exhibited lower error than its preexistences.
Occam's razor: supporting visual query expression for content-based image queries
NASA Astrophysics Data System (ADS)
Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.
2005-01-01
This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).
Occam"s razor: supporting visual query expression for content-based image queries
NASA Astrophysics Data System (ADS)
Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.
2004-12-01
This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).
NASA Astrophysics Data System (ADS)
Li, Dongming; Zhang, Lijuan; Wang, Ting; Liu, Huan; Yang, Jinhua; Chen, Guifen
2016-11-01
To improve the adaptive optics (AO) image's quality, we study the AO image restoration algorithm based on wavefront reconstruction technology and adaptive total variation (TV) method in this paper. Firstly, the wavefront reconstruction using Zernike polynomial is used for initial estimated for the point spread function (PSF). Then, we develop our proposed iterative solutions for AO images restoration, addressing the joint deconvolution issue. The image restoration experiments are performed to verify the image restoration effect of our proposed algorithm. The experimental results show that, compared with the RL-IBD algorithm and Wiener-IBD algorithm, we can see that GMG measures (for real AO image) from our algorithm are increased by 36.92%, and 27.44% respectively, and the computation time are decreased by 7.2%, and 3.4% respectively, and its estimation accuracy is significantly improved.
Real-time single image dehazing based on dark channel prior theory and guided filtering
NASA Astrophysics Data System (ADS)
Zhang, Zan
2017-10-01
Images and videos taken outside the foggy day are serious degraded. In order to restore degraded image taken in foggy day and overcome traditional Dark Channel prior algorithms problems of remnant fog in edge, we propose a new dehazing method.We first find the fog area in the dark primary color map to obtain the estimated value of the transmittance using quadratic tree. Then we regard the gray-scale image after guided filtering as atmospheric light map and remove haze based on it. Box processing and image down sampling technology are also used to improve the processing speed. Finally, the atmospheric light scattering model is used to restore the image. A plenty of experiments show that algorithm is effective, efficient and has a wide range of application.
Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel
2014-10-01
An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.
Tang, Jian; Jiang, Xiaoliang
2017-01-01
Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.
Sociocultural Experiences of Bulimic and Non-Bulimic Adolescents in a School-Based Chinese Sample
ERIC Educational Resources Information Center
Jackson, Todd; Chen, Hong
2010-01-01
From a large school-based sample (N = 3,084), 49 Mainland Chinese adolescents (31 girls, 18 boys) who endorsed all DSM-IV criteria for bulimia nervosa (BN) or sub-threshold BN and 49 matched controls (31 girls, 18 boys) completed measures of demographics and sociocultural experiences related to body image. Compared to less symptomatic peers, those…
Cloud Detection of Optical Satellite Images Using Support Vector Machine
NASA Astrophysics Data System (ADS)
Lee, Kuan-Yi; Lin, Chao-Hung
2016-06-01
Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.
Comments on the CASIA version 1.0 iris data set.
Phillips, P Jonathon; Bowyer, Kevin W; Flynn, Patrick J
2007-10-01
We note that the images in the CASIA version 1.0 iris dataset have been edited so that the pupil area is replaced by a circular region of uniform intensity. We recommend that this dataset is no longer used in iris biometrics research, unless there this a compelling reason that takes into account the nature of the images. In addition, based on our experience with the Iris Challenge Evaluation (ICE) 2005 technology development project, we make recommendations for reporting results of iris recognition experiments.
NASA Astrophysics Data System (ADS)
Abookasis, David; Moshe, Tomer
2014-11-01
This paper demonstrates the insertion of lens array in the front of a CCD camera in a laser speckle imaging (LSI) like-technique to acquire multiple speckle reflectance projections for imaging blood flow in an intact biological tissue. In some of LSI applications, flow imaging is obtained by thinning or removing of the upper tissue layers to access blood vessels. In contrast, with the proposed approach flow imaging can be achieved while the tissue is intact. In the system, each lens from an hexagonal lens array observed the sample from slightly different perspectives and captured with a CCD camera. In the computer, these multiview raw images are converted to speckled contrast maps. Then, a self-deconvolution shift-and-add algorithm is employed for processing yields high contrast flow information. The method is experimentally validated first with a plastic tube filled with scattering liquid running at different controlled flow rates hidden in a biological tissue and then extensively tested for imaging of cerebral blood flow in an intact rodent head experience different conditions. A total of fifteen mice were used in the experiments divided randomly into three groups as follows: Group 1 (n=5) consisted of injured mice experience hypoxic ischemic brain injury monitored for ~40 min. Group 2 (n=5) injured mice experience anoxic brain injury monitored up to 20 min. Group 3 (n=5) experience functional activation monitored up to ~35 min. To increase tissue transparency and the penetration depth of photons through head tissue layers, an optical clearing method was employed. To our knowledge, this work presents for the first time the use of lens array in LSI scheme.
An FPGA-based heterogeneous image fusion system design method
NASA Astrophysics Data System (ADS)
Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong
2011-08-01
Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.
No scanning depth imaging system based on TOF
NASA Astrophysics Data System (ADS)
Sun, Rongchun; Piao, Yan; Wang, Yu; Liu, Shuo
2016-03-01
To quickly obtain a 3D model of real world objects, multi-point ranging is very important. However, the traditional measuring method usually adopts the principle of point by point or line by line measurement, which is too slow and of poor efficiency. In the paper, a no scanning depth imaging system based on TOF (time of flight) was proposed. The system is composed of light source circuit, special infrared image sensor module, processor and controller of image data, data cache circuit, communication circuit, and so on. According to the working principle of the TOF measurement, image sequence was collected by the high-speed CMOS sensor, and the distance information was obtained by identifying phase difference, and the amplitude image was also calculated. Experiments were conducted and the experimental results show that the depth imaging system can achieve no scanning depth imaging function with good performance.
An effective non-rigid registration approach for ultrasound image based on "demons" algorithm.
Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong; Tian, Jiawei
2013-06-01
Medical image registration is an important component of computer-aided diagnosis system in diagnostics, therapy planning, and guidance of surgery. Because of its low signal/noise ratio (SNR), ultrasound (US) image registration is a difficult task. In this paper, a fully automatic non-rigid image registration algorithm based on demons algorithm is proposed for registration of ultrasound images. In the proposed method, an "inertia force" derived from the local motion trend of pixels in a Moore neighborhood system is produced and integrated into optical flow equation to estimate the demons force, which is helpful to handle the speckle noise and preserve the geometric continuity of US images. In the experiment, a series of US images and several similarity measure metrics are utilized for evaluating the performance. The experimental results demonstrate that the proposed method can register ultrasound images efficiently, robust to noise, quickly and automatically.
A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching
Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Zhang, Peng
2017-01-01
Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images. PMID:28885547
NASA Astrophysics Data System (ADS)
Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang
2017-12-01
In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.
A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.
Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng
2017-09-08
Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.
3D fluorescence anisotropy imaging using selective plane illumination microscopy.
Hedde, Per Niklas; Ranjit, Suman; Gratton, Enrico
2015-08-24
Fluorescence anisotropy imaging is a popular method to visualize changes in organization and conformation of biomolecules within cells and tissues. In such an experiment, depolarization effects resulting from differences in orientation, proximity and rotational mobility of fluorescently labeled molecules are probed with high spatial resolution. Fluorescence anisotropy is typically imaged using laser scanning and epifluorescence-based approaches. Unfortunately, those techniques are limited in either axial resolution, image acquisition speed, or by photobleaching. In the last decade, however, selective plane illumination microscopy has emerged as the preferred choice for three-dimensional time lapse imaging combining axial sectioning capability with fast, camera-based image acquisition, and minimal light exposure. We demonstrate how selective plane illumination microscopy can be utilized for three-dimensional fluorescence anisotropy imaging of live cells. We further examined the formation of focal adhesions by three-dimensional time lapse anisotropy imaging of CHO-K1 cells expressing an EGFP-paxillin fusion protein.
SKL algorithm based fabric image matching and retrieval
NASA Astrophysics Data System (ADS)
Cao, Yichen; Zhang, Xueqin; Ma, Guojian; Sun, Rongqing; Dong, Deping
2017-07-01
Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.
Automatic Detection of Welding Defects using Deep Neural Network
NASA Astrophysics Data System (ADS)
Hou, Wenhui; Wei, Ye; Guo, Jie; Jin, Yi; Zhu, Chang'an
2018-01-01
In this paper, we propose an automatic detection schema including three stages for weld defects in x-ray images. Firstly, the preprocessing procedure for the image is implemented to locate the weld region; Then a classification model which is trained and tested by the patches cropped from x-ray images is constructed based on deep neural network. And this model can learn the intrinsic feature of images without extra calculation; Finally, the sliding-window approach is utilized to detect the whole images based on the trained model. In order to evaluate the performance of the model, we carry out several experiments. The results demonstrate that the classification model we proposed is effective in the detection of welded joints quality.
NASA Astrophysics Data System (ADS)
Wang, Zhuozheng; Deller, J. R.; Fleet, Blair D.
2016-01-01
Acquired digital images are often corrupted by a lack of camera focus, faulty illumination, or missing data. An algorithm is presented for fusion of multiple corrupted images of a scene using the lifting wavelet transform. The method employs adaptive fusion arithmetic based on matrix completion and self-adaptive regional variance estimation. Characteristics of the wavelet coefficients are used to adaptively select fusion rules. Robust principal component analysis is applied to low-frequency image components, and regional variance estimation is applied to high-frequency components. Experiments reveal that the method is effective for multifocus, visible-light, and infrared image fusion. Compared with traditional algorithms, the new algorithm not only increases the amount of preserved information and clarity but also improves robustness.
Sequential deconvolution from wave-front sensing using bivariate simplex splines
NASA Astrophysics Data System (ADS)
Guo, Shiping; Zhang, Rongzhi; Li, Jisheng; Zou, Jianhua; Xu, Rong; Liu, Changhai
2015-05-01
Deconvolution from wave-front sensing (DWFS) is an imaging compensation technique for turbulence degraded images based on simultaneous recording of short exposure images and wave-front sensor data. This paper employs the multivariate splines method for the sequential DWFS: a bivariate simplex splines based average slopes measurement model is built firstly for Shack-Hartmann wave-front sensor; next, a well-conditioned least squares estimator for the spline coefficients is constructed using multiple Shack-Hartmann measurements; then, the distorted wave-front is uniquely determined by the estimated spline coefficients; the object image is finally obtained by non-blind deconvolution processing. Simulated experiments in different turbulence strength show that our method performs superior image restoration results and noise rejection capability especially when extracting the multidirectional phase derivatives.
Space-variant restoration of images degraded by camera motion blur.
Sorel, Michal; Flusser, Jan
2008-02-01
We examine the problem of restoration from multiple images degraded by camera motion blur. We consider scenes with significant depth variations resulting in space-variant blur. The proposed algorithm can be applied if the camera moves along an arbitrary curve parallel to the image plane, without any rotations. The knowledge of camera trajectory and camera parameters is not necessary. At the input, the user selects a region where depth variations are negligible. The algorithm belongs to the group of variational methods that estimate simultaneously a sharp image and a depth map, based on the minimization of a cost functional. To initialize the minimization, it uses an auxiliary window-based depth estimation algorithm. Feasibility of the algorithm is demonstrated by three experiments with real images.
Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou
2017-07-01
In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.
Kernel Regression Estimation of Fiber Orientation Mixtures in Diffusion MRI
Cabeen, Ryan P.; Bastin, Mark E.; Laidlaw, David H.
2016-01-01
We present and evaluate a method for kernel regression estimation of fiber orientations and associated volume fractions for diffusion MR tractography and population-based atlas construction in clinical imaging studies of brain white matter. This is a model-based image processing technique in which representative fiber models are estimated from collections of component fiber models in model-valued image data. This extends prior work in nonparametric image processing and multi-compartment processing to provide computational tools for image interpolation, smoothing, and fusion with fiber orientation mixtures. In contrast to related work on multi-compartment processing, this approach is based on directional measures of divergence and includes data-adaptive extensions for model selection and bilateral filtering. This is useful for reconstructing complex anatomical features in clinical datasets analyzed with the ball-and-sticks model, and our framework’s data-adaptive extensions are potentially useful for general multi-compartment image processing. We experimentally evaluate our approach with both synthetic data from computational phantoms and in vivo clinical data from human subjects. With synthetic data experiments, we evaluate performance based on errors in fiber orientation, volume fraction, compartment count, and tractography-based connectivity. With in vivo data experiments, we first show improved scan-rescan reproducibility and reliability of quantitative fiber bundle metrics, including mean length, volume, streamline count, and mean volume fraction. We then demonstrate the creation of a multi-fiber tractography atlas from a population of 80 human subjects. In comparison to single tensor atlasing, our multi-fiber atlas shows more complete features of known fiber bundles and includes reconstructions of the lateral projections of the corpus callosum and complex fronto-parietal connections of the superior longitudinal fasciculus I, II, and III. PMID:26691524
Psychophysically based model of surface gloss perception
NASA Astrophysics Data System (ADS)
Ferwerda, James A.; Pellacini, Fabio; Greenberg, Donald P.
2001-06-01
In this paper we introduce a new model of surface appearance that is based on quantitative studies of gloss perception. We use image synthesis techniques to conduct experiments that explore the relationships between the physical dimensions of glossy reflectance and the perceptual dimensions of glossy appearance. The product of these experiments is a psychophysically-based model of surface gloss, with dimensions that are both physically and perceptually meaningful and scales that reflect our sensitivity to gloss variations. We demonstrate that the model can be used to describe and control the appearance of glossy surfaces in synthesis images, allowing prediction of gloss matches and quantification of gloss differences. This work represents some initial steps toward developing psychophyscial models of the goniometric aspects of surface appearance to complement widely-used colorimetric models.
Automatic image enhancement based on multi-scale image decomposition
NASA Astrophysics Data System (ADS)
Feng, Lu; Wu, Zhuangzhi; Pei, Luo; Long, Xiong
2014-01-01
In image processing and computational photography, automatic image enhancement is one of the long-range objectives. Recently the automatic image enhancement methods not only take account of the globe semantics, like correct color hue and brightness imbalances, but also the local content of the image, such as human face and sky of landscape. In this paper we describe a new scheme for automatic image enhancement that considers both global semantics and local content of image. Our automatic image enhancement method employs the multi-scale edge-aware image decomposition approach to detect the underexposure regions and enhance the detail of the salient content. The experiment results demonstrate the effectiveness of our approach compared to existing automatic enhancement methods.
Image search engine with selective filtering and feature-element-based classification
NASA Astrophysics Data System (ADS)
Li, Qing; Zhang, Yujin; Dai, Shengyang
2001-12-01
With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.
An efficient intensity-based ready-to-use X-ray image stitcher.
Wang, Junchen; Zhang, Xiaohui; Sun, Zhen; Yuan, Fuzhen
2018-06-14
The limited field of view of the X-ray image intensifier makes it difficult to cover a large target area with a single X-ray image. X-ray image stitching techniques have been proposed to produce a panoramic X-ray image. This paper presents an efficient intensity-based X-ray image stitcher, which does not rely on accurate C-arm motion control or auxiliary devices and hence is ready to use in clinic. The stitcher consumes sequentially captured X-ray images with overlap areas and automatically produces a panoramic image. The gradient information for optimization of image alignment is obtained using a back-propagation scheme so that it is convenient to adopt various image warping models. The proposed stitcher has the following advantages over existing methods: (1) no additional hardware modification or auxiliary markers are needed; (2) it is robust against feature-based approaches; (3) arbitrary warping models and shapes of the region of interest are supported; (4) seamless stitching is achieved using multi-band blending. Experiments have been performed to confirm the effectiveness of the proposed method. The proposed X-ray image stitcher is efficient, accurate and ready to use in clinic. Copyright © 2018 John Wiley & Sons, Ltd.
