Spectral images browsing using principal component analysis and set partitioning in hierarchical tree

NASA Astrophysics Data System (ADS)

Ma, Long; Zhao, Deping

2011-12-01

Spectral imaging technology have been used mostly in remote sensing, but have recently been extended to new area requiring high fidelity color reproductions like telemedicine, e-commerce, etc. These spectral imaging systems are important because they offer improved color reproduction quality not only for a standard observer under a particular illuminantion, but for any other individual exhibiting normal color vision capability under another illuminantion. A possibility for browsing of the archives is needed. In this paper, the authors present a new spectral image browsing architecture. The architecture for browsing is expressed as follow: (1) The spectral domain of the spectral image is reduced with the PCA transform. As a result of the PCA transform the eigenvectors and the eigenimages are obtained. (2) We quantize the eigenimages with the original bit depth of spectral image (e.g. if spectral image is originally 8bit, then quantize eigenimage to 8bit), and use 32bit floating numbers for the eigenvectors. (3) The first eigenimage is lossless compressed by JPEG-LS, the other eigenimages were lossy compressed by wavelet based SPIHT algorithm. For experimental evalution, the following measures were used. We used PSNR as the measurement for spectral accuracy. And for the evaluation of color reproducibility, ΔE was used.here standard D65 was used as a light source. To test the proposed method, we used FOREST and CORAL spectral image databases contrain 12 and 10 spectral images, respectively. The images were acquired in the range of 403-696nm. The size of the images were 128*128, the number of bands was 40 and the resolution was 8 bits per sample. Our experiments show the proposed compression method is suitable for browsing, i.e., for visual purpose.

Color transfer between high-dynamic-range images

NASA Astrophysics Data System (ADS)

Hristova, Hristina; Cozot, Rémi; Le Meur, Olivier; Bouatouch, Kadi

2015-09-01

Color transfer methods alter the look of a source image with regards to a reference image. So far, the proposed color transfer methods have been limited to low-dynamic-range (LDR) images. Unlike LDR images, which are display-dependent, high-dynamic-range (HDR) images contain real physical values of the world luminance and are able to capture high luminance variations and finest details of real world scenes. Therefore, there exists a strong discrepancy between the two types of images. In this paper, we bridge the gap between the color transfer domain and the HDR imagery by introducing HDR extensions to LDR color transfer methods. We tackle the main issues of applying a color transfer between two HDR images. First, to address the nature of light and color distributions in the context of HDR imagery, we carry out modifications of traditional color spaces. Furthermore, we ensure high precision in the quantization of the dynamic range for histogram computations. As image clustering (based on light and colors) proved to be an important aspect of color transfer, we analyze it and adapt it to the HDR domain. Our framework has been applied to several state-of-the-art color transfer methods. Qualitative experiments have shown that results obtained with the proposed adaptation approach exhibit less artifacts and are visually more pleasing than results obtained when straightforwardly applying existing color transfer methods to HDR images.

Quality assessment of color images based on the measure of just noticeable color difference

NASA Astrophysics Data System (ADS)

Chou, Chun-Hsien; Hsu, Yun-Hsiang

2014-01-01

Accurate assessment on the quality of color images is an important step to many image processing systems that convey visual information of the reproduced images. An accurate objective image quality assessment (IQA) method is expected to give the assessment result highly agreeing with the subjective assessment. To assess the quality of color images, many approaches simply apply the metric for assessing the quality of gray scale images to each of three color channels of the color image, neglecting the correlation among three color channels. In this paper, a metric for assessing color images' quality is proposed, in which the model of variable just-noticeable color difference (VJNCD) is employed to estimate the visibility thresholds of distortion inherent in each color pixel. With the estimated visibility thresholds of distortion, the proposed metric measures the average perceptible distortion in terms of the quantized distortion according to the perceptual error map similar to that defined by National Bureau of Standards (NBS) for converting the color difference enumerated by CIEDE2000 to the objective score of perceptual quality assessment. The perceptual error map in this case is designed for each pixel according to the visibility threshold estimated by the VJNCD model. The performance of the proposed metric is verified by assessing the test images in the LIVE database, and is compared with those of many well-know IQA metrics. Experimental results indicate that the proposed metric is an effective IQA method that can accurately predict the image quality of color images in terms of the correlation between objective scores and subjective evaluation.

Pet fur color and texture classification

NASA Astrophysics Data System (ADS)

Yen, Jonathan; Mukherjee, Debarghar; Lim, SukHwan; Tretter, Daniel

2007-01-01

Object segmentation is important in image analysis for imaging tasks such as image rendering and image retrieval. Pet owners have been known to be quite vocal about how important it is to render their pets perfectly. We present here an algorithm for pet (mammal) fur color classification and an algorithm for pet (animal) fur texture classification. Per fur color classification can be applied as a necessary condition for identifying the regions in an image that may contain pets much like the skin tone classification for human flesh detection. As a result of the evolution, fur coloration of all mammals is caused by a natural organic pigment called Melanin and Melanin has only very limited color ranges. We have conducted a statistical analysis and concluded that mammal fur colors can be only in levels of gray or in two colors after the proper color quantization. This pet fur color classification algorithm has been applied for peteye detection. We also present here an algorithm for animal fur texture classification using the recently developed multi-resolution directional sub-band Contourlet transform. The experimental results are very promising as these transforms can identify regions of an image that may contain fur of mammals, scale of reptiles and feather of birds, etc. Combining the color and texture classification, one can have a set of strong classifiers for identifying possible animals in an image.

Transmission of digital images within the NTSC analog format

DOEpatents

Nickel, George H.

2004-06-15

HDTV and NTSC compatible image communication is done in a single NTSC channel bandwidth. Luminance and chrominance image data of a scene to be transmitted is obtained. The image data is quantized and digitally encoded to form digital image data in HDTV transmission format having low-resolution terms and high-resolution terms. The low-resolution digital image data terms are transformed to a voltage signal corresponding to NTSC color subcarrier modulation with retrace blanking and color bursts to form a NTSC video signal. The NTSC video signal and the high-resolution digital image data terms are then transmitted in a composite NTSC video transmission. In a NTSC receiver, the NTSC video signal is processed directly to display the scene. In a HDTV receiver, the NTSC video signal is processed to invert the color subcarrier modulation to recover the low-resolution terms, where the recovered low-resolution terms are combined with the high-resolution terms to reconstruct the scene in a high definition format.

Visual Typo Correction by Collocative Optimization: A Case Study on Merchandize Images.

PubMed

Wei, Xiao-Yong; Yang, Zhen-Qun; Ngo, Chong-Wah; Zhang, Wei

2014-02-01

Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most of the errors are introduced because of the quantization process where the visual words are considered individually, which has ignored the contextual relations among words. We propose a "spelling or phrase correction" like process for NDR, which extends the concept of collocations to visual domain for modeling the contextual relations. Binary quadratic programming is used to enforce the contextual consistency of words selected for an image, so that the errors (typos) are eliminated and the quality of the quantization process is improved. The experimental results show that the proposed method can improve the efficiency of NDR by reducing vocabulary size by 1000% times, and under the scenario of merchandize image NDR, the expensive local interest point feature used in conventional approaches can be replaced by color-moment feature, which reduces the time cost by 9202% while maintaining comparable performance to the state-of-the-art methods.