Scotti, F.; Soukhanovskii, V. A.
2015-12-09
A two-channel spectral imaging system based on a charge injection device radiation-hardened intensified camera was built for studies of plasma-surface interactions on divertor plasma facing components in the National Spherical Torus Experiment Upgrade (NSTX-U) tokamak. By means of commercially available mechanically referenced optical components, the two-wavelength setup images the light from the plasma, relayed by a fiber optic bundle, at two different wavelengths side-by-side on the same detector. Remotely controlled filter wheels are used for narrow band pass and neutral density filters on each optical path allowing for simultaneous imaging of emission at wavelengths differing in brightness up to 3more » orders of magnitude. Applications on NSTX-U will include the measurement of impurity influxes in the lower divertor strike point region and the imaging of plasma-material interaction on the head of the surface analysis probe MAPP (Material Analysis and Particle Probe). Furthermore, the diagnostic setup and initial results from its application on the lithium tokamak experiment are presented.« less
The utility of multiple synthesized views in the recognition of unfamiliar faces.
Jones, Scott P; Dwyer, Dominic M; Lewis, Michael B
2017-05-01
The ability to recognize an unfamiliar individual on the basis of prior exposure to a photograph is notoriously poor and prone to errors, but recognition accuracy is improved when multiple photographs are available. In applied situations, when only limited real images are available (e.g., from a mugshot or CCTV image), the generation of new images might provide a technological prosthesis for otherwise fallible human recognition. We report two experiments examining the effects of providing computer-generated additional views of a target face. In Experiment 1, provision of computer-generated views supported better target face recognition than exposure to the target image alone and equivalent performance to that for exposure of multiple photograph views. Experiment 2 replicated the advantage of providing generated views, but also indicated an advantage for multiple viewings of the single target photograph. These results strengthen the claim that identifying a target face can be improved by providing multiple synthesized views based on a single target image. In addition, our results suggest that the degree of advantage provided by synthesized views may be affected by the quality of synthesized material.
Full-wave Nonlinear Inverse Scattering for Acoustic and Electromagnetic Breast Imaging
NASA Astrophysics Data System (ADS)
Haynes, Mark Spencer
Acoustic and electromagnetic full-wave nonlinear inverse scattering techniques are explored in both theory and experiment with the ultimate aim of noninvasively mapping the material properties of the breast. There is evidence that benign and malignant breast tissue have different acoustic and electrical properties and imaging these properties directly could provide higher quality images with better diagnostic certainty. In this dissertation, acoustic and electromagnetic inverse scattering algorithms are first developed and validated in simulation. The forward solvers and optimization cost functions are modified from traditional forms in order to handle the large or lossy imaging scenes present in ultrasonic and microwave breast imaging. An antenna model is then presented, modified, and experimentally validated for microwave S-parameter measurements. Using the antenna model, a new electromagnetic volume integral equation is derived in order to link the material properties of the inverse scattering algorithms to microwave S-parameters measurements allowing direct comparison of model predictions and measurements in the imaging algorithms. This volume integral equation is validated with several experiments and used as the basis of a free-space inverse scattering experiment, where images of the dielectric properties of plastic objects are formed without the use of calibration targets. These efforts are used as the foundation of a solution and formulation for the numerical characterization of a microwave near-field cavity-based breast imaging system. The system is constructed and imaging results of simple targets are given. Finally, the same techniques are used to explore a new self-characterization method for commercial ultrasound probes. The method is used to calibrate an ultrasound inverse scattering experiment and imaging results of simple targets are presented. This work has demonstrated the feasibility of quantitative microwave inverse scattering by way of a self-consistent characterization formalism, and has made headway in the same area for ultrasound.
Low-dose CT image reconstruction using gain intervention-based dictionary learning
NASA Astrophysics Data System (ADS)
Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra
2018-05-01
Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.
Shkvarko, Yuriy; Tuxpan, José; Santos, Stewart
2011-01-01
We consider a problem of high-resolution array radar/SAR imaging formalized in terms of a nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) of the random wavefield scattered from a remotely sensed scene observed through a kernel signal formation operator and contaminated with random Gaussian noise. First, the Sobolev-type solution space is constructed to specify the class of consistent kernel SSP estimators with the reproducing kernel structures adapted to the metrics in such the solution space. Next, the "model-free" variational analysis (VA)-based image enhancement approach and the "model-based" descriptive experiment design (DEED) regularization paradigm are unified into a new dynamic experiment design (DYED) regularization framework. Application of the proposed DYED framework to the adaptive array radar/SAR imaging problem leads to a class of two-level (DEED-VA) regularized SSP reconstruction techniques that aggregate the kernel adaptive anisotropic windowing with the projections onto convex sets to enforce the consistency and robustness of the overall iterative SSP estimators. We also show how the proposed DYED regularization method may be considered as a generalization of the MVDR, APES and other high-resolution nonparametric adaptive radar sensing techniques. A family of the DYED-related algorithms is constructed and their effectiveness is finally illustrated via numerical simulations.
Structural Information Detection Based Filter for GF-3 SAR Images
NASA Astrophysics Data System (ADS)
Sun, Z.; Song, Y.
2018-04-01
GF-3 satellite with high resolution, large swath, multi-imaging mode, long service life and other characteristics, can achieve allweather and all day monitoring for global land and ocean. It has become the highest resolution satellite system in the world with the C-band multi-polarized synthetic aperture radar (SAR) satellite. However, due to the coherent imaging system, speckle appears in GF-3 SAR images, and it hinders the understanding and interpretation of images seriously. Therefore, the processing of SAR images has big challenges owing to the appearance of speckle. The high-resolution SAR images produced by the GF-3 satellite are rich in information and have obvious feature structures such as points, edges, lines and so on. The traditional filters such as Lee filter and Gamma MAP filter are not appropriate for the GF-3 SAR images since they ignore the structural information of images. In this paper, the structural information detection based filter is constructed, successively including the point target detection in the smallest window, the adaptive windowing method based on regional characteristics, and the most homogeneous sub-window selection. The despeckling experiments on GF-3 SAR images demonstrate that compared with the traditional filters, the proposed structural information detection based filter can well preserve the points, edges and lines as well as smooth the speckle more sufficiently.
NASA Astrophysics Data System (ADS)
Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing
2016-04-01
In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.
Peter, Silvia; Modregger, Peter; Fix, Michael K.; Volken, Werner; Frei, Daniel; Manser, Peter; Stampanoni, Marco
2014-01-01
Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle- and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle- and wave-like properties into account. The framework can be adapted to different phase-sensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging. PMID:24763652
Breast histopathology image segmentation using spatio-colour-texture based graph partition method.
Belsare, A D; Mushrif, M M; Pangarkar, M A; Meshram, N
2016-06-01
This paper proposes a novel integrated spatio-colour-texture based graph partitioning method for segmentation of nuclear arrangement in tubules with a lumen or in solid islands without a lumen from digitized Hematoxylin-Eosin stained breast histology images, in order to automate the process of histology breast image analysis to assist the pathologists. We propose a new similarity based super pixel generation method and integrate it with texton representation to form spatio-colour-texture map of Breast Histology Image. Then a new weighted distance based similarity measure is used for generation of graph and final segmentation using normalized cuts method is obtained. The extensive experiments carried shows that the proposed algorithm can segment nuclear arrangement in normal as well as malignant duct in breast histology tissue image. For evaluation of the proposed method the ground-truth image database of 100 malignant and nonmalignant breast histology images is created with the help of two expert pathologists and the quantitative evaluation of proposed breast histology image segmentation has been performed. It shows that the proposed method outperforms over other methods. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.
Content-based image retrieval from a database of fracture images
NASA Astrophysics Data System (ADS)
Müller, Henning; Do Hoang, Phuong Anh; Depeursinge, Adrien; Hoffmeyer, Pierre; Stern, Richard; Lovis, Christian; Geissbuhler, Antoine
2007-03-01
This article describes the use of a medical image retrieval system on a database of 16'000 fractures, selected from surgical routine over several years. Image retrieval has been a very active domain of research for several years. It was frequently proposed for the medical domain, but only few running systems were ever tested in clinical routine. For the planning of surgical interventions after fractures, x-ray images play an important role. The fractures are classified according to exact fracture location, plus whether and to which degree the fracture is damaging articulations to see how complicated a reparation will be. Several classification systems for fractures exist and the classification plus the experience of the surgeon lead in the end to the choice of surgical technique (screw, metal plate, ...). This choice is strongly influenced by the experience and knowledge of the surgeons with respect to a certain technique. Goal of this article is to describe a prototype that supplies similar cases to an example to help treatment planning and find the most appropriate technique for a surgical intervention. Our database contains over 16'000 fracture images before and after a surgical intervention. We use an image retrieval system (GNU Image Finding Tool, GIFT) to find cases/images similar to an example case currently under observation. Problems encountered are varying illumination of images as well as strong anatomic differences between patients. Regions of interest are usually small and the retrieval system needs to focus on this region. Results show that GIFT is capable of supplying similar cases, particularly when using relevance feedback, on such a large database. Usual image retrieval is based on a single image as search target but for this application we have to select images by case as similar cases need to be found and not images. A few false positive cases often remain in the results but they can be sorted out quickly by the surgeons. Image retrieval can well be used for the planning of operations by supplying similar cases. A variety of challenges has been identified and partly solved (varying luminosity, small region of interested, case-based instead of image-based). This article mainly presents a case study to identify potential benefits and problems. Several steps for improving the system have been identified as well and will be described at the end of the paper.
Stripe nonuniformity correction for infrared imaging system based on single image optimization
NASA Astrophysics Data System (ADS)
Hua, Weiping; Zhao, Jufeng; Cui, Guangmang; Gong, Xiaoli; Ge, Peng; Zhang, Jiang; Xu, Zhihai
2018-06-01
Infrared imaging is often disturbed by stripe nonuniformity noise. Scene-based correction method can effectively reduce the impact of stripe noise. In this paper, a stripe nonuniformity correction method based on differential constraint is proposed. Firstly, the gray distribution of stripe nonuniformity is analyzed and the penalty function is constructed by the difference of horizontal gradient and vertical gradient. With the weight function, the penalty function is optimized to obtain the corrected image. Comparing with other single-frame approaches, experiments show that the proposed method performs better in both subjective and objective analysis, and does less damage to edge and detail. Meanwhile, the proposed method runs faster. We have also discussed the differences between the proposed idea and multi-frame methods. Our method is finally well applied in hardware system.
Acoustic superlens using Helmholtz-resonator-based metamaterials
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Xishan; Yin, Jing; Yu, Gaokun, E-mail: gkyu@ouc.edu.cn
2015-11-09
Acoustic superlens provides a way to overcome the diffraction limit with respect to the wavelength of the bulk wave in air. However, the operating frequency range of subwavelength imaging is quite narrow. Here, an acoustic superlens is designed using Helmholtz-resonator-based metamaterials to broaden the bandwidth of super-resolution. An experiment is carried out to verify subwavelength imaging of double slits, the imaging of which can be well resolved in the frequency range from 570 to 650 Hz. Different from previous works based on the Fabry-Pérot resonance, the corresponding mechanism of subwavelength imaging is the Fano resonance, and the strong coupling between themore » neighbouring Helmholtz resonators separated at the subwavelength interval leads to the enhanced sound transmission over a relatively wide frequency range.« less
Efficient method of image edge detection based on FSVM
NASA Astrophysics Data System (ADS)
Cai, Aiping; Xiong, Xiaomei
2013-07-01
For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.
A novel approach for fire recognition using hybrid features and manifold learning-based classifier
NASA Astrophysics Data System (ADS)
Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng
2018-03-01
Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.
NASA Astrophysics Data System (ADS)
Alshehhi, Rasha; Marpu, Prashanth Reddy
2017-04-01
Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.
10. The surface and interior of venus
Masursky, H.; Kaula, W.M.; McGill, G.E.; Pettengill, G.H.; Phillips, R.J.; Russell, C.T.; Schubert, G.; Shapiro, I.I.
1977-01-01
Present ideas about the surface and interior of Venus are based on data obtained from (1) Earth-based radio and radar: temperature, rotation, shape, and topography; (2) fly-by and orbiting spacecraft: gravity and magnetic fields; and (3) landers: winds, local structure, gamma radiation. Surface features, including large basins, crater-like depressions, and a linear valley, have been recognized from recent ground-based radar images. Pictures of the surface acquired by the USSR's Venera 9 and 10 show abundant boulders and apparent wind erosion. On the Pioneer Venus 1978 Orbiter mission, the radar mapper experiment will determine surface heights, dielectric constant values and small-scale slope values along the sub-orbital track between 50??S and 75??N. This experiment will also estimate the global shape and provide coarse radar images (40-80 km identification resolution) of part of the surface. Gravity data will be obtained by radio tracking. Maps combining radar altimetry with spacecraft and ground-based images will be made. A fluxgate magnetometer will measure the magnetic fields around Venus. The radar and gravity data will provide clues to the level of crustal differentiation and tectonic activity. The magnetometer will determine the field variations accurately. Data from the combined experiments may constrain the dynamo mechanism; if so, a deeper understanding of both Venus and Earth will be gained. ?? 1977 D. Reidel Publishing Company.
NASA Astrophysics Data System (ADS)
Cheng, Xu; Jin, Xin; Zhang, Zhijing; Lu, Jun
2014-01-01
In order to improve the accuracy of geometrical defect detection, this paper presented a method based on HU moment invariants of skeleton image. This method have four steps: first of all, grayscale images of non-silicon MEMS parts are collected and converted into binary images, secondly, skeletons of binary images are extracted using medialaxis- transform method, and then HU moment invariants of skeleton images are calculated, finally, differences of HU moment invariants between measured parts and qualified parts are obtained to determine whether there are geometrical defects. To demonstrate the availability of this method, experiments were carried out between skeleton images and grayscale images, and results show that: when defects of non-silicon MEMS part are the same, HU moment invariants of skeleton images are more sensitive than that of grayscale images, and detection accuracy is higher. Therefore, this method can more accurately determine whether non-silicon MEMS parts qualified or not, and can be applied to nonsilicon MEMS part detection system.
Zschaeck, Sebastian; Lohaus, Fabian; Beck, Marcus; Habl, Gregor; Kroeze, Stephanie; Zamboglou, Constantinos; Koerber, Stefan Alexander; Debus, Jürgen; Hölscher, Tobias; Wust, Peter; Ganswindt, Ute; Baur, Alexander D J; Zöphel, Klaus; Cihoric, Nikola; Guckenberger, Matthias; Combs, Stephanie E; Grosu, Anca Ligia; Ghadjar, Pirus; Belka, Claus
2018-05-11
68 Gallium prostate specific membrane antigen (PSMA) ligand positron emission tomography (PET) is an increasingly used imaging modality in prostate cancer, especially in cases of tumor recurrence after curative intended therapy. Owed to the novelty of the PSMA-targeting tracers, clinical evidence on the value of PSMA-PET is moderate but rapidly increasing. State of the art imaging is pivotal for radiotherapy treatment planning as it may affect dose prescription, target delineation and use of concomitant therapy.This review summarizes the evidence on PSMA-PET imaging from a radiation oncologist's point of view. Additionally a short survey containing twelve examples of patients and 6 additional questions was performed in seven mayor academic centers with experience in PSMA ligand imaging and the findings are reported here.
Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors
Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung
2017-01-01
Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods. PMID:28587269
Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.
Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung
2017-06-06
Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.
NASA Astrophysics Data System (ADS)
Liu, Zhanwen; Feng, Yan; Chen, Hang; Jiao, Licheng
2017-10-01
A novel and effective image fusion method is proposed for creating a highly informative and smooth surface of fused image through merging visible and infrared images. Firstly, a two-scale non-subsampled shearlet transform (NSST) is employed to decompose the visible and infrared images into detail layers and one base layer. Then, phase congruency is adopted to extract the saliency maps from the detail layers and a guided filtering is proposed to compute the filtering output of base layer and saliency maps. Next, a novel weighted average technique is used to make full use of scene consistency for fusion and obtaining coefficients map. Finally the fusion image was acquired by taking inverse NSST of the fused coefficients map. Experiments show that the proposed approach can achieve better performance than other methods in terms of subjective visual effect and objective assessment.
Non-invasive imaging using reporter genes altering cellular water permeability
NASA Astrophysics Data System (ADS)
Mukherjee, Arnab; Wu, Di; Davis, Hunter C.; Shapiro, Mikhail G.
2016-12-01
Non-invasive imaging of gene expression in live, optically opaque animals is important for multiple applications, including monitoring of genetic circuits and tracking of cell-based therapeutics. Magnetic resonance imaging (MRI) could enable such monitoring with high spatiotemporal resolution. However, existing MRI reporter genes based on metalloproteins or chemical exchange probes are limited by their reliance on metals or relatively low sensitivity. Here we introduce a new class of MRI reporters based on the human water channel aquaporin 1. We show that aquaporin overexpression produces contrast in diffusion-weighted MRI by increasing tissue water diffusivity without affecting viability. Low aquaporin levels or mixed populations comprising as few as 10% aquaporin-expressing cells are sufficient to produce MRI contrast. We characterize this new contrast mechanism through experiments and simulations, and demonstrate its utility in vivo by imaging gene expression in tumours. Our results establish an alternative class of sensitive, metal-free reporter genes for non-invasive imaging.
Degraded Chinese rubbing images thresholding based on local first-order statistics
NASA Astrophysics Data System (ADS)
Wang, Fang; Hou, Ling-Ying; Huang, Han
2017-06-01
It is a necessary step for Chinese character segmentation from degraded document images in Optical Character Recognizer (OCR); however, it is challenging due to various kinds of noising in such an image. In this paper, we present three local first-order statistics method that had been adaptive thresholding for segmenting text and non-text of Chinese rubbing image. Both visual inspection and numerically investigate for the segmentation results of rubbing image had been obtained. In experiments, it obtained better results than classical techniques in the binarization of real Chinese rubbing image and PHIBD 2012 datasets.
NASA Astrophysics Data System (ADS)
Peichl, Markus; Dill, Stephan; Jirousek, Matthias; Süß, Helmut
2009-05-01
Passive microwave imaging allows a daytime independent observation and examination of objects and persons without artificial exposure under nearly all weather conditions. The penetration capability of microwaves allows the detection of hidden objects like weapons and explosive devices under the clothing. In August/September 2008 a comprehensive military experiment was conducted by the German armed forces at the naval base Eckernfoerde, Germany. One activity in the Eckernfoerde trial was the simulation of a military entrance portal by a tent including various imaging and a chemical sensor suite. Besides commercial optical and infrared cameras various passive millimeter-wave imagers have been used from different German research institutions. The DLR Microwaves and Radar Institute, Department for Reconnaissance and Security (HR-AS), provided an imaging radiometer scanner operating at W band. A multitude of situations have been simulated and many persons carrying hidden objects under their clothing have been scanned. Some exemplary results from the trial are shown and discussed in the paper.
Imaging model for the scintillator and its application to digital radiography image enhancement.
Wang, Qian; Zhu, Yining; Li, Hongwei
2015-12-28
Digital Radiography (DR) images obtained by OCD-based (optical coupling detector) Micro-CT system usually suffer from low contrast. In this paper, a mathematical model is proposed to describe the image formation process in scintillator. By solving the correlative inverse problem, the quality of DR images is improved, i.e. higher contrast and spatial resolution. By analyzing the radiative transfer process of visible light in scintillator, scattering is recognized as the main factor leading to low contrast. Moreover, involved blurring effect is also concerned and described as point spread function (PSF). Based on these physical processes, the scintillator imaging model is then established. When solving the inverse problem, pre-correction to the intensity of x-rays, dark channel prior based haze removing technique, and an effective blind deblurring approach are employed. Experiments on a variety of DR images show that the proposed approach could improve the contrast of DR images dramatically as well as eliminate the blurring vision effectively. Compared with traditional contrast enhancement methods, such as CLAHE, our method could preserve the relative absorption values well.
Peng, Jiaxin; Qu, Chen; Gu, Ruolei; Luo, Yue-Jia
2012-01-01
Previous emotion-regulation research has shown that the late positive potential (LPP) is sensitive to the down-regulation of emotion; however, whether LPP is also sensitive to the up-regulation of emotion remains unclear. The present study examined the description-based reappraisal effects on the up-regulation of positive emotions induced by erotic and neutral images in a Chinese population. Self-reported ratings and event-related potential (ERP) were recorded when subjects viewed pleasant and neutral images, which were shown after either a neutral or positive description. Self-reported results showed that images following positive descriptions were rated as more pleasant compared to images following neutral descriptions. ERP results revealed that the P2, P3, and slow wave (SW) components were larger for erotic pictures than for neutral pictures, while the positive description condition yielded attenuated erotic image-induced P2, P3 and SW and increased SW induced by neutral images. The results demonstrated that description-based reappraisal, as a method of reappraisal, significantly modulates the emotional experience and ERP responses to erotic and neutral images.
NASA Astrophysics Data System (ADS)
Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying
2018-03-01
In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.
Peng, Jiaxin; Qu, Chen; Gu, Ruolei; Luo, Yue-Jia
2013-01-01
Previous emotion-regulation research has shown that the late positive potential (LPP) is sensitive to the down-regulation of emotion; however, whether LPP is also sensitive to the up-regulation of emotion remains unclear. The present study examined the description-based reappraisal effects on the up-regulation of positive emotions induced by erotic and neutral images in a Chinese population. Self-reported ratings and event-related potential (ERP) were recorded when subjects viewed pleasant and neutral images, which were shown after either a neutral or positive description. Self-reported results showed that images following positive descriptions were rated as more pleasant compared to images following neutral descriptions. ERP results revealed that the P2, P3, and slow wave (SW) components were larger for erotic pictures than for neutral pictures, while the positive description condition yielded attenuated erotic image-induced P2, P3 and SW and increased SW induced by neutral images. The results demonstrated that description-based reappraisal, as a method of reappraisal, significantly modulates the emotional experience and ERP responses to erotic and neutral images. PMID:23335894
NASA Astrophysics Data System (ADS)
Huang, Zhenghua; Zhang, Tianxu; Deng, Lihua; Fang, Hao; Li, Qian
2015-12-01
Total variation(TV) based on regularization has been proven as a popular and effective model for image restoration, because of its ability of edge preserved. However, as the TV favors a piece-wise constant solution, the processing results in the flat regions of the image are easily produced "staircase effects", and the amplitude of the edges will be underestimated; the underlying cause of the problem is that the regularization parameter can not be changeable with spatial local information of image. In this paper, we propose a novel Scatter-matrix eigenvalues-based TV(SMETV) regularization with image blind restoration algorithm for deblurring medical images. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.
Supervised learning of tools for content-based search of image databases
NASA Astrophysics Data System (ADS)
Delanoy, Richard L.
1996-03-01
A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.
Eye gazing direction inspection based on image processing technique
NASA Astrophysics Data System (ADS)
Hao, Qun; Song, Yong
2005-02-01
According to the research result in neural biology, human eyes can obtain high resolution only at the center of view of field. In the research of Virtual Reality helmet, we design to detect the gazing direction of human eyes in real time and feed it back to the control system to improve the resolution of the graph at the center of field of view. In the case of current display instruments, this method can both give attention to the view field of virtual scene and resolution, and improve the immersion of virtual system greatly. Therefore, detecting the gazing direction of human eyes rapidly and exactly is the basis of realizing the design scheme of this novel VR helmet. In this paper, the conventional method of gazing direction detection that based on Purklinje spot is introduced firstly. In order to overcome the disadvantage of the method based on Purklinje spot, this paper proposed a method based on image processing to realize the detection and determination of the gazing direction. The locations of pupils and shapes of eye sockets change with the gazing directions. With the aid of these changes, analyzing the images of eyes captured by the cameras, gazing direction of human eyes can be determined finally. In this paper, experiments have been done to validate the efficiency of this method by analyzing the images. The algorithm can carry out the detection of gazing direction base on normal eye image directly, and it eliminates the need of special hardware. Experiment results show that the method is easy to implement and have high precision.
Quantitative analysis of single-molecule superresolution images
Coltharp, Carla; Yang, Xinxing; Xiao, Jie
2014-01-01
This review highlights the quantitative capabilities of single-molecule localization-based superresolution imaging methods. In addition to revealing fine structural details, the molecule coordinate lists generated by these methods provide the critical ability to quantify the number, clustering, and colocalization of molecules with 10 – 50 nm resolution. Here we describe typical workflows and precautions for quantitative analysis of single-molecule superresolution images. These guidelines include potential pitfalls and essential control experiments, allowing critical assessment and interpretation of superresolution images. PMID:25179006
Research on Method of Interactive Segmentation Based on Remote Sensing Images
NASA Astrophysics Data System (ADS)
Yang, Y.; Li, H.; Han, Y.; Yu, F.
2017-09-01
In this paper, we aim to solve the object extraction problem in remote sensing images using interactive segmentation tools. Firstly, an overview of the interactive segmentation algorithm is proposed. Then, our detailed implementation of intelligent scissors and GrabCut for remote sensing images is described. Finally, several experiments on different typical features (water area, vegetation) in remote sensing images are performed respectively. Compared with the manual result, it indicates that our tools maintain good feature boundaries and show good performance.
NASA Astrophysics Data System (ADS)
Mansoor, Awais; Robinson, J. Paul; Rajwa, Bartek
2009-02-01
Modern automated microscopic imaging techniques such as high-content screening (HCS), high-throughput screening, 4D imaging, and multispectral imaging are capable of producing hundreds to thousands of images per experiment. For quick retrieval, fast transmission, and storage economy, these images should be saved in a compressed format. A considerable number of techniques based on interband and intraband redundancies of multispectral images have been proposed in the literature for the compression of multispectral and 3D temporal data. However, these works have been carried out mostly in the elds of remote sensing and video processing. Compression for multispectral optical microscopy imaging, with its own set of specialized requirements, has remained under-investigated. Digital photography{oriented 2D compression techniques like JPEG (ISO/IEC IS 10918-1) and JPEG2000 (ISO/IEC 15444-1) are generally adopted for multispectral images which optimize visual quality but do not necessarily preserve the integrity of scientic data, not to mention the suboptimal performance of 2D compression techniques in compressing 3D images. Herein we report our work on a new low bit-rate wavelet-based compression scheme for multispectral fluorescence biological imaging. The sparsity of signicant coefficients in high-frequency subbands of multispectral microscopic images is found to be much greater than in natural images; therefore a quad-tree concept such as Said et al.'s SPIHT1 along with correlation of insignicant wavelet coefficients has been proposed to further exploit redundancy at high-frequency subbands. Our work propose a 3D extension to SPIHT, incorporating a new hierarchal inter- and intra-spectral relationship amongst the coefficients of 3D wavelet-decomposed image. The new relationship, apart from adopting the parent-child relationship of classical SPIHT, also brought forth the conditional "sibling" relationship by relating only the insignicant wavelet coefficients of subbands at the same level of decomposition. The insignicant quadtrees in dierent subbands in the high-frequency subband class are coded by a combined function to reduce redundancy. A number of experiments conducted on microscopic multispectral images have shown promising results for the proposed method over current state-of-the-art image-compression techniques.
Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
Liu, Haoting; Zhou, Qianxiang; Yang, Jin; Jiang, Ting; Liu, Zhizhen; Li, Jie
2017-01-01
An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes. PMID:28208781
Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback.
Liu, Haoting; Zhou, Qianxiang; Yang, Jin; Jiang, Ting; Liu, Zhizhen; Li, Jie
2017-02-09
An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes.
The Interactive Origin and the Aesthetic Modelling of Image-Schemas and Primary Metaphors.
Martínez, Isabel C; Español, Silvia A; Pérez, Diana I
2018-06-02
According to the theory of conceptual metaphor, image-schemas and primary metaphors are preconceptual structures configured in human cognition, based on sensory-motor environmental activity. Focusing on the way both non-conceptual structures are embedded in early social interaction, we provide empirical evidence for the interactive and intersubjective ontogenesis of image-schemas and primary metaphors. We present the results of a multimodal image-schematic microanalysis of three interactive infant-directed performances (the composition of movement, touch, speech, and vocalization that adults produce for-and-with the infants). The microanalyses show that adults aesthetically highlight the image-schematic structures embedded in the multimodal composition of the performance, and that primary metaphors are also lived as embedded in these inter-enactive experiences. The findings allow corroborating that the psychological domains of cognition and affection are not in rivalry or conflict but rather intertwined in meaningful experiences.
NASA Astrophysics Data System (ADS)
Gustafsson, Alexander; Okabayashi, Norio; Peronio, Angelo; Giessibl, Franz J.; Paulsson, Magnus
2017-08-01
We describe a first-principles method to calculate scanning tunneling microscopy (STM) images, and compare the results to well-characterized experiments combining STM with atomic force microscopy (AFM). The theory is based on density functional theory with a localized basis set, where the wave functions in the vacuum gap are computed by propagating the localized-basis wave functions into the gap using a real-space grid. Constant-height STM images are computed using Bardeen's approximation method, including averaging over the reciprocal space. We consider copper adatoms and single CO molecules adsorbed on Cu(111), scanned with a single-atom copper tip with and without CO functionalization. The calculated images agree with state-of-the-art experiments, where the atomic structure of the tip apex is determined by AFM. The comparison further allows for detailed interpretation of the STM images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deng, J.