Just Noticeable Distortion Model and Its Application in Color Image Watermarking

NASA Astrophysics Data System (ADS)

Liu, Kuo-Cheng

In this paper, a perceptually adaptive watermarking scheme for color images is proposed in order to achieve robustness and transparency. A new just noticeable distortion (JND) estimator for color images is first designed in the wavelet domain. The key issue of the JND model is to effectively integrate visual masking effects. The estimator is an extension to the perceptual model that is used in image coding for grayscale images. Except for the visual masking effects given coefficient by coefficient by taking into account the luminance content and the texture of grayscale images, the crossed masking effect given by the interaction between luminance and chrominance components and the effect given by the variance within the local region of the target coefficient are investigated such that the visibility threshold for the human visual system (HVS) can be evaluated. In a locally adaptive fashion based on the wavelet decomposition, the estimator applies to all subbands of luminance and chrominance components of color images and is used to measure the visibility of wavelet quantization errors. The subband JND profiles are then incorporated into the proposed color image watermarking scheme. Performance in terms of robustness and transparency of the watermarking scheme is obtained by means of the proposed approach to embed the maximum strength watermark while maintaining the perceptually lossless quality of the watermarked color image. Simulation results show that the proposed scheme with inserting watermarks into luminance and chrominance components is more robust than the existing scheme while retaining the watermark transparency.

Evaluation of color encodings for high dynamic range pixels

NASA Astrophysics Data System (ADS)

Boitard, Ronan; Mantiuk, Rafal K.; Pouli, Tania

2015-03-01

Traditional Low Dynamic Range (LDR) color spaces encode a small fraction of the visible color gamut, which does not encompass the range of colors produced on upcoming High Dynamic Range (HDR) displays. Future imaging systems will require encoding much wider color gamut and luminance range. Such wide color gamut can be represented using floating point HDR pixel values but those are inefficient to encode. They also lack perceptual uniformity of the luminance and color distribution, which is provided (in approximation) by most LDR color spaces. Therefore, there is a need to devise an efficient, perceptually uniform and integer valued representation for high dynamic range pixel values. In this paper we evaluate several methods for encoding colour HDR pixel values, in particular for use in image and video compression. Unlike other studies we test both luminance and color difference encoding in a rigorous 4AFC threshold experiments to determine the minimum bit-depth required. Results show that the Perceptual Quantizer (PQ) encoding provides the best perceptual uniformity in the considered luminance range, however the gain in bit-depth is rather modest. More significant difference can be observed between color difference encoding schemes, from which YDuDv encoding seems to be the most efficient.

Analysis and segmentation of images in case of solving problems of detecting and tracing objects on real-time video

NASA Astrophysics Data System (ADS)

Ezhova, Kseniia; Fedorenko, Dmitriy; Chuhlamov, Anton

2016-04-01

The article deals with the methods of image segmentation based on color space conversion, and allow the most efficient way to carry out the detection of a single color in a complex background and lighting, as well as detection of objects on a homogeneous background. The results of the analysis of segmentation algorithms of this type, the possibility of their implementation for creating software. The implemented algorithm is very time-consuming counting, making it a limited application for the analysis of the video, however, it allows us to solve the problem of analysis of objects in the image if there is no dictionary of images and knowledge bases, as well as the problem of choosing the optimal parameters of the frame quantization for video analysis.

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

A Spatiotemporal Clustering Approach to Maritime Domain Awareness

DTIC Science & Technology

2013-09-01

1997. [25] M. E. Celebi, “Effective initialization of k-means for color quantization,” 16th IEEE International Conference on Image Processing (ICIP...release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Spatiotemporal clustering is the process of grouping...Department of Electrical and Computer Engineering iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Spatiotemporal clustering is the process of

Coupled binary embedding for large-scale image retrieval.

PubMed

Zheng, Liang; Wang, Shengjin; Tian, Qi

2014-08-01

Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2001-10-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, 12 combinations of color space and quantization were selected, together with 12 histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-by-example scenario. For that purpose, a set of still-picture databases was built by extracting key frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2001-01-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, twelve combinations of color space and quantization were selected, together with twelve histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-be-example scenario. For that purpose, a set of still-picture databases was built by extracting key-frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2000-12-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, twelve combinations of color space and quantization were selected, together with twelve histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-be-example scenario. For that purpose, a set of still-picture databases was built by extracting key-frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Image-adapted visually weighted quantization matrices for digital image compression

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1994-01-01

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Color image lossy compression based on blind evaluation and prediction of noise characteristics

NASA Astrophysics Data System (ADS)

Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Lepisto, Leena

2011-03-01

The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

BSIFT: toward data-independent codebook for large scale image search.

PubMed

Zhou, Wengang; Li, Houqiang; Hong, Richang; Lu, Yijuan; Tian, Qi

2015-03-01

Bag-of-Words (BoWs) model based on Scale Invariant Feature Transform (SIFT) has been widely used in large-scale image retrieval applications. Feature quantization by vector quantization plays a crucial role in BoW model, which generates visual words from the high- dimensional SIFT features, so as to adapt to the inverted file structure for the scalable retrieval. Traditional feature quantization approaches suffer several issues, such as necessity of visual codebook training, limited reliability, and update inefficiency. To avoid the above problems, in this paper, a novel feature quantization scheme is proposed to efficiently quantize each SIFT descriptor to a descriptive and discriminative bit-vector, which is called binary SIFT (BSIFT). Our quantizer is independent of image collections. In addition, by taking the first 32 bits out from BSIFT as code word, the generated BSIFT naturally lends itself to adapt to the classic inverted file structure for image indexing. Moreover, the quantization error is reduced by feature filtering, code word expansion, and query sensitive mask shielding. Without any explicit codebook for quantization, our approach can be readily applied in image search in some resource-limited scenarios. We evaluate the proposed algorithm for large scale image search on two public image data sets. Experimental results demonstrate the index efficiency and retrieval accuracy of our approach.

Optimal Compression of Floating-Point Astronomical Images Without Significant Loss of Information

NASA Technical Reports Server (NTRS)

Pence, William D.; White, R. L.; Seaman, R.

2010-01-01

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 - 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process greatly improves the precision of measurements in the more coarsely quantized images. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.

Image data compression having minimum perceptual error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1995-01-01

A method for performing image compression that eliminates redundant and invisible image components is described. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Data compression experiments with LANDSAT thematic mapper and Nimbus-7 coastal zone color scanner data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Ramapriyan, H. K.

1989-01-01

A case study is presented where an image segmentation based compression technique is applied to LANDSAT Thematic Mapper (TM) and Nimbus-7 Coastal Zone Color Scanner (CZCS) data. The compression technique, called Spatially Constrained Clustering (SCC), can be regarded as an adaptive vector quantization approach. The SCC can be applied to either single or multiple spectral bands of image data. The segmented image resulting from SCC is encoded in small rectangular blocks, with the codebook varying from block to block. Lossless compression potential (LDP) of sample TM and CZCS images are evaluated. For the TM test image, the LCP is 2.79. For the CZCS test image the LCP is 1.89, even though when only a cloud-free section of the image is considered the LCP increases to 3.48. Examples of compressed images are shown at several compression ratios ranging from 4 to 15. In the case of TM data, the compressed data are classified using the Bayes' classifier. The results show an improvement in the similarity between the classification results and ground truth when compressed data are used, thus showing that compression is, in fact, a useful first step in the analysis.

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

PubMed

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

2017-06-22

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

Modeling semantic aspects for cross-media image indexing.

PubMed

Monay, Florent; Gatica-Perez, Daniel

2007-10-01

To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Low-rate image coding using vector quantization

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

Makur, A.