This imaging educational program will focus on solutions to common pediatric image quality optimization challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. One of the most commonly encountered pediatric imaging requirements for the non-specialist hospital is pediatric CT in the emergency room setting. Thus, this educational program will begin with optimization of pediatric CT in the emergency department. Though pediatric cardiovascular MRI may be less common in the non-specialist hospitals, low pediatric volumes and unique cardiovascular anatomy make optimization of these techniques difficult. Therefore, our second speaker willmore » review best practices in pediatric cardiovascular MRI based on experiences from a children’s hospital with a large volume of cardiac patients. Learning Objectives: To learn techniques for optimizing radiation dose and image quality for CT of children in the emergency room setting. To learn solutions for consistently high quality cardiovascular MRI of children.« less
Iterative Nonlocal Total Variation Regularization Method for Image Restoration
Xu, Huanyu; Sun, Quansen; Luo, Nan; Cao, Guo; Xia, Deshen
2013-01-01
In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed. Experiment results show that the proposed algorithms outperform some other regularization methods. PMID:23776560
Danhier, Pierre; Deumer, Gladys; Joudiou, Nicolas; Bouzin, Caroline; Levêque, Philippe; Haufroid, Vincent; Jordan, Bénédicte F.; Feron, Olivier; Sonveaux, Pierre; Gallez, Bernard
2017-01-01
Magnetic resonance imaging (MRI) cell tracking of cancer cells labeled with superparamagnetic iron oxides (SPIO) allows visualizing metastatic cells in preclinical models. However, previous works showed that the signal void induced by SPIO on T2(*)-weighted images decreased over time. Here, we aim at characterizing the fate of iron oxide nanoparticles used in cell tracking studies and the role of macrophages in SPIO metabolism. In vivo MRI cell tracking of SPIO positive 4T1 breast cancer cells revealed a quick loss of T2* contrast after injection. We next took advantage of electron paramagnetic resonance (EPR) spectroscopy and inductively coupled plasma mass spectroscopy (ICP-MS) for characterizing the evolution of superparamagnetic and non-superparamagnetic iron pools in 4T1 breast cancer cells and J774 macrophages after SPIO labeling. These in vitro experiments and histology studies performed on 4T1 tumors highlighted the quick degradation of iron oxides by macrophages in SPIO-based cell tracking experiments. In conclusion, the release of SPIO by dying cancer cells and the subsequent uptake of iron oxides by tumor macrophages are limiting factors in MRI cell tracking experiments that plead for the use of (MR) reporter-gene based imaging methods for the long-term tracking of metastatic cells. PMID:28467814
Cytology 3D structure formation based on optical microscopy images
NASA Astrophysics Data System (ADS)
Pronichev, A. N.; Polyakov, E. V.; Shabalova, I. P.; Djangirova, T. V.; Zaitsev, S. M.
2017-01-01
The article the article is devoted to optimization of the parameters of imaging of biological preparations in optical microscopy using a multispectral camera in visible range of electromagnetic radiation. A model for the image forming of virtual preparations was proposed. The optimum number of layers was determined for the object scan in depth and holistic perception of its switching according to the results of the experiment.
Integrated framework for developing search and discrimination metrics
NASA Astrophysics Data System (ADS)
Copeland, Anthony C.; Trivedi, Mohan M.
1997-06-01
This paper presents an experimental framework for evaluating target signature metrics as models of human visual search and discrimination. This framework is based on a prototype eye tracking testbed, the Integrated Testbed for Eye Movement Studies (ITEMS). ITEMS determines an observer's visual fixation point while he studies a displayed image scene, by processing video of the observer's eye. The utility of this framework is illustrated with an experiment using gray-scale images of outdoor scenes that contain randomly placed targets. Each target is a square region of a specific size containing pixel values from another image of an outdoor scene. The real-world analogy of this experiment is that of a military observer looking upon the sensed image of a static scene to find camouflaged enemy targets that are reported to be in the area. ITEMS provides the data necessary to compute various statistics for each target to describe how easily the observers located it, including the likelihood the target was fixated or identified and the time required to do so. The computed values of several target signature metrics are compared to these statistics, and a second-order metric based on a model of image texture was found to be the most highly correlated.
A new FOD recognition algorithm based on multi-source information fusion and experiment analysis
NASA Astrophysics Data System (ADS)
Li, Yu; Xiao, Gang
2011-08-01
Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.
NASA Astrophysics Data System (ADS)
Xia, Wenze; Ma, Yayun; Han, Shaokun; Wang, Yulin; Liu, Fei; Zhai, Yu
2018-06-01
One of the most important goals of research on three-dimensional nonscanning laser imaging systems is the improvement of the illumination system. In this paper, a new three-dimensional nonscanning laser imaging system based on the illumination pattern of a point-light-source array is proposed. This array is obtained using a fiber array connected to a laser array with each unit laser having independent control circuits. This system uses a point-to-point imaging process, which is realized using the exact corresponding optical relationship between the point-light-source array and a linear-mode avalanche photodiode array detector. The complete working process of this system is explained in detail, and the mathematical model of this system containing four equations is established. A simulated contrast experiment and two real contrast experiments which use the simplified setup without a laser array are performed. The final results demonstrate that unlike a conventional three-dimensional nonscanning laser imaging system, the proposed system meets all the requirements of an eligible illumination system. Finally, the imaging performance of this system is analyzed under defocusing situations, and analytical results show that the system has good defocusing robustness and can be easily adjusted in real applications.
Hybrid statistics-simulations based method for atom-counting from ADF STEM images.
De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra
2017-06-01
A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Xu, Jing; Wu, Jian; Feng, Daming; Cui, Zhiming
Serious types of vascular diseases such as carotid stenosis, aneurysm and vascular malformation may lead to brain stroke, which are the third leading cause of death and the number one cause of disability. In the clinical practice of diagnosis and treatment of cerebral vascular diseases, how to do effective detection and description of the vascular structure of two-dimensional angiography sequence image that is blood vessel skeleton extraction has been a difficult study for a long time. This paper mainly discussed two-dimensional image of blood vessel skeleton extraction based on the level set method, first do the preprocessing to the DSA image, namely uses anti-concentration diffusion model for the effective enhancement and uses improved Otsu local threshold segmentation technology based on regional division for the image binarization, then vascular skeleton extraction based on GMM (Group marching method) with fast sweeping theory was actualized. Experiments show that our approach not only improved the time complexity, but also make a good extraction results.
Multi-focus image fusion based on window empirical mode decomposition
NASA Astrophysics Data System (ADS)
Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao
2017-09-01
In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.
de Groot, Reinoud; Lüthi, Joel; Lindsay, Helen; Holtackers, René; Pelkmans, Lucas
2018-01-23
High-content imaging using automated microscopy and computer vision allows multivariate profiling of single-cell phenotypes. Here, we present methods for the application of the CISPR-Cas9 system in large-scale, image-based, gene perturbation experiments. We show that CRISPR-Cas9-mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image-based phenotyping. We developed a pipeline to construct a large-scale arrayed library of 2,281 sequence-verified CRISPR-Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine-learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in-depth characterization of gene perturbation effects. This approach enables genome-scale image-based multivariate gene perturbation profiling using CRISPR-Cas9. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.
Femtosecond imaging of nonlinear acoustics in gold.
Pezeril, Thomas; Klieber, Christoph; Shalagatskyi, Viktor; Vaudel, Gwenaelle; Temnov, Vasily; Schmidt, Oliver G; Makarov, Denys
2014-02-24
We have developed a high-sensitivity, low-noise femtosecond imaging technique based on pump-probe time-resolved measurements with a standard CCD camera. The approach used in the experiment is based on lock-in acquisitions of images generated by a femtosecond laser probe synchronized to modulation of a femtosecond laser pump at the same rate. This technique allows time-resolved imaging of laser-excited phenomena with femtosecond time resolution. We illustrate the technique by time-resolved imaging of the nonlinear reshaping of a laser-excited picosecond acoustic pulse after propagation through a thin gold layer. Image analysis reveals the direct 2D visualization of the nonlinear acoustic propagation of the picosecond acoustic pulse. Many ultrafast pump-probe investigations can profit from this technique because of the wealth of information it provides over a typical single diode and lock-in amplifier setup, for example it can be used to image ultrasonic echoes in biological samples.
Gutman, David A.; Dunn, William D.; Cobb, Jake; Stoner, Richard M.; Kalpathy-Cramer, Jayashree; Erickson, Bradley
2014-01-01
Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance. PMID:24904399
Multi-viewpoint Image Array Virtual Viewpoint Rapid Generation Algorithm Based on Image Layering
NASA Astrophysics Data System (ADS)
Jiang, Lu; Piao, Yan
2018-04-01
The use of multi-view image array combined with virtual viewpoint generation technology to record 3D scene information in large scenes has become one of the key technologies for the development of integrated imaging. This paper presents a virtual viewpoint rendering method based on image layering algorithm. Firstly, the depth information of reference viewpoint image is quickly obtained. During this process, SAD is chosen as the similarity measure function. Then layer the reference image and calculate the parallax based on the depth information. Through the relative distance between the virtual viewpoint and the reference viewpoint, the image layers are weighted and panned. Finally the virtual viewpoint image is rendered layer by layer according to the distance between the image layers and the viewer. This method avoids the disadvantages of the algorithm DIBR, such as high-precision requirements of depth map and complex mapping operations. Experiments show that, this algorithm can achieve the synthesis of virtual viewpoints in any position within 2×2 viewpoints range, and the rendering speed is also very impressive. The average result proved that this method can get satisfactory image quality. The average SSIM value of the results relative to real viewpoint images can reaches 0.9525, the PSNR value can reaches 38.353 and the image histogram similarity can reaches 93.77%.
Image standards in tissue-based diagnosis (diagnostic surgical pathology).
Kayser, Klaus; Görtler, Jürgen; Goldmann, Torsten; Vollmer, Ekkehard; Hufnagl, Peter; Kayser, Gian
2008-04-18
Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis. To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology. THEORY AND EXPERIENCES: Images used in tissue-based diagnosis present with pathology-specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease-image combination, human-diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image acquisition systems (resolution, colour temperature, focus, brightness, and quality evaluation procedures), display resolution data, implemented image formats, storage, cycle frequency, backup procedures, operation system, and external system accessibility. The lowest third level describes the permitted limits and threshold in detail. At present, an applicable standard including all mentioned features does not exist to our knowledge; some aspects can be taken from radiological standards (PACS, DICOM 3); others require specific solutions or are not covered yet. The progress in virtual microscopy and application of artificial intelligence (AI) in tissue-based diagnosis demands fast preparation and implementation of an internationally acceptable standard. The described hierarchic order as well as analytic investigation in all potentially necessary aspects and details offers an appropriate tool to specifically determine standardized requirements.
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.
Image fusion based on millimeter-wave for concealed weapon detection
NASA Astrophysics Data System (ADS)
Zhu, Weiwen; Zhao, Yuejin; Deng, Chao; Zhang, Cunlin; Zhang, Yalin; Zhang, Jingshui
2010-11-01
This paper describes a novel multi sensors image fusion technology which is presented for concealed weapon detection (CWD). It is known to all, because of the good transparency of the clothes at millimeter wave band, a millimeter wave radiometer can be used to image and distinguish concealed contraband beneath clothes, for example guns, knives, detonator and so on. As a result, we adopt the passive millimeter wave (PMMW) imaging technology for airport security. However, in consideration of the wavelength of millimeter wave and the single channel mechanical scanning, the millimeter wave image has law optical resolution, which can't meet the need of practical application. Therefore, visible image (VI), which has higher resolution, is proposed for the image fusion with the millimeter wave image to enhance the readability. Before the image fusion, a novel image pre-processing which specifics to the fusion of millimeter wave imaging and visible image is adopted. And in the process of image fusion, multi resolution analysis (MRA) based on Wavelet Transform (WT) is adopted. In this way, the experiment result shows that this method has advantages in concealed weapon detection and has practical significance.
Multistage morphological segmentation of bright-field and fluorescent microscopy images
NASA Astrophysics Data System (ADS)
Korzyńska, A.; Iwanowski, M.
2012-06-01
This paper describes the multistage morphological segmentation method (MSMA) for microscopic cell images. The proposed method enables us to study the cell behaviour by using a sequence of two types of microscopic images: bright field images and/or fluorescent images. The proposed method is based on two types of information: the cell texture coming from the bright field images and intensity of light emission, done by fluorescent markers. The method is dedicated to the image sequences segmentation and it is based on mathematical morphology methods supported by other image processing techniques. The method allows for detecting cells in image independently from a degree of their flattening and from presenting structures which produce the texture. It makes use of some synergic information from the fluorescent light emission image as the support information. The MSMA method has been applied to images acquired during the experiments on neural stem cells as well as to artificial images. In order to validate the method, two types of errors have been considered: the error of cell area detection and the error of cell position using artificial images as the "gold standard".
NASA Astrophysics Data System (ADS)
Zhang, Wei; Wang, Yanan; Zhu, Zhenhao; Su, Jinhui
2018-05-01
A focused plenoptic camera can effectively transform angular and spatial information to yield a refocused rendered image with high resolution. However, choosing a proper patch size poses a significant problem for the image-rendering algorithm. By using a spatial frequency response measurement, a method to obtain a suitable patch size is presented. By evaluating the spatial frequency response curves, the optimized patch size can be obtained quickly and easily. Moreover, the range of depth over which images can be rendered without artifacts can be estimated. Experiments show that the results of the image rendered based on frequency response measurement are in accordance with the theoretical calculation, which indicates that this is an effective way to determine the patch size. This study may provide support to light-field image rendering.
Automated recognition and characterization of solar active regions based on the SOHO/MDI images
NASA Technical Reports Server (NTRS)
Pap, J. M.; Turmon, M.; Mukhtar, S.; Bogart, R.; Ulrich, R.; Froehlich, C.; Wehrli, C.
1997-01-01
The first results of a new method to identify and characterize the various surface structures on the sun, which may contribute to the changes in solar total and spectral irradiance, are shown. The full disk magnetograms (1024 x 1024 pixels) of the Michelson Doppler Imager (MDI) experiment onboard SOHO are analyzed. Use of a Bayesian inference scheme allows objective, uniform, automated processing of a long sequence of images. The main goal is to identify the solar magnetic features causing irradiance changes. The results presented are based on a pilot time interval of August 1996.
Optimized feature-detection for on-board vision-based surveillance
NASA Astrophysics Data System (ADS)
Gond, Laetitia; Monnin, David; Schneider, Armin
2012-06-01
The detection and matching of robust features in images is an important step in many computer vision applications. In this paper, the importance of the keypoint detection algorithms and their inherent parameters in the particular context of an image-based change detection system for IED detection is studied. Through extensive application-oriented experiments, we draw an evaluation and comparison of the most popular feature detectors proposed by the computer vision community. We analyze how to automatically adjust these algorithms to changing imaging conditions and suggest improvements in order to achieve more exibility and robustness in their practical implementation.
Computer-aided light sheet flow visualization using photogrammetry
NASA Technical Reports Server (NTRS)
Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.
1994-01-01
A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and a visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) results, was chosen to interactively display the reconstructed light sheet images with the numerical surface geometry for the model or aircraft under study. The photogrammetric reconstruction technique and the image processing and computer graphics techniques and equipment are described. Results of the computer-aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images with CFD solutions in the same graphics environment is also demonstrated.
Computer-Aided Light Sheet Flow Visualization
NASA Technical Reports Server (NTRS)
Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.
1993-01-01
A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.
IDEAL: Images Across Domains, Experiments, Algorithms and Learning
NASA Astrophysics Data System (ADS)
Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao
2016-11-01
Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.
Computer-aided light sheet flow visualization
NASA Technical Reports Server (NTRS)
Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.
1993-01-01
A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.
MR image denoising method for brain surface 3D modeling
NASA Astrophysics Data System (ADS)
Zhao, De-xin; Liu, Peng-jie; Zhang, De-gan
2014-11-01
Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.
Automated seamline detection along skeleton for remote sensing image mosaicking
NASA Astrophysics Data System (ADS)
Zhang, Hansong; Chen, Jianyu; Liu, Xin
2015-08-01
The automatic generation of seamline along the overlap region skeleton is a concerning problem for the mosaicking of Remote Sensing(RS) images. Along with the improvement of RS image resolution, it is necessary to ensure rapid and accurate processing under complex conditions. So an automated seamline detection method for RS image mosaicking based on image object and overlap region contour contraction is introduced. By this means we can ensure universality and efficiency of mosaicking. The experiments also show that this method can select seamline of RS images with great speed and high accuracy over arbitrary overlap regions, and realize RS image rapid mosaicking in surveying and mapping production.