1990-01-01

This thesis deals with the development and analysis of a computationally simple vector quantization image compression system for coding monochrome images at low bit rate. Vector quantization has been known to be an effective compression scheme when a low bit rate is desirable, but the intensive computation required in a vector quantization encoder has been a handicap in using it for low rate image coding. The present work shows that, without substantially increasing the coder complexity, it is indeed possible to achieve acceptable picture quality while attaining a high compression ratio. Several modifications to the conventional vector quantization coder aremore » proposed in the thesis. These modifications are shown to offer better subjective quality when compared to the basic coder. Distributed blocks are used instead of spatial blocks to construct the input vectors. A class of input-dependent weighted distortion functions is used to incorporate psychovisual characteristics in the distortion measure. Computationally simple filtering techniques are applied to further improve the decoded image quality. Finally, unique designs of the vector quantization coder using electronic neural networks are described, so that the coding delay is reduced considerably.« less

Magnetic resonance image compression using scalar-vector quantization

NASA Astrophysics Data System (ADS)

Mohsenian, Nader; Shahri, Homayoun

1995-12-01

A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

The wavelet/scalar quantization compression standard for digital fingerprint images

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

Bradley, J.N.; Brislawn, C.M.

1994-04-01

A new digital image compression standard has been adopted by the US Federal Bureau of Investigation for use on digitized gray-scale fingerprint images. The algorithm is based on adaptive uniform scalar quantization of a discrete wavelet transform image decomposition and is referred to as the wavelet/scalar quantization standard. The standard produces archival quality images at compression ratios of around 20:1 and will allow the FBI to replace their current database of paper fingerprint cards with digital imagery.

Quark and gluon production from a boost-invariantly expanding color electric field

NASA Astrophysics Data System (ADS)

Taya, Hidetoshi

2017-07-01

Particle production from an expanding classical color electromagnetic field is extensively studied, motivated by the early stage dynamics of ultrarelativistic heavy ion collisions. We develop a formalism at one-loop order to compute the particle spectra by canonically quantizing quark, gluon, and ghost fluctuations under the presence of such an expanding classical color background field; the canonical quantization is done in the τ -η coordinates in order to take into account manifestly the expanding geometry. As a demonstration, we model the expanding classical color background field by a boost-invariantly expanding homogeneous color electric field with lifetime T , for which we obtain analytically the quark and gluon production spectra by solving the equations of motion of QCD nonperturbatively with respect to the color electric field. In this paper we study (i) the finite lifetime effect, which is found to modify significantly the particle spectra from those expected from the Schwinger formula; (ii) the difference between the quark and gluon production; and (iii) the quark mass dependence of the production spectra. Implications of these results to ultrarelativistic heavy ion collisions are also discussed.

A progressive data compression scheme based upon adaptive transform coding: Mixture block coding of natural images

NASA Technical Reports Server (NTRS)

Rost, Martin C.; Sayood, Khalid

1991-01-01

A method for efficiently coding natural images using a vector-quantized variable-blocksized transform source coder is presented. The method, mixture block coding (MBC), incorporates variable-rate coding by using a mixture of discrete cosine transform (DCT) source coders. Which coders are selected to code any given image region is made through a threshold driven distortion criterion. In this paper, MBC is used in two different applications. The base method is concerned with single-pass low-rate image data compression. The second is a natural extension of the base method which allows for low-rate progressive transmission (PT). Since the base method adapts easily to progressive coding, it offers the aesthetic advantage of progressive coding without incorporating extensive channel overhead. Image compression rates of approximately 0.5 bit/pel are demonstrated for both monochrome and color images.

Image compression system and method having optimized quantization tables

NASA Technical Reports Server (NTRS)

Ratnakar, Viresh (Inventor); Livny, Miron (Inventor)

1998-01-01

A digital image compression preprocessor for use in a discrete cosine transform-based digital image compression device is provided. The preprocessor includes a gathering mechanism for determining discrete cosine transform statistics from input digital image data. A computing mechanism is operatively coupled to the gathering mechanism to calculate a image distortion array and a rate of image compression array based upon the discrete cosine transform statistics for each possible quantization value. A dynamic programming mechanism is operatively coupled to the computing mechanism to optimize the rate of image compression array against the image distortion array such that a rate-distortion-optimal quantization table is derived. In addition, a discrete cosine transform-based digital image compression device and a discrete cosine transform-based digital image compression and decompression system are provided. Also, a method for generating a rate-distortion-optimal quantization table, using discrete cosine transform-based digital image compression, and operating a discrete cosine transform-based digital image compression and decompression system are provided.

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

Stochastic quantization of (λϕ4)d scalar theory: Generalized Langevin equation with memory kernel

NASA Astrophysics Data System (ADS)

Menezes, G.; Svaiter, N. F.

2007-02-01

The method of stochastic quantization for a scalar field theory is reviewed. A brief survey for the case of self-interacting scalar field, implementing the stochastic perturbation theory up to the one-loop level, is presented. Then, it is introduced a colored random noise in the Einstein's relations, a common prescription employed by one of the stochastic regularizations, to control the ultraviolet divergences of the theory. This formalism is extended to the case where a Langevin equation with a memory kernel is used. It is shown that, maintaining the Einstein's relations with a colored noise, there is convergence to a non-regularized theory.

Quantization Distortion in Block Transform-Compressed Data

NASA Technical Reports Server (NTRS)

Boden, A. F.

1995-01-01

The popular JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into block that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. A generic block transform model is introduced.

Application of heterogeneous pulse coupled neural network in image quantization

NASA Astrophysics Data System (ADS)

Huang, Yi; Ma, Yide; Li, Shouliang; Zhan, Kun

2016-11-01

On the basis of the different strengths of synaptic connections between actual neurons, this paper proposes a heterogeneous pulse coupled neural network (HPCNN) algorithm to perform quantization on images. HPCNNs are developed from traditional pulse coupled neural network (PCNN) models, which have different parameters corresponding to different image regions. This allows pixels of different gray levels to be classified broadly into two categories: background regional and object regional. Moreover, an HPCNN also satisfies human visual characteristics. The parameters of the HPCNN model are calculated automatically according to these categories, and quantized results will be optimal and more suitable for humans to observe. At the same time, the experimental results of natural images from the standard image library show the validity and efficiency of our proposed quantization method.

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

PubMed

Li, Yeqing; Liu, Wei; Huang, Junzhou

2018-06-01

Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning. As case studies, we apply the sub-selection algorithm to several popular quantization techniques including cases using linear and nonlinear mappings. Crucially, we can justify the resulting sub-selective quantization by proving its theoretic properties. Extensive experiments are carried out on three image benchmarks with up to one million samples, corroborating the efficacy of the sub-selective quantization method in terms of image retrieval.

A hybrid LBG/lattice vector quantizer for high quality image coding

NASA Technical Reports Server (NTRS)

Ramamoorthy, V.; Sayood, K.; Arikan, E. (Editor)

1991-01-01

It is well known that a vector quantizer is an efficient coder offering a good trade-off between quantization distortion and bit rate. The performance of a vector quantizer asymptotically approaches the optimum bound with increasing dimensionality. A vector quantized image suffers from the following types of degradations: (1) edge regions in the coded image contain staircase effects, (2) quasi-constant or slowly varying regions suffer from contouring effects, and (3) textured regions lose details and suffer from granular noise. All three of these degradations are due to the finite size of the code book, the distortion measures used in the design, and due to the finite training procedure involved in the construction of the code book. In this paper, we present an adaptive technique which attempts to ameliorate the edge distortion and contouring effects.