Image Transform Based on the Distribution of Representative Colors for Color Deficient
NASA Astrophysics Data System (ADS)
Ohata, Fukashi; Kudo, Hiroaki; Matsumoto, Tetsuya; Takeuchi, Yoshinori; Ohnishi, Noboru
This paper proposes the method to convert digital image containing distinguishing difficulty sets of colors into the image with high visibility. We set up four criteria, automatically processing by a computer, retaining continuity in color space, not making images into lower visible for people with normal color vision, and not making images not originally having distinguishing difficulty sets of colors into lower visible. We conducted the psychological experiment. We obtained the result that the visibility of a converted image had been improved at 60% for 40 images, and we confirmed the main criterion of the continuity in color space was kept.
NASA Astrophysics Data System (ADS)
Liu, Sijia; Sa, Ruhan; Maguire, Orla; Minderman, Hans; Chaudhary, Vipin
2015-03-01
Cytogenetic abnormalities are important diagnostic and prognostic criteria for acute myeloid leukemia (AML). A flow cytometry-based imaging approach for FISH in suspension (FISH-IS) was established that enables the automated analysis of several log-magnitude higher number of cells compared to the microscopy-based approaches. The rotational positioning can occur leading to discordance between spot count. As a solution of counting error from overlapping spots, in this study, a Gaussian Mixture Model based classification method is proposed. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) of GMM are used as global image features of this classification method. Via Random Forest classifier, the result shows that the proposed method is able to detect closely overlapping spots which cannot be separated by existing image segmentation based spot detection methods. The experiment results show that by the proposed method we can obtain a significant improvement in spot counting accuracy.
Image fusion algorithm based on energy of Laplacian and PCNN
NASA Astrophysics Data System (ADS)
Li, Meili; Wang, Hongmei; Li, Yanjun; Zhang, Ke
2009-12-01
Owing to the global coupling and pulse synchronization characteristic of pulse coupled neural networks (PCNN), it has been proved to be suitable for image processing and successfully employed in image fusion. However, in almost all the literatures of image processing about PCNN, linking strength of each neuron is assigned the same value which is chosen by experiments. This is not consistent with the human vision system in which the responses to the region with notable features are stronger than that to the region with nonnotable features. It is more reasonable that notable features, rather than the same value, are employed to linking strength of each neuron. As notable feature, energy of Laplacian (EOL) is used to obtain the value of linking strength in PCNN in this paper. Experimental results demonstrate that the proposed algorithm outperforms Laplacian-based, wavelet-based, PCNN -based fusion algorithms.
Optimization of the scan protocols for CT-based material extraction in small animal PET/CT studies
NASA Astrophysics Data System (ADS)
Yang, Ching-Ching; Yu, Jhih-An; Yang, Bang-Hung; Wu, Tung-Hsin
2013-12-01
We investigated the effects of scan protocols on CT-based material extraction to minimize radiation dose while maintaining sufficient image information in small animal studies. The phantom simulation experiments were performed with the high dose (HD), medium dose (MD) and low dose (LD) protocols at 50, 70 and 80 kVp with varying mA s. The reconstructed CT images were segmented based on Hounsfield unit (HU)-physical density (ρ) calibration curves and the dual-energy CT-based (DECT) method. Compared to the (HU;ρ) method performed on CT images acquired with the 80 kVp HD protocol, a 2-fold improvement in segmentation accuracy and a 7.5-fold reduction in radiation dose were observed when the DECT method was performed on CT images acquired with the 50/80 kVp LD protocol, showing the possibility to reduce radiation dose while achieving high segmentation accuracy.
An acceleration system for Laplacian image fusion based on SoC
NASA Astrophysics Data System (ADS)
Gao, Liwen; Zhao, Hongtu; Qu, Xiujie; Wei, Tianbo; Du, Peng
2018-04-01
Based on the analysis of Laplacian image fusion algorithm, this paper proposes a partial pipelining and modular processing architecture, and a SoC based acceleration system is implemented accordingly. Full pipelining method is used for the design of each module, and modules in series form the partial pipelining with unified data formation, which is easy for management and reuse. Integrated with ARM processor, DMA and embedded bare-mental program, this system achieves 4 layers of Laplacian pyramid on the Zynq-7000 board. Experiments show that, with small resources consumption, a couple of 256×256 images can be fused within 1ms, maintaining a fine fusion effect at the same time.
Deep learning and non-negative matrix factorization in recognition of mammograms
NASA Astrophysics Data System (ADS)
Swiderski, Bartosz; Kurek, Jaroslaw; Osowski, Stanislaw; Kruk, Michal; Barhoumi, Walid
2017-02-01
This paper presents novel approach to the recognition of mammograms. The analyzed mammograms represent the normal and breast cancer (benign and malignant) cases. The solution applies the deep learning technique in image recognition. To obtain increased accuracy of classification the nonnegative matrix factorization and statistical self-similarity of images are applied. The images reconstructed by using these two approaches enrich the data base and thanks to this improve of quality measures of mammogram recognition (increase of accuracy, sensitivity and specificity). The results of numerical experiments performed on large DDSM data base containing more than 10000 mammograms have confirmed good accuracy of class recognition, exceeding the best results reported in the actual publications for this data base.
Local reconstruction in computed tomography of diffraction enhanced imaging
NASA Astrophysics Data System (ADS)
Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia
2007-07-01
Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.
The Cortex Transform as an image preprocessor for sparse distributed memory: An initial study
NASA Technical Reports Server (NTRS)
Olshausen, Bruno; Watson, Andrew
1990-01-01
An experiment is described which was designed to evaluate the use of the Cortex Transform as an image processor for Sparse Distributed Memory (SDM). In the experiment, a set of images were injected with Gaussian noise, preprocessed with the Cortex Transform, and then encoded into bit patterns. The various spatial frequency bands of the Cortex Transform were encoded separately so that they could be evaluated based on their ability to properly cluster patterns belonging to the same class. The results of this study indicate that by simply encoding the low pass band of the Cortex Transform, a very suitable input representation for the SDM can be achieved.
Cone Beam X-Ray Luminescence Tomography Imaging Based on KA-FEM Method for Small Animals.
Chen, Dongmei; Meng, Fanzhen; Zhao, Fengjun; Xu, Cao
2016-01-01
Cone beam X-ray luminescence tomography can realize fast X-ray luminescence tomography imaging with relatively low scanning time compared with narrow beam X-ray luminescence tomography. However, cone beam X-ray luminescence tomography suffers from an ill-posed reconstruction problem. First, the feasibility of experiments with different penetration and multispectra in small animal has been tested using nanophosphor material. Then, the hybrid reconstruction algorithm with KA-FEM method has been applied in cone beam X-ray luminescence tomography for small animals to overcome the ill-posed reconstruction problem, whose advantage and property have been demonstrated in fluorescence tomography imaging. The in vivo mouse experiment proved the feasibility of the proposed method.
a Region-Based Multi-Scale Approach for Object-Based Image Analysis
NASA Astrophysics Data System (ADS)
Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.
2016-06-01
Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.
Improved patch-based learning for image deblurring
NASA Astrophysics Data System (ADS)
Dong, Bo; Jiang, Zhiguo; Zhang, Haopeng
2015-05-01
Most recent image deblurring methods only use valid information found in input image as the clue to fill the deblurring region. These methods usually have the defects of insufficient prior information and relatively poor adaptiveness. Patch-based method not only uses the valid information of the input image itself, but also utilizes the prior information of the sample images to improve the adaptiveness. However the cost function of this method is quite time-consuming and the method may also produce ringing artifacts. In this paper, we propose an improved non-blind deblurring algorithm based on learning patch likelihoods. On one hand, we consider the effect of the Gaussian mixture model with different weights and normalize the weight values, which can optimize the cost function and reduce running time. On the other hand, a post processing method is proposed to solve the ringing artifacts produced by traditional patch-based method. Extensive experiments are performed. Experimental results verify that our method can effectively reduce the execution time, suppress the ringing artifacts effectively, and keep the quality of deblurred image.
Psychological reactions in women undergoing fetal magnetic resonance imaging.
Leithner, Katharina; Pörnbacher, Susanne; Assem-Hilger, Eva; Krampl, Elisabeth; Ponocny-Seliger, Elisabeth; Prayer, Daniela
2008-02-01
To investigate women's psychological reactions when undergoing fetal magnetic resonance imaging (MRI), and to estimate whether certain groups, based on clinical and sociodemographic variables, differ in their subjective experiences with fetal MRI and in their anxiety levels related to the scanning procedure. This study is a prospective cohort investigation of 62 women before and immediately after fetal MRI. Anxiety levels and subjective experiences were measured by questionnaires. Groups based on clinical and sociodemographic variables were compared with regard to anxiety levels and to the scores on the Prescan and Postscan Imaging Distress Questionnaire. Anxiety scores before fetal MRI were 8.8 points higher than those of the female, nonclinical, norm population (P<.001). The severity of the referral diagnosis showed a linearly increasing effect on anxiety level before MRI (weighted linear term: F1,59=5.325, P=.025). Magnetic resonance imaging was experienced as unpleasant by 33.9% (95% confidence interval [CI] 21.2-46.6%) and as hardly bearable by 4.8% (95% CI 0-17.5%) of the women. Physical restraint (49.9%, 95% CI 37.4-62.4%), noise level (53.2%, 95% CI 40.7-65.7%), anxiety for the infant (53.2%, 95% CI 40.7-65.7%), and the duration of the examination (51.6%, 95% CI 39.1-64.1%) were major distressing factors. Women who undergo fetal magnetic resonance imaging experience considerable distress, especially those with poor fetal prognoses. Ongoing technical developments, such as a reduction of noise, shortening the duration of the MRI, and a more comfortable position in open MRI machines, may have the potential to improve the subjective experiences of women during fetal MRI. III.
Fluid Registration of Diffusion Tensor Images Using Information Theory
Chiang, Ming-Chang; Leow, Alex D.; Klunder, Andrea D.; Dutton, Rebecca A.; Barysheva, Marina; Rose, Stephen E.; McMahon, Katie L.; de Zubicaray, Greig I.; Toga, Arthur W.; Thompson, Paul M.
2008-01-01
We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or J-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the J-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data. PMID:18390342
Interactive classification and content-based retrieval of tissue images
NASA Astrophysics Data System (ADS)
Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof
2002-11-01
We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.
Method of passive ranging from infrared image sequence based on equivalent area
NASA Astrophysics Data System (ADS)
Yang, Weiping; Shen, Zhenkang
2007-11-01
The information of range between missile and targets is important not only to missile controlling component, but also to automatic target recognition, so studying the technique of passive ranging from infrared images has important theoretic and practical meanings. Here we tried to get the range between guided missile and target and help to identify targets or dodge a hit. The issue of distance between missile and target is currently a hot and difficult research content. As all know, infrared imaging detector can not range so that it restricts the functions of the guided information processing system based on infrared images. In order to break through the technical puzzle, we investigated the principle of the infrared imaging, after analysing the imaging geometric relationship between the guided missile and the target, we brought forward the method of passive ranging based on equivalent area and provided mathematical analytic formulas. Validating Experiments demonstrate that the presented method has good effect, the lowest relative error can reach 10% in some circumstances.
Biological applications of confocal fluorescence polarization microscopy
NASA Astrophysics Data System (ADS)
Bigelow, Chad E.
Fluorescence polarization microscopy is a powerful modality capable of sensing changes in the physical properties and local environment of fluorophores. In this thesis we present new applications for the technique in cancer diagnosis and treatment and explore the limits of the modality in scattering media. We describe modifications to our custom-built confocal fluorescence microscope that enable dual-color imaging, optical fiber-based confocal spectroscopy and fluorescence polarization imaging. Experiments are presented that indicate the performance of the instrument for all three modalities. The limits of confocal fluorescence polarization imaging in scattering media are explored and the microscope parameters necessary for accurate polarization images in this regime are determined. A Monte Carlo routine is developed to model the effect of scattering on images. Included in it are routines to track the polarization state of light using the Mueller-Stokes formalism and a model for fluorescence generation that includes sampling the excitation light polarization ellipse, Brownian motion of excited-state fluorophores in solution, and dipole fluorophore emission. Results from this model are compared to experiments performed on a fluorophore-embedded polymer rod in a turbid medium consisting of polystyrene microspheres in aqueous suspension. We demonstrate the utility of the fluorescence polarization imaging technique for removal of contaminating autofluorescence and for imaging photodynamic therapy drugs in cell monolayers. Images of cells expressing green fluorescent protein are extracted from contaminating fluorescein emission. The distribution of meta-tetrahydroxypheny1chlorin in an EMT6 cell monolayer is also presented. A new technique for imaging enzyme activity is presented that is based on observing changes in the anisotropy of fluorescently-labeled substrates. Proof-of-principle studies are performed in a model system consisting of fluorescently labeled bovine serum albumin attached to sepharose beads. The action of trypsin and proteinase K on the albumin is monitored to demonstrate validity of the technique. Images of the processing of the albumin in J774 murine macrophages are also presented indicating large intercellular differences in enzyme activity. Future directions for the technique are also presented, including the design of enzyme probes specific for prostate specific antigen based on fluorescently-labeled dendrimers. A technique for enzyme imaging based on extracellular autofluorescence is also proposed.
FISH Finder: a high-throughput tool for analyzing FISH images
Shirley, James W.; Ty, Sereyvathana; Takebayashi, Shin-ichiro; Liu, Xiuwen; Gilbert, David M.
2011-01-01
Motivation: Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus. Analyzing the data from FISH images is a tedious process that invokes an element of subjectivity. Automated FISH image analysis offers savings in time as well as gaining the benefit of objective data analysis. While several FISH image analysis software tools have been developed, they often use a threshold-based segmentation algorithm for nucleus segmentation. As fluorescence signal intensities can vary significantly from experiment to experiment, from cell to cell, and within a cell, threshold-based segmentation is inflexible and often insufficient for automatic image analysis, leading to additional manual segmentation and potential subjective bias. To overcome these problems, we developed a graphical software tool called FISH Finder to automatically analyze FISH images that vary significantly. By posing the nucleus segmentation as a classification problem, compound Bayesian classifier is employed so that contextual information is utilized, resulting in reliable classification and boundary extraction. This makes it possible to analyze FISH images efficiently and objectively without adjustment of input parameters. Additionally, FISH Finder was designed to analyze the distances between differentially stained FISH probes. Availability: FISH Finder is a standalone MATLAB application and platform independent software. The program is freely available from: http://code.google.com/p/fishfinder/downloads/list Contact: gilbert@bio.fsu.edu PMID:21310746
A homeostatic, chip-based platform for zebrafish larvae immobilization and long-term imaging
NASA Astrophysics Data System (ADS)
Friedrich, Timo; Zhu, Feng; Wlodkowic, Donald; Kaslin, Jan
2015-12-01
Zebrafish larvae are ideal for toxicology and drug screens due to their transparency, small size and similarity to humans on the genetic level. Using modern imaging techniques, cells and tissues can be dynamically visualised and followed over days in multiple zebrafish. Yet continued imaging experiments require specialized conditions such as: moisture and heat control to maintain specimen homeostasis. Chambers that control the environment are generally very expensive and are not always available for all imaging platforms. A highly customizable mounting configuration with built-in means of controlling temperature and media flow would therefore be a valuable tool for long term imaging experiments. Rapid prototyping using 3D printing is particularly suitable as a production method as it offers high flexibility in design, is widely available and allows a high degree of customizing. We study neural regeneration in zebrafish. Regeneration is limited in humans, but zebrafish recover from neural damage within days. Yet, the underlying regenerative mechanisms remain unclear. We developed an agarose based mounting system that holds the embryos in defined positions along removable strips. Homeostasis and temperature control is ensured by channels circulating buffer and heated water. This allows to image up to 120 larvae simultaneously for more than two days. Its flexibility and the low-volume, high larvae ratio will allow screening of small compound libraries. Taken together, we offer a low cost, highly adaptable solution for long term in-vivo imaging.