High Order Entropy-Constrained Residual VQ for Lossless Compression of Images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen

1995-01-01

High order entropy coding is a powerful technique for exploiting high order statistical dependencies. However, the exponentially high complexity associated with such a method often discourages its use. In this paper, an entropy-constrained residual vector quantization method is proposed for lossless compression of images. The method consists of first quantizing the input image using a high order entropy-constrained residual vector quantizer and then coding the residual image using a first order entropy coder. The distortion measure used in the entropy-constrained optimization is essentially the first order entropy of the residual image. Experimental results show very competitive performance.

2-Step scalar deadzone quantization for bitplane image coding.

PubMed

Auli-Llinas, Francesc

2013-12-01

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform scalar deadzone quantization (USDQ) together with a bitplane coding strategy. This paper introduces a 2-step scalar deadzone quantization (2SDQ) scheme that achieves same coding performance as that of USDQ while reducing the coding passes and the emitted symbols of the bitplane coding engine. This serves to reduce the computational costs of the codec and/or to code high dynamic range images. The main insights behind 2SDQ are the use of two quantization step sizes that approximate wavelet coefficients with more or less precision depending on their density, and a rate-distortion optimization technique that adjusts the distortion decreases produced when coding 2SDQ indexes. The integration of 2SDQ in current codecs is straightforward. The applicability and efficiency of 2SDQ are demonstrated within the framework of JPEG2000.

Fast large-scale object retrieval with binary quantization

NASA Astrophysics Data System (ADS)

Zhou, Shifu; Zeng, Dan; Shen, Wei; Zhang, Zhijiang; Tian, Qi

2015-11-01

The objective of large-scale object retrieval systems is to search for images that contain the target object in an image database. Where state-of-the-art approaches rely on global image representations to conduct searches, we consider many boxes per image as candidates to search locally in a picture. In this paper, a feature quantization algorithm called binary quantization is proposed. In binary quantization, a scale-invariant feature transform (SIFT) feature is quantized into a descriptive and discriminative bit-vector, which allows itself to adapt to the classic inverted file structure for box indexing. The inverted file, which stores the bit-vector and box ID where the SIFT feature is located inside, is compact and can be loaded into the main memory for efficient box indexing. We evaluate our approach on available object retrieval datasets. Experimental results demonstrate that the proposed approach is fast and achieves excellent search quality. Therefore, the proposed approach is an improvement over state-of-the-art approaches for object retrieval.

Reducing weight precision of convolutional neural networks towards large-scale on-chip image recognition

NASA Astrophysics Data System (ADS)

Ji, Zhengping; Ovsiannikov, Ilia; Wang, Yibing; Shi, Lilong; Zhang, Qiang

2015-05-01

In this paper, we develop a server-client quantization scheme to reduce bit resolution of deep learning architecture, i.e., Convolutional Neural Networks, for image recognition tasks. Low bit resolution is an important factor in bringing the deep learning neural network into hardware implementation, which directly determines the cost and power consumption. We aim to reduce the bit resolution of the network without sacrificing its performance. To this end, we design a new quantization algorithm called supervised iterative quantization to reduce the bit resolution of learned network weights. In the training stage, the supervised iterative quantization is conducted via two steps on server - apply k-means based adaptive quantization on learned network weights and retrain the network based on quantized weights. These two steps are alternated until the convergence criterion is met. In this testing stage, the network configuration and low-bit weights are loaded to the client hardware device to recognize coming input in real time, where optimized but expensive quantization becomes infeasible. Considering this, we adopt a uniform quantization for the inputs and internal network responses (called feature maps) to maintain low on-chip expenses. The Convolutional Neural Network with reduced weight and input/response precision is demonstrated in recognizing two types of images: one is hand-written digit images and the other is real-life images in office scenarios. Both results show that the new network is able to achieve the performance of the neural network with full bit resolution, even though in the new network the bit resolution of both weight and input are significantly reduced, e.g., from 64 bits to 4-5 bits.

A Low Power Digital Accumulation Technique for Digital-Domain CMOS TDI Image Sensor.

PubMed

Yu, Changwei; Nie, Kaiming; Xu, Jiangtao; Gao, Jing

2016-09-23

In this paper, an accumulation technique suitable for digital domain CMOS time delay integration (TDI) image sensors is proposed to reduce power consumption without degrading the rate of imaging. In terms of the slight variations of quantization codes among different pixel exposures towards the same object, the pixel array is divided into two groups: one is for coarse quantization of high bits only, and the other one is for fine quantization of low bits. Then, the complete quantization codes are composed of both results from the coarse-and-fine quantization. The equivalent operation comparably reduces the total required bit numbers of the quantization. In the 0.18 µm CMOS process, two versions of 16-stage digital domain CMOS TDI image sensor chains based on a 10-bit successive approximate register (SAR) analog-to-digital converter (ADC), with and without the proposed technique, are designed. The simulation results show that the average power consumption of slices of the two versions are 6 . 47 × 10 - 8 J/line and 7 . 4 × 10 - 8 J/line, respectively. Meanwhile, the linearity of the two versions are 99.74% and 99.99%, respectively.

Entropy-aware projected Landweber reconstruction for quantized block compressive sensing of aerial imagery

NASA Astrophysics Data System (ADS)

Liu, Hao; Li, Kangda; Wang, Bing; Tang, Hainie; Gong, Xiaohui

2017-01-01

A quantized block compressive sensing (QBCS) framework, which incorporates the universal measurement, quantization/inverse quantization, entropy coder/decoder, and iterative projected Landweber reconstruction, is summarized. Under the QBCS framework, this paper presents an improved reconstruction algorithm for aerial imagery, QBCS, with entropy-aware projected Landweber (QBCS-EPL), which leverages the full-image sparse transform without Wiener filter and an entropy-aware thresholding model for wavelet-domain image denoising. Through analyzing the functional relation between the soft-thresholding factors and entropy-based bitrates for different quantization methods, the proposed model can effectively remove wavelet-domain noise of bivariate shrinkage and achieve better image reconstruction quality. For the overall performance of QBCS reconstruction, experimental results demonstrate that the proposed QBCS-EPL algorithm significantly outperforms several existing algorithms. With the experiment-driven methodology, the QBCS-EPL algorithm can obtain better reconstruction quality at a relatively moderate computational cost, which makes it more desirable for aerial imagery applications.

Efficient storage and management of radiographic images using a novel wavelet-based multiscale vector quantizer

NASA Astrophysics Data System (ADS)

Yang, Shuyu; Mitra, Sunanda

2002-05-01

Due to the huge volumes of radiographic images to be managed in hospitals, efficient compression techniques yielding no perceptual loss in the reconstructed images are becoming a requirement in the storage and management of such datasets. A wavelet-based multi-scale vector quantization scheme that generates a global codebook for efficient storage and transmission of medical images is presented in this paper. The results obtained show that even at low bit rates one is able to obtain reconstructed images with perceptual quality higher than that of the state-of-the-art scalar quantization method, the set partitioning in hierarchical trees.

Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images.

PubMed

Liu, Xianming; Cheung, Gene; Lin, Chia-Wen; Zhao, Debin; Gao, Wen

2018-07-01

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors-sparsity prior and graph-signal smoothness prior-for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB).

Performance of customized DCT quantization tables on scientific data

NASA Technical Reports Server (NTRS)

Ratnakar, Viresh; Livny, Miron

1994-01-01

We show that it is desirable to use data-specific or customized quantization tables for scaling the spatial frequency coefficients obtained using the Discrete Cosine Transform (DCT). DCT is widely used for image and video compression (MP89, PM93) but applications typically use default quantization matrices. Using actual scientific data gathered from divers sources such as spacecrafts and electron-microscopes, we show that the default compression/quality tradeoffs can be significantly improved upon by using customized tables. We also show that significant improvements are possible for the standard test images Lena and Baboon. This work is part of an effort to develop a practical scheme for optimizing quantization matrices for any given image or video stream, under any given quality or compression constraints.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

PubMed Central

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. PMID:23049544

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

PubMed

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

Perceptual compression of magnitude-detected synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Werness, Susan A.

1994-01-01

A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.

Direct Volume Rendering with Shading via Three-Dimensional Textures

NASA Technical Reports Server (NTRS)

VanGelder, Allen; Kim, Kwansik

1996-01-01

A new and easy-to-implement method for direct volume rendering that uses 3D texture maps for acceleration, and incorporates directional lighting, is described. The implementation, called Voltx, produces high-quality images at nearly interactive speeds on workstations with hardware support for three-dimensional texture maps. Previously reported methods did not incorporate a light model, and did not address issues of multiple texture maps for large volumes. Our research shows that these extensions impact performance by about a factor of ten. Voltx supports orthographic, perspective, and stereo views. This paper describes the theory and implementation of this technique, and compares it to the shear-warp factorization approach. A rectilinear data set is converted into a three-dimensional texture map containing color and opacity information. Quantized normal vectors and a lookup table provide efficiency. A new tesselation of the sphere is described, which serves as the basis for normal-vector quantization. A new gradient-based shading criterion is described, in which the gradient magnitude is interpreted in the context of the field-data value and the material classification parameters, and not in isolation. In the rendering phase, the texture map is applied to a stack of parallel planes, which effectively cut the texture into many slabs. The slabs are composited to form an image.

Electronic Photography at the NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Holm, Jack; Judge, Nancianne

1995-01-01

An electronic photography facility has been established in the Imaging & Photographic Technology Section, Visual Imaging Branch, at the NASA Langley Research Center (LaRC). The purpose of this facility is to provide the LaRC community with access to digital imaging technology. In particular, capabilities have been established for image scanning, direct image capture, optimized image processing for storage, image enhancement, and optimized device dependent image processing for output. Unique approaches include: evaluation and extraction of the entire film information content through scanning; standardization of image file tone reproduction characteristics for optimal bit utilization and viewing; education of digital imaging personnel on the effects of sampling and quantization to minimize image processing related information loss; investigation of the use of small kernel optimal filters for image restoration; characterization of a large array of output devices and development of image processing protocols for standardized output. Currently, the laboratory has a large collection of digital image files which contain essentially all the information present on the original films. These files are stored at 8-bits per color, but the initial image processing was done at higher bit depths and/or resolutions so that the full 8-bits are used in the stored files. The tone reproduction of these files has also been optimized so the available levels are distributed according to visual perceptibility. Look up tables are available which modify these files for standardized output on various devices, although color reproduction has been allowed to float to some extent to allow for full utilization of output device gamut.

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design

PubMed Central

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-01-01

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. PMID:27886061

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.

PubMed

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-11-23

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.

DCTune Perceptual Optimization of Compressed Dental X-Rays

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

1996-01-01

In current dental practice, x-rays of completed dental work are often sent to the insurer for verification. It is faster and cheaper to transmit instead digital scans of the x-rays. Further economies result if the images are sent in compressed form. DCTune is a technology for optimizing DCT (digital communication technology) quantization matrices to yield maximum perceptual quality for a given bit-rate, or minimum bit-rate for a given perceptual quality. Perceptual optimization of DCT color quantization matrices. In addition, the technology provides a means of setting the perceptual quality of compressed imagery in a systematic way. The purpose of this research was, with respect to dental x-rays, 1) to verify the advantage of DCTune over standard JPEG (Joint Photographic Experts Group), 2) to verify the quality control feature of DCTune, and 3) to discover regularities in the optimized matrices of a set of images. We optimized matrices for a total of 20 images at two resolutions (150 and 300 dpi) and four bit-rates (0.25, 0.5, 0.75, 1.0 bits/pixel), and examined structural regularities in the resulting matrices. We also conducted psychophysical studies (1) to discover the DCTune quality level at which the images became 'visually lossless,' and (2) to rate the relative quality of DCTune and standard JPEG images at various bitrates. Results include: (1) At both resolutions, DCTune quality is a linear function of bit-rate. (2) DCTune quantization matrices for all images at all bitrates and resolutions are modeled well by an inverse Gaussian, with parameters of amplitude and width. (3) As bit-rate is varied, optimal values of both amplitude and width covary in an approximately linear fashion. (4) Both amplitude and width vary in systematic and orderly fashion with either bit-rate or DCTune quality; simple mathematical functions serve to describe these relationships. (5) In going from 150 to 300 dpi, amplitude parameters are substantially lower and widths larger at corresponding bit-rates or qualities. (6) Visually lossless compression occurs at a DCTune quality value of about 1. (7) At 0.25 bits/pixel, comparative ratings give DCTune a substantial advantage over standard JPEG. As visually lossless bit-rates are approached, this advantage of necessity diminishes. We have concluded that DCTune optimized quantization matrices provide better visual quality than standard JPEG. Meaningful quality levels may be specified by means of the DCTune metric. Optimized matrices are very similar across the class of dental x-rays, suggesting the possibility of a 'class-optimal' matrix. DCTune technology appears to provide some value in the context of compressed dental x-rays.

Subband directional vector quantization in radiological image compression

NASA Astrophysics Data System (ADS)

Akrout, Nabil M.; Diab, Chaouki; Prost, Remy; Goutte, Robert; Amiel, Michel

1992-05-01

The aim of this paper is to propose a new scheme for image compression. The method is very efficient for images which have directional edges such as the tree-like structure of the coronary vessels in digital angiograms. This method involves two steps. First, the original image is decomposed at different resolution levels using a pyramidal subband decomposition scheme. For decomposition/reconstruction of the image, free of aliasing and boundary errors, we use an ideal band-pass filter bank implemented in the Discrete Cosine Transform domain (DCT). Second, the high-frequency subbands are vector quantized using a multiresolution codebook with vertical and horizontal codewords which take into account the edge orientation of each subband. The proposed method reduces the blocking effect encountered at low bit rates in conventional vector quantization.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Rate and power efficient image compressed sensing and transmission

NASA Astrophysics Data System (ADS)

Olanigan, Saheed; Cao, Lei; Viswanathan, Ramanarayanan

2016-01-01

This paper presents a suboptimal quantization and transmission scheme for multiscale block-based compressed sensing images over wireless channels. The proposed method includes two stages: dealing with quantization distortion and transmission errors. First, given the total transmission bit rate, the optimal number of quantization bits is assigned to the sensed measurements in different wavelet sub-bands so that the total quantization distortion is minimized. Second, given the total transmission power, the energy is allocated to different quantization bit layers based on their different error sensitivities. The method of Lagrange multipliers with Karush-Kuhn-Tucker conditions is used to solve both optimization problems, for which the first problem can be solved with relaxation and the second problem can be solved completely. The effectiveness of the scheme is illustrated through simulation results, which have shown up to 10 dB improvement over the method without the rate and power optimization in medium and low signal-to-noise ratio cases.

A recursive technique for adaptive vector quantization

NASA Technical Reports Server (NTRS)

Lindsay, Robert A.

1989-01-01

Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Wavelet/scalar quantization compression standard for fingerprint images

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

Brislawn, C.M.

1996-06-12

US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class ofmore » potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.« less

MIAQuant, a novel system for automatic segmentation, measurement, and localization comparison of different biomarkers from serialized histological slices.