Image preprocessing study on KPCA-based face recognition
NASA Astrophysics Data System (ADS)
Li, Xuan; Li, Dehua
2015-12-01
Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.
[Detecting fire smoke based on the multispectral image].
Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei
2010-04-01
Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.
Locality constrained joint dynamic sparse representation for local matching based face recognition.
Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun
2014-01-01
Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.
Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.
Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel
2017-07-28
New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.
Gordon, Jeremy W.; Niles, David J.; Fain, Sean B.; Johnson, Kevin M.
2014-01-01
Purpose To develop a novel imaging technique to reduce the number of excitations and required scan time for hyperpolarized 13C imaging. Methods A least-squares based optimization and reconstruction is developed to simultaneously solve for both spatial and spectral encoding. By jointly solving both domains, spectral imaging can potentially be performed with a spatially oversampled single echo spiral acquisition. Digital simulations, phantom experiments, and initial in vivo hyperpolarized [1-13C]pyruvate experiments were performed to assess the performance of the algorithm as compared to a multi-echo approach. Results Simulations and phantom data indicate that accurate single echo imaging is possible when coupled with oversampling factors greater than six (corresponding to a worst case of pyruvate to metabolite ratio < 9%), even in situations of substantial T2* decay and B0 heterogeneity. With lower oversampling rates, two echoes are required for similar accuracy. These results were confirmed with in vivo data experiments, showing accurate single echo spectral imaging with an oversampling factor of 7 and two echo imaging with an oversampling factor of 4. Conclusion The proposed k-t approach increases data acquisition efficiency by reducing the number of echoes required to generate spectroscopic images, thereby allowing accelerated acquisition speed, preserved polarization, and/or improved temporal or spatial resolution. Magn Reson Med PMID:23716402
NASA Astrophysics Data System (ADS)
Hariharan, Harishwaran; Aklaghi, Nima; Baker, Clayton A.; Rangwala, Huzefa; Kosecka, Jana; Sikdar, Siddhartha
2016-04-01
In spite of major advances in biomechanical design of upper extremity prosthetics, these devices continue to lack intuitive control. Conventional myoelectric control strategies typically utilize electromyography (EMG) signal amplitude sensed from forearm muscles. EMG has limited specificity in resolving deep muscle activity and poor signal-to-noise ratio. We have been investigating alternative control strategies that rely on real-time ultrasound imaging that can overcome many of the limitations of EMG. In this work, we present an ultrasound image sequence classification method that utilizes spatiotemporal features to describe muscle activity and classify motor intent. Ultrasound images of the forearm muscles were obtained from able-bodied subjects and a trans-radial amputee while they attempted different hand movements. A grid-based approach is used to test the feasibility of using spatio-temporal features by classifying hand motions performed by the subjects. Using the leave-one-out cross validation on image sequences acquired from able-bodied subjects, we observe that the grid-based approach is able to discern four hand motions with 95.31% accuracy. In case of the trans-radial amputee, we are able to discern three hand motions with 80% accuracy. In a second set of experiments, we study classification accuracy by extracting spatio-temporal sub-sequences the depict activity due to the motion of local anatomical interfaces. Short time and space limited cuboidal sequences are initially extracted and assigned an optical flow behavior label, based on a response function. The image space is clustered based on the location of cuboids and features calculated from the cuboids in each cluster. Using sequences of known motions, we extract feature vectors that describe said motion. A K-nearest neighbor classifier is designed for classification experiments. Using the leave-one-out cross validation on image sequences for an amputee subject, we demonstrate that the classifier is able to discern three important hand motions with an accuracy of 93.33% accuracy, 91-100% precision and 80-100% recall rate. We anticipate that ultrasound imaging based methods will address some limitations of conventional myoelectric sensing, while adding advantages inherent to ultrasound imaging.
NASA Astrophysics Data System (ADS)
Liu, Yu-Hang; Xu, Yu; Chan, Kim Chuan; Mehta, Kalpesh; Thakor, Nitish; Liao, Lun-De
2017-02-01
Stroke is the second leading cause of death worldwide. Rapid and precise diagnosis is essential to expedite clinical decision and improve functional outcomes in stroke patients; therefore, real-time imaging plays an important role to provide crucial information for post-stroke recovery analysis. In this study, based on the multi-wavelength laser and 18.5 MHz array-based ultrasound platform, a real-time handheld photoacoustic (PA) system was developed to evaluate cerebrovascular functions pre- and post-stroke in rats. Using this system, hemodynamic information such as cerebral blood volume (CBV) can be acquired for assessment. One rat stroke model (i.e., photothrombotic ischemia (PTI)) was employed for evaluating the effect of local ischemia. For achieving better intrinsic PA contrast, Vantage and COMSOL simulations were applied to optimize the light delivery (e.g., interval between two arms) from customized fiber bundle, while phantom experiment was conducted to evaluate the imaging performance of this system. Results of phantom experiment showed that hairs ( 150 μm diameter) and pencil lead (500 μm diameter) can be imaged clearly. On the other hand, results of in vivo experiments also demonstrated that stroke symptoms can be observed in PTI model poststroke. In the near future, with the help of PA specific contrast agent, the system would be able to achieve blood-brain barrier leakage imaging post-stroke. Overall, the real-time handheld PA system holds great potential in disease models involving impairments in cerebrovascular functions.
Bringing the Digital Camera to the Physics Lab
ERIC Educational Resources Information Center
Rossi, M.; Gratton, L. M.; Oss, S.
2013-01-01
We discuss how compressed images created by modern digital cameras can lead to even severe problems in the quantitative analysis of experiments based on such images. Difficulties result from the nonlinear treatment of lighting intensity values stored in compressed files. To overcome such troubles, one has to adopt noncompressed, native formats, as…
Optical disk processing of solar images.
NASA Astrophysics Data System (ADS)
Title, A.; Tarbell, T.
The current generation of space and ground-based experiments in solar physics produces many megabyte-sized image data arrays. Optical disk technology is the leading candidate for convenient analysis, distribution, and archiving of these data. The authors have been developing data analysis procedures which use both analog and digital optical disks for the study of solar phenomena.
A Picture Is Worth a Thousand Words: Applying Image-Based Learning to Course Design
ERIC Educational Resources Information Center
Whitley, Cameron T.
2013-01-01
Although images are often used in the classroom to communicate difficult concepts, students have little input into their selection and application. This approach can create a passive experience for students and represents a missed opportunity for instructors to engage participation. By applying concepts found in visual sociology to techniques…
ERIC Educational Resources Information Center
Connell, Louise; Lynott, Dermot
2012-01-01
Abstract concepts are traditionally thought to differ from concrete concepts by their lack of perceptual information, which causes them to be processed more slowly and less accurately than perceptually-based concrete concepts. In two studies, we examined this assumption by comparing concreteness and imageability ratings to a set of perceptual…
Particle-image Velocimetry (PIV)
2015-05-12
Particle-image velocimetry (PIV) is performed on the upper surface of a pitching airfoil in the NASA Glenn Icing Research Tunnel. PIV is a laser-based flow velocity measurement technique used widely in wind tunnels. These experiments were conducted as part of a research project focused on enhancing rotorcraft speed, efficiency and maneuverability by suppressing dynamic stall.
Ultrasoft x-ray imaging system for the National Spherical Torus Experiment
NASA Astrophysics Data System (ADS)
Stutman, D.; Finkenthal, M.; Soukhanovskii, V.; May, M. J.; Moos, H. W.; Kaita, R.
1999-01-01
A spectrally resolved ultrasoft x-ray imaging system, consisting of arrays of high resolution (<2 Å) and throughput (⩾tens of kHz) miniature monochromators, and based on multilayer mirrors and absolute photodiodes, is being designed for the National Spherical Torus Experiment. Initially, three poloidal arrays of diodes filtered for C 1s-np emission will be implemented for fast tomographic imaging of the colder start-up plasmas. Later on, mirrors tuned to the C Lyα emission will be added in order to enable the arrays to "see" the periphery through the hot core and to study magnetohydrodynamic activity and impurity transport in this region. We also discuss possible core diagnostics, based on tomographic imaging of the Lyα emission from the plume of recombined, low Z impurity ions left by neutral beams or fueling pellets. The arrays can also be used for radiated power measurements and to map the distribution of high Z impurities injected for transport studies. The performance of the proposed system is illustrated with results from test channels on the CDX-U spherical torus at Princeton Plasma Physics Laboratory.
Wright, Alexander I.; Magee, Derek R.; Quirke, Philip; Treanor, Darren E.
2015-01-01
Background: Obtaining ground truth for pathological images is essential for various experiments, especially for training and testing image analysis algorithms. However, obtaining pathologist input is often difficult, time consuming and expensive. This leads to algorithms being over-fitted to small datasets, and inappropriate validation, which causes poor performance on real world data. There is a great need to gather data from pathologists in a simple and efficient manner, in order to maximise the amount of data obtained. Methods: We present a lightweight, web-based HTML5 system for administering and participating in data collection experiments. The system is designed for rapid input with minimal effort, and can be accessed from anywhere in the world with a reliable internet connection. Results: We present two case studies that use the system to assess how limitations on fields of view affect pathologist agreement, and to what extent poorly stained slides affect judgement. In both cases, the system collects pathologist scores at a rate of less than two seconds per image. Conclusions: The system has multiple potential applications in pathology and other domains. PMID:26110089
Wright, Alexander I; Magee, Derek R; Quirke, Philip; Treanor, Darren E
2015-01-01
Obtaining ground truth for pathological images is essential for various experiments, especially for training and testing image analysis algorithms. However, obtaining pathologist input is often difficult, time consuming and expensive. This leads to algorithms being over-fitted to small datasets, and inappropriate validation, which causes poor performance on real world data. There is a great need to gather data from pathologists in a simple and efficient manner, in order to maximise the amount of data obtained. We present a lightweight, web-based HTML5 system for administering and participating in data collection experiments. The system is designed for rapid input with minimal effort, and can be accessed from anywhere in the world with a reliable internet connection. We present two case studies that use the system to assess how limitations on fields of view affect pathologist agreement, and to what extent poorly stained slides affect judgement. In both cases, the system collects pathologist scores at a rate of less than two seconds per image. The system has multiple potential applications in pathology and other domains.
A method of non-contact reading code based on computer vision
NASA Astrophysics Data System (ADS)
Zhang, Chunsen; Zong, Xiaoyu; Guo, Bingxuan
2018-03-01
With the purpose of guarantee the computer information exchange security between internal and external network (trusted network and un-trusted network), A non-contact Reading code method based on machine vision has been proposed. Which is different from the existing network physical isolation method. By using the computer monitors, camera and other equipment. Deal with the information which will be on exchanged, Include image coding ,Generate the standard image , Display and get the actual image , Calculate homography matrix, Image distort correction and decoding in calibration, To achieve the computer information security, Non-contact, One-way transmission between the internal and external network , The effectiveness of the proposed method is verified by experiments on real computer text data, The speed of data transfer can be achieved 24kb/s. The experiment shows that this algorithm has the characteristics of high security, fast velocity and less loss of information. Which can meet the daily needs of the confidentiality department to update the data effectively and reliably, Solved the difficulty of computer information exchange between Secret network and non-secret network, With distinctive originality, practicability, and practical research value.
Li, Feng
2015-07-01
This review paper is based on our research experience in the past 30 years. The importance of radiologists' role is discussed in the development or evaluation of new medical images and of computer-aided detection (CAD) schemes in chest radiology. The four main topics include (1) introducing what diseases can be included in a research database for different imaging techniques or CAD systems and what imaging database can be built by radiologists, (2) understanding how radiologists' subjective judgment can be combined with technical objective features to improve CAD performance, (3) sharing our experience in the design of successful observer performance studies, and (4) finally, discussing whether the new images and CAD systems can improve radiologists' diagnostic ability in chest radiology. In conclusion, advanced imaging techniques and detection/classification of CAD systems have a potential clinical impact on improvement of radiologists' diagnostic ability, for both the detection and the differential diagnosis of various lung diseases, in chest radiology.
PhAst: A Flexible IDL Astronomical Image Viewer
NASA Astrophysics Data System (ADS)
Rehnberg, Morgan; Crawford, R.; Trueblood, M.; Mighell, K.
2012-01-01
We present near-Earth asteroid data analyzed with PhAst, a new IDL astronomical image viewer based on the existing application ATV. PhAst opens, displays, and analyzes an arbitrary number of FITS images. Analysis packages include image calibration, photometry, and astrometry (provided through an interface with SExtractor, SCAMP, and missFITS). PhAst has been designed to generate reports for Minor Planet Center reporting. PhAst is cross platform (Linux/Mac OSX/Windows for image viewing and Linux/Mac OSX for image analysis) and can be downloaded from the following website at NOAO: http://www.noao.edu/staff/mighell/phast/. Rehnberg was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.
NASA Astrophysics Data System (ADS)
Ouyang, Bing; Hou, Weilin; Gong, Cuiling; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.
2016-05-01
The Compressive Line Sensing (CLS) active imaging system has been demonstrated to be effective in scattering mediums, such as turbid coastal water through simulations and test tank experiments. Since turbulence is encountered in many atmospheric and underwater surveillance applications, a new CLS imaging prototype was developed to investigate the effectiveness of the CLS concept in a turbulence environment. Compared with earlier optical bench top prototype, the new system is significantly more robust and compact. A series of experiments were conducted at the Naval Research Lab's optical turbulence test facility with the imaging path subjected to various turbulence intensities. In addition to validating the system design, we obtained some unexpected exciting results - in the strong turbulence environment, the time-averaged measurements using the new CLS imaging prototype improved both SNR and resolution of the reconstructed images. We will discuss the implications of the new findings, the challenges of acquiring data through strong turbulence environment, and future enhancements.
NASA Astrophysics Data System (ADS)
Kesiman, Made Windu Antara; Valy, Dona; Burie, Jean-Christophe; Paulus, Erick; Sunarya, I. Made Gede; Hadi, Setiawan; Sok, Kim Heng; Ogier, Jean-Marc
2017-01-01
Due to their specific characteristics, palm leaf manuscripts provide new challenges for text line segmentation tasks in document analysis. We investigated the performance of six text line segmentation methods by conducting comparative experimental studies for the collection of palm leaf manuscript images. The image corpus used in this study comes from the sample images of palm leaf manuscripts of three different Southeast Asian scripts: Balinese script from Bali and Sundanese script from West Java, both from Indonesia, and Khmer script from Cambodia. For the experiments, four text line segmentation methods that work on binary images are tested: the adaptive partial projection line segmentation approach, the A* path planning approach, the shredding method, and our proposed energy function for shredding method. Two other methods that can be directly applied on grayscale images are also investigated: the adaptive local connectivity map method and the seam carving-based method. The evaluation criteria and tool provided by ICDAR2013 Handwriting Segmentation Contest were used in this experiment.