PubMed

Casiraghi, Elena; Cossa, Mara; Huber, Veronica; Rivoltini, Licia; Tozzi, Matteo; Villa, Antonello; Vergani, Barbara

2017-11-02

In the clinical practice, automatic image analysis methods quickly quantizing histological results by objective and replicable methods are getting more and more necessary and widespread. Despite several commercial software products are available for this task, they are very little flexible, and provided as black boxes without modifiable source code. To overcome the aforementioned problems, we employed the commonly used MATLAB platform to develop an automatic method, MIAQuant, for the analysis of histochemical and immunohistochemical images, stained with various methods and acquired by different tools. It automatically extracts and quantifies markers characterized by various colors and shapes; furthermore, it aligns contiguous tissue slices stained by different markers and overlaps them with differing colors for visual comparison of their localization. Application of MIAQuant for clinical research fields, such as oncology and cardiovascular disease studies, has proven its efficacy, robustness and flexibility with respect to various problems; we highlight that, the flexibility of MIAQuant makes it an important tool to be exploited for basic researches where needs are constantly changing. MIAQuant software and its user manual are freely available for clinical studies, pathological research, and diagnosis.

On-chip frame memory reduction using a high-compression-ratio codec in the overdrives of liquid-crystal displays

NASA Astrophysics Data System (ADS)

Wang, Jun; Min, Kyeong-Yuk; Chong, Jong-Wha

2010-11-01

Overdrive is commonly used to reduce the liquid-crystal response time and motion blur in liquid-crystal displays (LCDs). However, overdrive requires a large frame memory in order to store the previous frame for reference. In this paper, a high-compression-ratio codec is presented to compress the image data stored in the on-chip frame memory so that only 1 Mbit of on-chip memory is required in the LCD overdrives of mobile devices. The proposed algorithm further compresses the color bitmaps and representative values (RVs) resulting from the block truncation coding (BTC). The color bitmaps are represented by a luminance bitmap, which is further reduced and reconstructed using median filter interpolation in the decoder, while the RVs are compressed using adaptive quantization coding (AQC). Interpolation and AQC can provide three-level compression, which leads to 16 combinations. Using a rate-distortion analysis, we select the three optimal schemes to compress the image data for video graphics array (VGA), wide-VGA LCD, and standard-definitionTV applications. Our simulation results demonstrate that the proposed schemes outperform interpolation BTC both in PSNR (by 1.479 to 2.205 dB) and in subjective visual quality.

Visually Lossless JPEG 2000 for Remote Image Browsing

PubMed Central

Oh, Han; Bilgin, Ali; Marcellin, Michael

2017-01-01

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of (spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting (multiple) quantization step sizes into a single JPEG2000 codestream. This codestream is JPEG2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG2000 Interactive Protocol (JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results. PMID:28748112

Fusion of Deep Learning and Compressed Domain features for Content Based Image Retrieval.

PubMed

Liu, Peizhong; Guo, Jing-Ming; Wu, Chi-Yi; Cai, Danlin

2017-08-29

This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate. Two metrics, average precision rate (APR) and average recall rate (ARR), are employed to examine various datasets. As documented in the experimental results, the proposed schemes can achieve superior performance compared to the state-of-the-art methods with either low- or high-level features in terms of the retrieval rate. Thus, it can be a strong candidate for various image retrieval related applications.

Automatic Generation of Caricatures with Multiple Expressions Using Transformative Approach

NASA Astrophysics Data System (ADS)

Liao, Wen-Hung; Lai, Chien-An

The proliferation of digital cameras has changed the way we create and share photos. Novel forms of photo composition and reproduction have surfaced in recent years. In this paper, we present an automatic caricature generation system using transformative approaches. By combing facial feature detection, image segmentation and image warping/morphing techniques, the system is able to generate stylized caricature using only one reference image. When more than one reference sample are available, the system can either choose the best fit based on shape matching, or synthesize a composite style using polymorph technique. The system can also produce multiple expressions by controlling a subset of MPEG-4 facial animation parameters (FAP). Finally, to enable flexible manipulation of the synthetic caricature, we also investigate issues such as color quantization and raster-to-vector conversion. A major strength of our method is that the synthesized caricature bears a higher degree of resemblance to the real person than traditional component-based approaches.

Vector quantization

NASA Technical Reports Server (NTRS)

Gray, Robert M.

1989-01-01

During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility promised by Shannon's source coding theorems into a powerful and competitive technique for speech and image coding and compression at medium to low bit rates. In this survey, the basic ideas behind the design of vector quantizers are sketched and some comments made on the state-of-the-art and current research efforts.

Investigation of digital encoding techniques for television transmission

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1983-01-01

Composite color television signals are sampled at four times the color subcarrier and transformed using intraframe two dimensional Walsh functions. It is shown that by properly sampling a composite color signal and employing a Walsh transform the YIQ time signals which sum to produce the composite color signal can be represented, in the transform domain, by three component signals in space. By suitably zonal quantizing the transform coefficients, the YIQ signals can be processed independently to achieve data compression and obtain the same results as component coding. Computer simulations of three bandwidth compressors operating at 1.09, 1.53 and 1.8 bits/ sample are presented. The above results can also be applied to the PAL color system.

Optimal sampling and quantization of synthetic aperture radar signals

NASA Technical Reports Server (NTRS)

Wu, C.

1978-01-01

Some theoretical and experimental results on optimal sampling and quantization of synthetic aperture radar (SAR) signals are presented. It includes a description of a derived theoretical relationship between the pixel signal to noise ratio of processed SAR images and the number of quantization bits per sampled signal, assuming homogeneous extended targets. With this relationship known, a solution may be realized for the problem of optimal allocation of a fixed data bit-volume (for specified surface area and resolution criterion) between the number of samples and the number of bits per sample. The results indicate that to achieve the best possible image quality for a fixed bit rate and a given resolution criterion, one should quantize individual samples coarsely and thereby maximize the number of multiple looks. The theoretical results are then compared with simulation results obtained by processing aircraft SAR data.

Justification of Fuzzy Declustering Vector Quantization Modeling in Classification of Genotype-Image Phenotypes

NASA Astrophysics Data System (ADS)

Ng, Theam Foo; Pham, Tuan D.; Zhou, Xiaobo

2010-01-01

With the fast development of multi-dimensional data compression and pattern classification techniques, vector quantization (VQ) has become a system that allows large reduction of data storage and computational effort. One of the most recent VQ techniques that handle the poor estimation of vector centroids due to biased data from undersampling is to use fuzzy declustering-based vector quantization (FDVQ) technique. Therefore, in this paper, we are motivated to propose a justification of FDVQ based hidden Markov model (HMM) for investigating its effectiveness and efficiency in classification of genotype-image phenotypes. The performance evaluation and comparison of the recognition accuracy between a proposed FDVQ based HMM (FDVQ-HMM) and a well-known LBG (Linde, Buzo, Gray) vector quantization based HMM (LBG-HMM) will be carried out. The experimental results show that the performances of both FDVQ-HMM and LBG-HMM are almost similar. Finally, we have justified the competitiveness of FDVQ-HMM in classification of cellular phenotype image database by using hypotheses t-test. As a result, we have validated that the FDVQ algorithm is a robust and an efficient classification technique in the application of RNAi genome-wide screening image data.

Text Line Detection from Rectangle Traffic Panels of Natural Scene

NASA Astrophysics Data System (ADS)

Wang, Shiyuan; Huang, Linlin; Hu, Jian

2018-01-01

Traffic sign detection and recognition is very important for Intelligent Transportation. Among traffic signs, traffic panel contains rich information. However, due to low resolution and blur in the rectangular traffic panel, it is difficult to extract the character and symbols. In this paper, we propose a coarse-to-fine method to detect the Chinese character on traffic panels from natural scenes. Given a traffic panel Color Quantization is applied to extract candidate regions of Chinese characters. Second, a multi-stage filter based on learning is applied to discard the non-character regions. Third, we aggregate the characters for text lines by Distance Metric Learning method. Experimental results on real traffic images from Baidu Street View demonstrate the effectiveness of the proposed method.

Experimental Studies on a Compact Storage Scheme for Wavelet-based Multiresolution Subregion Retrieval

NASA Technical Reports Server (NTRS)

Poulakidas, A.; Srinivasan, A.; Egecioglu, O.; Ibarra, O.; Yang, T.

1996-01-01

Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress images effectively. In order to use them for image library systems, a compact storage scheme for quantized coefficient wavelet data must be developed with a support for fast subregion retrieval. We have designed such a scheme and in this paper we provide experimental studies to demonstrate that it achieves good image compression ratios, while providing a natural indexing mechanism that facilitates fast retrieval of portions of the image at various resolutions.

Cascade Error Projection with Low Bit Weight Quantization for High Order Correlation Data

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher

1998-01-01

In this paper, we reinvestigate the solution for chaotic time series prediction problem using neural network approach. The nature of this problem is such that the data sequences are never repeated, but they are rather in chaotic region. However, these data sequences are correlated between past, present, and future data in high order. We use Cascade Error Projection (CEP) learning algorithm to capture the high order correlation between past and present data to predict a future data using limited weight quantization constraints. This will help to predict a future information that will provide us better estimation in time for intelligent control system. In our earlier work, it has been shown that CEP can sufficiently learn 5-8 bit parity problem with 4- or more bits, and color segmentation problem with 7- or more bits of weight quantization. In this paper, we demonstrate that chaotic time series can be learned and generalized well with as low as 4-bit weight quantization using round-off and truncation techniques. The results show that generalization feature will suffer less as more bit weight quantization is available and error surfaces with the round-off technique are more symmetric around zero than error surfaces with the truncation technique. This study suggests that CEP is an implementable learning technique for hardware consideration.

Minimum uncertainty and squeezing in diffusion processes and stochastic quantization

NASA Technical Reports Server (NTRS)

Demartino, S.; Desiena, S.; Illuminati, Fabrizo; Vitiello, Giuseppe

1994-01-01

We show that uncertainty relations, as well as minimum uncertainty coherent and squeezed states, are structural properties for diffusion processes. Through Nelson stochastic quantization we derive the stochastic image of the quantum mechanical coherent and squeezed states.

Image-adaptive and robust digital wavelet-domain watermarking for images

NASA Astrophysics Data System (ADS)

Zhao, Yi; Zhang, Liping

2018-03-01

We propose a new frequency domain wavelet based watermarking technique. The key idea of our scheme is twofold: multi-tier solution representation of image and odd-even quantization embedding/extracting watermark. Because many complementary watermarks need to be hidden, the watermark image designed is image-adaptive. The meaningful and complementary watermark images was embedded into the original image (host image) by odd-even quantization modifying coefficients, which was selected from the detail wavelet coefficients of the original image, if their magnitudes are larger than their corresponding Just Noticeable Difference thresholds. The tests show good robustness against best-known attacks such as noise addition, image compression, median filtering, clipping as well as geometric transforms. Further research may improve the performance by refining JND thresholds.

Direct Images, Fields of Hilbert Spaces, and Geometric Quantization

NASA Astrophysics Data System (ADS)

Lempert, László; Szőke, Róbert

2014-04-01

Geometric quantization often produces not one Hilbert space to represent the quantum states of a classical system but a whole family H s of Hilbert spaces, and the question arises if the spaces H s are canonically isomorphic. Axelrod et al. (J. Diff. Geo. 33:787-902, 1991) and Hitchin (Commun. Math. Phys. 131:347-380, 1990) suggest viewing H s as fibers of a Hilbert bundle H, introduce a connection on H, and use parallel transport to identify different fibers. Here we explore to what extent this can be done. First we introduce the notion of smooth and analytic fields of Hilbert spaces, and prove that if an analytic field over a simply connected base is flat, then it corresponds to a Hermitian Hilbert bundle with a flat connection and path independent parallel transport. Second we address a general direct image problem in complex geometry: pushing forward a Hermitian holomorphic vector bundle along a non-proper map . We give criteria for the direct image to be a smooth field of Hilbert spaces. Third we consider quantizing an analytic Riemannian manifold M by endowing TM with the family of adapted Kähler structures from Lempert and Szőke (Bull. Lond. Math. Soc. 44:367-374, 2012). This leads to a direct image problem. When M is homogeneous, we prove the direct image is an analytic field of Hilbert spaces. For certain such M—but not all—the direct image is even flat; which means that in those cases quantization is unique.

Learning vector quantization neural networks improve accuracy of transcranial color-coded duplex sonography in detection of middle cerebral artery spasm--preliminary report.

PubMed

Swiercz, Miroslaw; Kochanowicz, Jan; Weigele, John; Hurst, Robert; Liebeskind, David S; Mariak, Zenon; Melhem, Elias R; Krejza, Jaroslaw

2008-01-01

To determine the performance of an artificial neural network in transcranial color-coded duplex sonography (TCCS) diagnosis of middle cerebral artery (MCA) spasm. TCCS was prospectively acquired within 2 h prior to routine cerebral angiography in 100 consecutive patients (54M:46F, median age 50 years). Angiographic MCA vasospasm was classified as mild (<25% of vessel caliber reduction), moderate (25-50%), or severe (>50%). A Learning Vector Quantization neural network classified MCA spasm based on TCCS peak-systolic, mean, and end-diastolic velocity data. During a four-class discrimination task, accurate classification by the network ranged from 64.9% to 72.3%, depending on the number of neurons in the Kohonen layer. Accurate classification of vasospasm ranged from 79.6% to 87.6%, with an accuracy of 84.7% to 92.1% for the detection of moderate-to-severe vasospasm. An artificial neural network may increase the accuracy of TCCS in diagnosis of MCA spasm.

Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1994-01-01

A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

Compression of digital images over local area networks. Appendix 1: Item 3. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gorjala, Bhargavi

1991-01-01

Differential Pulse Code Modulation (DPCM) has been used with speech for many years. It has not been as successful for images because of poor edge performance. The only corruption in DPC is quantizer error but this corruption becomes quite large in the region of an edge because of the abrupt changes in the statistics of the signal. We introduce two improved DPCM schemes; Edge correcting DPCM and Edge Preservation Differential Coding. These two coding schemes will detect the edges and take action to correct them. In an Edge Correcting scheme, the quantizer error for an edge is encoded using a recursive quantizer with entropy coding and sent to the receiver as side information. In an Edge Preserving scheme, when the quantizer input falls in the overload region, the quantizer error is encoded and sent to the receiver repeatedly until the quantizer input falls in the inner levels. Therefore these coding schemes increase the bit rate in the region of an edge and require variable rate channels. We implement these two variable rate coding schemes on a token wing network. Timed token protocol supports two classes of messages; asynchronous and synchronous. The synchronous class provides a pre-allocated bandwidth and guaranteed response time. The remaining bandwidth is dynamically allocated to the asynchronous class. The Edge Correcting DPCM is simulated by considering the edge information under the asynchronous class. For the simulation of the Edge Preserving scheme, the amount of information sent each time is fixed, but the length of the packet or the bit rate for that packet is chosen depending on the availability capacity. The performance of the network, and the performance of the image coding algorithms, is studied.

Survey of adaptive image coding techniques

NASA Technical Reports Server (NTRS)

Habibi, A.