TH-B-207B-00: Pediatric Image Quality Optimization
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
This imaging educational program will focus on solutions to common pediatric image quality optimization challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. One of the most commonly encountered pediatric imaging requirements for the non-specialist hospital is pediatric CT in the emergency room setting. Thus, this educational program will begin with optimization of pediatric CT in the emergency department. Though pediatric cardiovascular MRI may be less common in the non-specialist hospitals, low pediatric volumes and unique cardiovascular anatomy make optimization of these techniques difficult. Therefore, our second speaker willmore » review best practices in pediatric cardiovascular MRI based on experiences from a children’s hospital with a large volume of cardiac patients. Learning Objectives: To learn techniques for optimizing radiation dose and image quality for CT of children in the emergency room setting. To learn solutions for consistently high quality cardiovascular MRI of children.« less
Quantitative imaging of the human upper airway: instrument design and clinical studies
NASA Astrophysics Data System (ADS)
Leigh, M. S.; Armstrong, J. J.; Paduch, A.; Sampson, D. D.; Walsh, J. H.; Hillman, D. R.; Eastwood, P. R.
2006-08-01
Imaging of the human upper airway is widely used in medicine, in both clinical practice and research. Common imaging modalities include video endoscopy, X-ray CT, and MRI. However, no current modality is both quantitative and safe to use for extended periods of time. Such a capability would be particularly valuable for sleep research, which is inherently reliant on long observation sessions. We have developed an instrument capable of quantitative imaging of the human upper airway, based on endoscopic optical coherence tomography. There are no dose limits for optical techniques, and the minimally invasive imaging probe is safe for use in overnight studies. We report on the design of the instrument and its use in preliminary clinical studies, and we present results from a range of initial experiments. The experiments show that the instrument is capable of imaging during sleep, and that it can record dynamic changes in airway size and shape. This information is useful for research into sleep disorders, and potentially for clinical diagnosis and therapies.
A lane line segmentation algorithm based on adaptive threshold and connected domain theory
NASA Astrophysics Data System (ADS)
Feng, Hui; Xu, Guo-sheng; Han, Yi; Liu, Yang
2018-04-01
Before detecting cracks and repairs on road lanes, it's necessary to eliminate the influence of lane lines on the recognition result in road lane images. Aiming at the problems caused by lane lines, an image segmentation algorithm based on adaptive threshold and connected domain is proposed. First, by analyzing features like grey level distribution and the illumination of the images, the algorithm uses Hough transform to divide the images into different sections and convert them into binary images separately. It then uses the connected domain theory to amend the outcome of segmentation, remove noises and fill the interior zone of lane lines. Experiments have proved that this method could eliminate the influence of illumination and lane line abrasion, removing noises thoroughly while maintaining high segmentation precision.
A Double-function Digital Watermarking Algorithm Based on Chaotic System and LWT
NASA Astrophysics Data System (ADS)
Yuxia, Zhao; Jingbo, Fan
A double- function digital watermarking technology is studied and a double-function digital watermarking algorithm of colored image is presented based on chaotic system and the lifting wavelet transformation (LWT).The algorithm has realized the double aims of the copyright protection and the integrity authentication of image content. Making use of feature of human visual system (HVS), the watermark image is embedded into the color image's low frequency component and middle frequency components by different means. The algorithm has great security by using two kinds chaotic mappings and Arnold to scramble the watermark image at the same time. The algorithm has good efficiency by using LWT. The emulation experiment indicates the algorithm has great efficiency and security, and the effect of concealing is really good.
Social Image Tag Ranking by Two-View Learning
NASA Astrophysics Data System (ADS)
Zhuang, Jinfeng; Hoi, Steven C. H.
Tags play a central role in text-based social image retrieval and browsing. However, the tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In order to solve this problem, researchers have proposed techniques to rank the annotated tags of a social image according to their relevance to the visual content of the image. In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assumes some parametric models, our method is completely data-driven and makes no assumption about the underlying models, making the proposed solution practically more effective. We formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks. Our empirical results showed that the proposed method can be more effective than the conventional approaches.
Li, Qiang; Liu, Hao-Li; Chen, Wen-Shiang
2013-01-01
Previous studies developed ultrasound temperature-imaging methods based on changes in backscattered energy (CBE) to monitor variations in temperature during hyperthermia. In conventional CBE imaging, tracking and compensation of the echo shift due to temperature increase need to be done. Moreover, the CBE image does not enable visualization of the temperature distribution in tissues during nonuniform heating, which limits its clinical application in guidance of tissue ablation treatment. In this study, we investigated a CBE imaging method based on the sliding window technique and the polynomial approximation of the integrated CBE (ICBEpa image) to overcome the difficulties of conventional CBE imaging. We conducted experiments with tissue samples of pork tenderloin ablated by microwave irradiation to validate the feasibility of the proposed method. During ablation, the raw backscattered signals were acquired using an ultrasound scanner for B-mode and ICBEpa imaging. The experimental results showed that the proposed ICBEpa image can visualize the temperature distribution in a tissue with a very good contrast. Moreover, tracking and compensation of the echo shift were not necessary when using the ICBEpa image to visualize the temperature profile. The experimental findings suggested that the ICBEpa image, a new CBE imaging method, has a great potential in CBE-based imaging of hyperthermia and other thermal therapies. PMID:24260041
Efficient OCT Image Enhancement Based on Collaborative Shock Filtering
2018-01-01
Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments. PMID:29599954
Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.
Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin
2018-01-01
Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.
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.
Digital Image Quality And Interpretability: Database And Hardcopy Studies
NASA Astrophysics Data System (ADS)
Snyder, H. L.; Maddox, M. E.; Shedivy, D. I.; Turpin, J. A.; Burke, J. J.; Strickland, R. N.
1982-02-01
Two hundred fifty transparencies, displaying a new digital database consisting of 25 degraded versions (5 blur levels x 5 noise levels) of each of 10 digitized, first-generation positive transparencies, were used in two experiments involving 15 trained military photointer-preters. Each image is 86 mm square and represents 40962 8-bit pixels. In the "interpretation" experiment, each photointerpreter (judge) spent approximately two days extracting essential elements of information (EEls) from one degraded version of each scene at a constant Gaussian blur level (FWHM = 40, 84, or 322 Am). In the scaling experiment, each judge assigned a numerical value to each of the 250 images, according to its perceived position on a 10-point NATO-standardized scale (0 = useless through 9 = nearly perfect), to the nearest 0.1 unit. Eighty-eight of the 100 possible values were used by the judges, indicating that 62 categories, based on the Shannon-Wiener measure of information, are needed to scale these hardcopy images. The overall correlation between the scaling and interpretation results was 0.9. Though the main effect of blur was not statistically significant in the interpretation experiment, that of noise was significant, and all main factors (blur, noise, scene, order of battle) and most interactions were statistically significant in the scaling experiment.
The recognition of ocean red tide with hyper-spectral-image based on EMD
NASA Astrophysics Data System (ADS)
Zhao, Wencang; Wei, Hongli; Shi, Changjiang; Ji, Guangrong
2008-05-01
A new technique is introduced in this paper regarding red tide recognition with remotely sensed hyper-spectral images based on empirical mode decomposition (EMD), from an artificial red tide experiment in the East China Sea in 2002. A set of characteristic parameters that describe absorbing crest and reflecting crest of the red tide and its recognition methods are put forward based on general picture data, with which the spectral information of certain non-dominant alga species of a red tide occurrence is analyzed for establishing the foundation to estimate the species. Comparative experiments have proved that the method is effective. Meanwhile, the transitional area between red-tide zone and non-red-tide zone can be detected with the information of thickness of algae influence, with which a red tide can be forecast.
Magnetic resonance image segmentation using multifractal techniques
NASA Astrophysics Data System (ADS)
Yu, Yue-e.; Wang, Fang; Liu, Li-lin
2015-11-01
In order to delineate target region for magnetic resonance image (MRI) with diseases, the classical multifractal spectrum (MFS)-segmentation method and latest multifractal detrended fluctuation spectrum (MF-DFS)-based segmentation method are employed in our study. One of our main conclusions from experiments is that both of the two multifractal-based methods are workable for handling MRIs. The best result is obtained by MF-DFS-based method using Lh10 as local characteristic. The anti-noises experiments also suppot the conclusion. This interest finding shows that the features can be better represented by the strong fluctuations instead of the weak fluctuations for the MRIs. By comparing the multifractal nature between lesion and non-lesion area on the basis of the segmentation results, an interest finding is that the gray value's fluctuation in lesion area is much severer than that in non-lesion area.
Benoit, Michel; Guerchouche, Rachid; Petit, Pierre-David; Chapoulie, Emmanuelle; Manera, Valeria; Chaurasia, Gaurav; Drettakis, George; Robert, Philippe
2015-01-01
Virtual reality (VR) opens up a vast number of possibilities in many domains of therapy. The primary objective of the present study was to evaluate the acceptability for elderly subjects of a VR experience using the image-based rendering virtual environment (IBVE) approach and secondly to test the hypothesis that visual cues using VR may enhance the generation of autobiographical memories. Eighteen healthy volunteers (mean age 68.2 years) presenting memory complaints with a Mini-Mental State Examination score higher than 27 and no history of neuropsychiatric disease were included. Participants were asked to perform an autobiographical fluency task in four conditions. The first condition was a baseline grey screen, the second was a photograph of a well-known location in the participant's home city (FamPhoto), and the last two conditions displayed VR, ie, a familiar image-based virtual environment (FamIBVE) consisting of an image-based representation of a known landmark square in the center of the city of experimentation (Nice) and an unknown image-based virtual environment (UnknoIBVE), which was captured in a public housing neighborhood containing unrecognizable building fronts. After each of the four experimental conditions, participants filled in self-report questionnaires to assess the task acceptability (levels of emotion, motivation, security, fatigue, and familiarity). CyberSickness and Presence questionnaires were also assessed after the two VR conditions. Autobiographical memory was assessed using a verbal fluency task and quality of the recollection was assessed using the "remember/know" procedure. All subjects completed the experiment. Sense of security and fatigue were not significantly different between the conditions with and without VR. The FamPhoto condition yielded a higher emotion score than the other conditions (P<0.05). The CyberSickness questionnaire showed that participants did not experience sickness during the experiment across the VR conditions. VR stimulates autobiographical memory, as demonstrated by the increased total number of responses on the autobiographical fluency task and the increased number of conscious recollections of memories for familiar versus unknown scenes (P<0.01). The study indicates that VR using the FamIBVE system is well tolerated by the elderly. VR can also stimulate recollections of autobiographical memory and convey familiarity of a given scene, which is an essential requirement for use of VR during reminiscence therapy.
Benoit, Michel; Guerchouche, Rachid; Petit, Pierre-David; Chapoulie, Emmanuelle; Manera, Valeria; Chaurasia, Gaurav; Drettakis, George; Robert, Philippe
2015-01-01
Background Virtual reality (VR) opens up a vast number of possibilities in many domains of therapy. The primary objective of the present study was to evaluate the acceptability for elderly subjects of a VR experience using the image-based rendering virtual environment (IBVE) approach and secondly to test the hypothesis that visual cues using VR may enhance the generation of autobiographical memories. Methods Eighteen healthy volunteers (mean age 68.2 years) presenting memory complaints with a Mini-Mental State Examination score higher than 27 and no history of neuropsychiatric disease were included. Participants were asked to perform an autobiographical fluency task in four conditions. The first condition was a baseline grey screen, the second was a photograph of a well-known location in the participant’s home city (FamPhoto), and the last two conditions displayed VR, ie, a familiar image-based virtual environment (FamIBVE) consisting of an image-based representation of a known landmark square in the center of the city of experimentation (Nice) and an unknown image-based virtual environment (UnknoIBVE), which was captured in a public housing neighborhood containing unrecognizable building fronts. After each of the four experimental conditions, participants filled in self-report questionnaires to assess the task acceptability (levels of emotion, motivation, security, fatigue, and familiarity). CyberSickness and Presence questionnaires were also assessed after the two VR conditions. Autobiographical memory was assessed using a verbal fluency task and quality of the recollection was assessed using the “remember/know” procedure. Results All subjects completed the experiment. Sense of security and fatigue were not significantly different between the conditions with and without VR. The FamPhoto condition yielded a higher emotion score than the other conditions (P<0.05). The CyberSickness questionnaire showed that participants did not experience sickness during the experiment across the VR conditions. VR stimulates autobiographical memory, as demonstrated by the increased total number of responses on the autobiographical fluency task and the increased number of conscious recollections of memories for familiar versus unknown scenes (P<0.01). Conclusion The study indicates that VR using the FamIBVE system is well tolerated by the elderly. VR can also stimulate recollections of autobiographical memory and convey familiarity of a given scene, which is an essential requirement for use of VR during reminiscence therapy. PMID:25834437
DARTFire Sees Microgravity Fires in a New Light--Large Data Base of Images Obtained
NASA Technical Reports Server (NTRS)
Olson, Sandra L.; Hegde, Uday; Altenkirch, Robert A.; Bhatacharjee, Subrata
1999-01-01
The recently completed DARTFire sounding rocket microgravity combustion experiment launched a new era in the imaging of flames in microgravity. DARTFire stands for "Diffusive and Radiative Transport in Fires," which perfectly describes the two primary variables--diffusive flow and radiation effects--that were studied in the four launches of this program (June 1996 to September 1997). During each launch, two experiments, which were conducted simultaneously during the 6 min of microgravity, obtained results as the rocket briefly exited the Earth s atmosphere.
Study on super-resolution three-dimensional range-gated imaging technology
NASA Astrophysics Data System (ADS)
Guo, Huichao; Sun, Huayan; Wang, Shuai; Fan, Youchen; Li, Yuanmiao
2018-04-01
Range-gated three dimensional imaging technology is a hotspot in recent years, because of the advantages of high spatial resolution, high range accuracy, long range, and simultaneous reflection of target reflectivity information. Based on the study of the principle of intensity-related method, this paper has carried out theoretical analysis and experimental research. The experimental system adopts the high power pulsed semiconductor laser as light source, gated ICCD as the imaging device, can realize the imaging depth and distance flexible adjustment to achieve different work mode. The imaging experiment of small imaging depth is carried out aiming at building 500m away, and 26 group images were obtained with distance step 1.5m. In this paper, the calculation method of 3D point cloud based on triangle method is analyzed, and 15m depth slice of the target 3D point cloud are obtained by using two frame images, the distance precision is better than 0.5m. The influence of signal to noise ratio, illumination uniformity and image brightness on distance accuracy are analyzed. Based on the comparison with the time-slicing method, a method for improving the linearity of point cloud is proposed.
A kind of color image segmentation algorithm based on super-pixel and PCNN
NASA Astrophysics Data System (ADS)
Xu, GuangZhu; Wang, YaWen; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun
2018-04-01
Image segmentation is a very important step in the low-level visual computing. Although image segmentation has been studied for many years, there are still many problems. PCNN (Pulse Coupled Neural network) has biological background, when it is applied to image segmentation it can be viewed as a region-based method, but due to the dynamics properties of PCNN, many connectionless neurons will pulse at the same time, so it is necessary to identify different regions for further processing. The existing PCNN image segmentation algorithm based on region growing is used for grayscale image segmentation, cannot be directly used for color image segmentation. In addition, the super-pixel can better reserve the edges of images, and reduce the influences resulted from the individual difference between the pixels on image segmentation at the same time. Therefore, on the basis of the super-pixel, the original PCNN algorithm based on region growing is improved by this paper. First, the color super-pixel image was transformed into grayscale super-pixel image which was used to seek seeds among the neurons that hadn't been fired. And then it determined whether to stop growing by comparing the average of each color channel of all the pixels in the corresponding regions of the color super-pixel image. Experiment results show that the proposed algorithm for the color image segmentation is fast and effective, and has a certain effect and accuracy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Kuangcai
The goal of this study is to help with future data analysis and experiment designs in rotational dynamics research using DIC-based SPORT technique. Most of the current studies using DIC-based SPORT techniques are technical demonstrations. Understanding the mechanisms behind the observed rotational behaviors of the imaging probes should be the focus of the future SPORT studies. More efforts are still needed in the development of new imaging probes, particle tracking methods, instrumentations, and advanced data analysis methods to further extend the potential of DIC-based SPORT technique.
Supporting flight data analysis for Space Shuttle Orbiter Experiments at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Green, M. J.; Budnick, M. P.; Yang, L.; Chiasson, M. P.
1983-01-01
The Space Shuttle Orbiter Experiments program in responsible for collecting flight data to extend the research and technology base for future aerospace vehicle design. The Infrared Imagery of Shuttle (IRIS), Catalytic Surface Effects, and Tile Gap Heating experiments sponsored by Ames Research Center are part of this program. The paper describes the software required to process the flight data which support these experiments. In addition, data analysis techniques, developed in support of the IRIS experiment, are discussed. Using the flight data base, the techniques have provided information useful in analyzing and correcting problems with the experiment, and in interpreting the IRIS image obtained during the entry of the third Shuttle mission.
Supporting flight data analysis for Space Shuttle Orbiter experiments at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Green, M. J.; Budnick, M. P.; Yang, L.; Chiasson, M. P.
1983-01-01
The space shuttle orbiter experiments program is responsible for collecting flight data to extend the research and technology base for future aerospace vehicle design. The infrared imagery of shuttle (IRIS), catalytic surface effects, and tile gap heating experiments sponsored by Ames Research Center are part of this program. The software required to process the flight data which support these experiments is described. In addition, data analysis techniques, developed in support of the IRIS experiment, are discussed. Using the flight data base, the techniques provide information useful in analyzing and correcting problems with the experiment, and in interpreting the IRIS image obtained during the entry of the third shuttle mission.
Chowdhury, Debbrota Paul; Bakshi, Sambit; Guo, Guodong; Sa, Pankaj Kumar
2017-11-27
In this paper, an overall framework has been presented for person verification using ear biometric which uses tunable filter bank as local feature extractor. The tunable filter bank, based on a half-band polynomial of 14th order, extracts distinct features from ear images maintaining its frequency selectivity property. To advocate the applicability of tunable filter bank on ear biometrics, recognition test has been performed on available constrained databases like AMI, WPUT, IITD and unconstrained database like UERC. Experiments have been conducted applying tunable filter based feature extractor on subparts of the ear. Empirical experiments have been conducted with four and six subdivisions of the ear image. Analyzing the experimental results, it has been found that tunable filter moderately succeeds to distinguish ear features at par with the state-of-the-art features used for ear recognition. Accuracies of 70.58%, 67.01%, 81.98%, and 57.75% have been achieved on AMI, WPUT, IITD, and UERC databases through considering Canberra Distance as underlying measure of separation. The performances indicate that tunable filter is a candidate for recognizing human from ear images.
The experience of mathematical beauty and its neural correlates
Zeki, Semir; Romaya, John Paul; Benincasa, Dionigi M. T.; Atiyah, Michael F.
2014-01-01
Many have written of the experience of mathematical beauty as being comparable to that derived from the greatest art. This makes it interesting to learn whether the experience of beauty derived from such a highly intellectual and abstract source as mathematics correlates with activity in the same part of the emotional brain as that derived from more sensory, perceptually based, sources. To determine this, we used functional magnetic resonance imaging (fMRI) to image the activity in the brains of 15 mathematicians when they viewed mathematical formulae which they had individually rated as beautiful, indifferent or ugly. Results showed that the experience of mathematical beauty correlates parametrically with activity in the same part of the emotional brain, namely field A1 of the medial orbito-frontal cortex (mOFC), as the experience of beauty derived from other sources. PMID:24592230
Background suppression of infrared small target image based on inter-frame registration
NASA Astrophysics Data System (ADS)
Ye, Xiubo; Xue, Bindang
2018-04-01
We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.
Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A
2013-01-01
This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces. PMID:23250787
Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A
2013-06-01
This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces.
[Lateral chromatic aberrations correction for AOTF imaging spectrometer based on doublet prism].
Zhao, Hui-Jie; Zhou, Peng-Wei; Zhang, Ying; Li, Chong-Chong
2013-10-01
An user defined surface function method was proposed to model the acousto-optic interaction of AOTF based on wave-vector match principle. Assessment experiment result shows that this model can achieve accurate ray trace of AOTF diffracted beam. In addition, AOTF imaging spectrometer presents large residual lateral color when traditional chromatic aberrations correcting method is adopted. In order to reduce lateral chromatic aberrations, a method based on doublet prism is proposed. The optical material and angle of the prism are optimized automatically using global optimization with the help of user defined AOTF surface. Simulation result shows that the proposed method provides AOTF imaging spectrometer with great conveniences, which reduces the lateral chromatic aberration to less than 0.000 3 degrees and improves by one order of magnitude, with spectral image shift effectively corrected.
NASA Astrophysics Data System (ADS)
Li, Jing; Cai, Cong-Bo; Chen, Lin; Chen, Ying; Qu, Xiao-Bo; Cai, Shu-Hui
2015-10-01
In many ultrafast imaging applications, the reduced field-of-view (rFOV) technique is often used to enhance the spatial resolution and field inhomogeneity immunity of the images. The stationary-phase characteristic of the spatiotemporally-encoded (SPEN) method offers an inherent applicability to rFOV imaging. In this study, a flexible rFOV imaging method is presented and the superiority of the SPEN approach in rFOV imaging is demonstrated. The proposed method is validated with phantom and in vivo rat experiments, including cardiac imaging and contrast-enhanced perfusion imaging. For comparison, the echo planar imaging (EPI) experiments with orthogonal RF excitation are also performed. The results show that the signal-to-noise ratios of the images acquired by the proposed method can be higher than those obtained with the rFOV EPI. Moreover, the proposed method shows better performance in the cardiac imaging and perfusion imaging of rat kidney, and it can scan one or more regions of interest (ROIs) with high spatial resolution in a single shot. It might be a favorable solution to ultrafast imaging applications in cases with severe susceptibility heterogeneities, such as cardiac imaging and perfusion imaging. Furthermore, it might be promising in applications with separate ROIs, such as mammary and limb imaging. Project supported by the National Natural Science Foundation of China (Grant Nos. 11474236, 81171331, and U1232212).
Hyperspectral imaging of skin and lung cancers
NASA Astrophysics Data System (ADS)
Zherdeva, Larisa A.; Bratchenko, Ivan A.; Alonova, Marina V.; Myakinin, Oleg O.; Artemyev, Dmitry N.; Moryatov, Alexander A.; Kozlov, Sergey V.; Zakharov, Valery P.
2016-04-01
The problem of cancer control requires design of new approaches for instrumental diagnostics, as the accuracy of cancer detection on the first step of diagnostics in clinics is slightly more than 50%. In this study, we present a method of visualization and diagnostics of skin and lung tumours based on registration and processing of tissues hyperspectral images. In a series of experiments registration of hyperspectral images of skin and lung tissue samples is carried out. Melanoma, basal cell carcinoma, nevi and benign tumours are studied in skin ex vivo and in vivo experiments; adenocarcinomas and squamous cell carcinomas are studied in ex vivo lung experiments. In a series of experiments the typical features of diffuse reflection spectra for pathological and normal tissues were found. Changes in tissues morphology during the tumour growth lead to the changes of blood and pigments concentration, such as melanin in skin. That is why tumours and normal tissues maybe differentiated with information about spectral response in 500-600 nm and 600 - 670 nm areas. Thus, hyperspectral imaging in the visible region may be a useful tool for cancer detection as it helps to estimate spectral properties of tissues and determine malignant regions for precise resection of tumours.
Burgner, J.; Simpson, A. L.; Fitzpatrick, J. M.; Lathrop, R. A.; Herrell, S. D.; Miga, M. I.; Webster, R. J.
2013-01-01
Background Registered medical images can assist with surgical navigation and enable image-guided therapy delivery. In soft tissues, surface-based registration is often used and can be facilitated by laser surface scanning. Tracked conoscopic holography (which provides distance measurements) has been recently proposed as a minimally invasive way to obtain surface scans. Moving this technique from concept to clinical use requires a rigorous accuracy evaluation, which is the purpose of our paper. Methods We adapt recent non-homogeneous and anisotropic point-based registration results to provide a theoretical framework for predicting the accuracy of tracked distance measurement systems. Experiments are conducted a complex objects of defined geometry, an anthropomorphic kidney phantom and a human cadaver kidney. Results Experiments agree with model predictions, producing point RMS errors consistently < 1 mm, surface-based registration with mean closest point error < 1 mm in the phantom and a RMS target registration error of 0.8 mm in the human cadaver kidney. Conclusions Tracked conoscopic holography is clinically viable; it enables minimally invasive surface scan accuracy comparable to current clinical methods that require open surgery. PMID:22761086
An Automatic Diagnosis Method of Facial Acne Vulgaris Based on Convolutional Neural Network.
Shen, Xiaolei; Zhang, Jiachi; Yan, Chenjun; Zhou, Hong
2018-04-11
In this paper, we present a new automatic diagnosis method for facial acne vulgaris which is based on convolutional neural networks (CNNs). To overcome the shortcomings of previous methods which were the inability to classify enough types of acne vulgaris. The core of our method is to extract features of images based on CNNs and achieve classification by classifier. A binary-classifier of skin-and-non-skin is used to detect skin area and a seven-classifier is used to achieve the classification task of facial acne vulgaris and healthy skin. In the experiments, we compare the effectiveness of our CNN and the VGG16 neural network which is pre-trained on the ImageNet data set. We use a ROC curve to evaluate the performance of binary-classifier and use a normalized confusion matrix to evaluate the performance of seven-classifier. The results of our experiments show that the pre-trained VGG16 neural network is effective in extracting features from facial acne vulgaris images. And the features are very useful for the follow-up classifiers. Finally, we try applying the classifiers both based on the pre-trained VGG16 neural network to assist doctors in facial acne vulgaris diagnosis.
Integrated optical 3D digital imaging based on DSP scheme
NASA Astrophysics Data System (ADS)
Wang, Xiaodong; Peng, Xiang; Gao, Bruce Z.
2008-03-01
We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-D imaging. In this integrated scheme of 3-D imaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-D imaging. Experiment results are also presented to show the validity of proposed scheme.
NASA Astrophysics Data System (ADS)
Wardaya, P. D.; Noh, K. A. B. M.; Yusoff, W. I. B. W.; Ridha, S.; Nurhandoko, B. E. B.
2014-09-01
This paper discusses a new approach for investigating the seismic wave velocity of rock, specifically carbonates, as affected by their pore structures. While the conventional routine of seismic velocity measurement highly depends on the extensive laboratory experiment, the proposed approach utilizes the digital rock physics view which lies on the numerical experiment. Thus, instead of using core sample, we use the thin section image of carbonate rock to measure the effective seismic wave velocity when travelling on it. In the numerical experiment, thin section images act as the medium on which wave propagation will be simulated. For the modeling, an advanced technique based on artificial neural network was employed for building the velocity and density profile, replacing image's RGB pixel value with the seismic velocity and density of each rock constituent. Then, ultrasonic wave was simulated to propagate in the thin section image by using finite difference time domain method, based on assumption of an acoustic-isotropic medium. Effective velocities were drawn from the recorded signal and being compared to the velocity modeling from Wyllie time average model and Kuster-Toksoz rock physics model. To perform the modeling, image analysis routines were undertaken for quantifying the pore aspect ratio that is assumed to represent the rocks pore structure. In addition, porosity and mineral fraction required for velocity modeling were also quantified by using integrated neural network and image analysis technique. It was found that the Kuster-Toksoz gives the closer prediction to the measured velocity as compared to the Wyllie time average model. We also conclude that Wyllie time average that does not incorporate the pore structure parameter deviates significantly for samples having more than 40% porosity. Utilizing this approach we found a good agreement between numerical experiment and theoretically derived rock physics model for estimating the effective seismic wave velocity of rock.
Nakashima, Ryoichi; Iwai, Ritsuko; Ueda, Sayako; Kumada, Takatsune
2015-01-01
When observers perceive several objects in a space, at the same time, they should effectively perceive their own position as a viewpoint. However, little is known about observers’ percepts of their own spatial location based on the visual scene information viewed from them. Previous studies indicate that two distinct visual spatial processes exist in the locomotion situation: the egocentric position perception and egocentric direction perception. Those studies examined such perceptions in information rich visual environments where much dynamic and static visual information was available. This study examined these two perceptions in information of impoverished environments, including only static lane edge information (i.e., limited information). We investigated the visual factors associated with static lane edge information that may affect these perceptions. Especially, we examined the effects of the two factors on egocentric direction and position perceptions. One is the “uprightness factor” that “far” visual information is seen at upper location than “near” visual information. The other is the “central vision factor” that observers usually look at “far” visual information using central vision (i.e., foveal vision) whereas ‘near’ visual information using peripheral vision. Experiment 1 examined the effect of the “uprightness factor” using normal and inverted road images. Experiment 2 examined the effect of the “central vision factor” using normal and transposed road images where the upper half of the normal image was presented under the lower half. Experiment 3 aimed to replicate the results of Experiments 1 and 2. Results showed that egocentric direction perception is interfered with image inversion or image transposition, whereas egocentric position perception is robust against these image transformations. That is, both “uprightness” and “central vision” factors are important for egocentric direction perception, but not for egocentric position perception. Therefore, the two visual spatial perceptions about observers’ own viewpoints are fundamentally dissociable. PMID:26648895
Dictionary Learning for Data Recovery in Positron Emission Tomography
Valiollahzadeh, SeyyedMajid; Clark, John W.; Mawlawi, Osama
2015-01-01
Compressed sensing (CS) aims to recover images from fewer measurements than that governed by the Nyquist sampling theorem. Most CS methods use analytical predefined sparsifying domains such as Total variation (TV), wavelets, curvelets, and finite transforms to perform this task. In this study, we evaluated the use of dictionary learning (DL) as a sparsifying domain to reconstruct PET images from partially sampled data, and compared the results to the partially and fully sampled image (baseline). A CS model based on learning an adaptive dictionary over image patches was developed to recover missing observations in PET data acquisition. The recovery was done iteratively in two steps: a dictionary learning step and an image reconstruction step. Two experiments were performed to evaluate the proposed CS recovery algorithm: an IEC phantom study and five patient studies. In each case, 11% of the detectors of a GE PET/CT system were removed and the acquired sinogram data were recovered using the proposed DL algorithm. The recovered images (DL) as well as the partially sampled images (with detector gaps) for both experiments were then compared to the baseline. Comparisons were done by calculating RMSE, contrast recovery and SNR in ROIs drawn in the background, and spheres of the phantom as well as patient lesions. For the phantom experiment, the RMSE for the DL recovered images were 5.8% when compared with the baseline images while it was 17.5% for the partially sampled images. In the patients’ studies, RMSE for the DL recovered images were 3.8%, while it was 11.3% for the partially sampled images. Our proposed CS with DL is a good approach to recover partially sampled PET data. This approach has implications towards reducing scanner cost while maintaining accurate PET image quantification. PMID:26161630