1977-01-01

The general problem of image data compression is discussed briefly with attention given to the use of Karhunen-Loeve transforms, suboptimal systems, and block quantization. A survey is then conducted encompassing the four categories of adaptive systems: (1) adaptive transform coding (adaptive sampling, adaptive quantization, etc.), (2) adaptive predictive coding (adaptive delta modulation, adaptive DPCM encoding, etc.), (3) adaptive cluster coding (blob algorithms and the multispectral cluster coding technique), and (4) adaptive entropy coding.

Perceptually-Based Adaptive JPEG Coding

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Rosenholtz, Ruth; Null, Cynthia H. (Technical Monitor)

1996-01-01

An extension to the JPEG standard (ISO/IEC DIS 10918-3) allows spatial adaptive coding of still images. As with baseline JPEG coding, one quantization matrix applies to an entire image channel, but in addition the user may specify a multiplier for each 8 x 8 block, which multiplies the quantization matrix, yielding the new matrix for the block. MPEG 1 and 2 use much the same scheme, except there the multiplier changes only on macroblock boundaries. We propose a method for perceptual optimization of the set of multipliers. We compute the perceptual error for each block based upon DCT quantization error adjusted according to contrast sensitivity, light adaptation, and contrast masking, and pick the set of multipliers which yield maximally flat perceptual error over the blocks of the image. We investigate the bitrate savings due to this adaptive coding scheme and the relative importance of the different sorts of masking on adaptive coding.

Predicting chroma from luma with frequency domain intra prediction

NASA Astrophysics Data System (ADS)

Egge, Nathan E.; Valin, Jean-Marc

2015-03-01

This paper describes a technique for performing intra prediction of the chroma planes based on the reconstructed luma plane in the frequency domain. This prediction exploits the fact that while RGB to YUV color conversion has the property that it decorrelates the color planes globally across an image, there is still some correlation locally at the block level.1 Previous proposals compute a linear model of the spatial relationship between the luma plane (Y) and the two chroma planes (U and V).2 In codecs that use lapped transforms this is not possible since transform support extends across the block boundaries3 and thus neighboring blocks are unavailable during intra- prediction. We design a frequency domain intra predictor for chroma that exploits the same local correlation with lower complexity than the spatial predictor and which works with lapped transforms. We then describe a low- complexity algorithm that directly uses luma coefficients as a chroma predictor based on gain-shape quantization and band partitioning. An experiment is performed that compares these two techniques inside the experimental Daala video codec and shows the lower complexity algorithm to be a better chroma predictor.

Combining Vector Quantization and Histogram Equalization.

ERIC Educational Resources Information Center

Cosman, Pamela C.; And Others

1992-01-01

Discussion of contrast enhancement techniques focuses on the use of histogram equalization with a data compression technique, i.e., tree-structured vector quantization. The enhancement technique of intensity windowing is described, and the use of enhancement techniques for medical images is explained, including adaptive histogram equalization.…

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

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

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-05-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI`s Integrated Automated Fingerprint Identification System.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

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

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-01-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI's Integrated Automated Fingerprint Identification System.

Digital television system design study

NASA Technical Reports Server (NTRS)

Huth, G. K.

1976-01-01

The use of digital techniques for transmission of pictorial data is discussed for multi-frame images (television). Video signals are processed in a manner which includes quantization and coding such that they are separable from the noise introduced into the channel. The performance of digital television systems is determined by the nature of the processing techniques (i.e., whether the video signal itself or, instead, something related to the video signal is quantized and coded) and to the quantization and coding schemes employed.

Vector quantizer based on brightness maps for image compression with the polynomial transform

NASA Astrophysics Data System (ADS)

Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

2002-11-01

We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be a unique tool to structurally classify the image block within a given lattice. This particular operation intends to be one of the main contributions of this work. The fifth section will fuse the proposals derived from the study of the three main topics- addressed in the last sections- in order to propose an image compression model that takes advantage of vector quantizers inside the brightness transformed domain to determine the most important structures, finding the energy distribution inside the Hermite domain. Sixth and last section will show some results obtained while testing the coding-decoding model. The guidelines to evaluate the image compressing performance were the compression ratio, SNR and psycho-visual quality. Some conclusions derived from the research and possible unexplored paths will be shown on this section as well.

Subband/transform functions for image processing

NASA Technical Reports Server (NTRS)

Glover, Daniel

1993-01-01

Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.

Helicity amplitudes for QCD with massive quarks

NASA Astrophysics Data System (ADS)

Ochirov, Alexander

2018-04-01

The novel massive spinor-helicity formalism of Arkani-Hamed, Huang and Huang provides an elegant way to calculate scattering amplitudes in quantum chromodynamics for arbitrary quark spin projections. In this note we compute two families of tree-level QCD amplitudes with one massive quark pair and n - 2 gluons. The two cases include all gluons with identical helicity and one opposite-helicity gluon being color-adjacent to one of the quarks. Our results naturally incorporate the previously known amplitudes for both quark spins quantized along one of the gluonic momenta. In the all-multiplicity formulae presented here the spin quantization axes can be tuned at will, which includes the case of the definite-helicity quark states.

Synthetic aperture radar signal data compression using block adaptive quantization

NASA Technical Reports Server (NTRS)

Kuduvalli, Gopinath; Dutkiewicz, Melanie; Cumming, Ian

1994-01-01

This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

The FBI compression standard for digitized fingerprint images

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

Brislawn, C.M.; Bradley, J.N.; Onyshczak, R.J.

1996-10-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the currentmore » status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.« less

FBI compression standard for digitized fingerprint images

NASA Astrophysics Data System (ADS)

Brislawn, Christopher M.; Bradley, Jonathan N.; Onyshczak, Remigius J.; Hopper, Thomas

1996-11-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the current status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

A neural net based architecture for the segmentation of mixed gray-level and binary pictures

NASA Technical Reports Server (NTRS)

Tabatabai, Ali; Troudet, Terry P.

1991-01-01

A neural-net-based architecture is proposed to perform segmentation in real time for mixed gray-level and binary pictures. In this approach, the composite picture is divided into 16 x 16 pixel blocks, which are identified as character blocks or image blocks on the basis of a dichotomy measure computed by an adaptive 16 x 16 neural net. For compression purposes, each image block is further divided into 4 x 4 subblocks; a one-bit nonparametric quantizer is used to encode 16 x 16 character and 4 x 4 image blocks; and the binary map and quantizer levels are obtained through a neural net segmentor over each block. The efficiency of the neural segmentation in terms of computational speed, data compression, and quality of the compressed picture is demonstrated. The effect of weight quantization is also discussed. VLSI implementations of such adaptive neural nets in CMOS technology are described and simulated in real time for a maximum block size of 256 pixels.

A CMOS Imager with Focal Plane Compression using Predictive Coding

NASA Technical Reports Server (NTRS)

Leon-Salas, Walter D.; Balkir, Sina; Sayood, Khalid; Schemm, Nathan; Hoffman, Michael W.

2007-01-01

This paper presents a CMOS image sensor with focal-plane compression. The design has a column-level architecture and it is based on predictive coding techniques for image decorrelation. The prediction operations are performed in the analog domain to avoid quantization noise and to decrease the area complexity of the circuit, The prediction residuals are quantized and encoded by a joint quantizer/coder circuit. To save area resources, the joint quantizerlcoder circuit exploits common circuitry between a single-slope analog-to-digital converter (ADC) and a Golomb-Rice entropy coder. This combination of ADC and encoder allows the integration of the entropy coder at the column level. A prototype chip was fabricated in a 0.35 pm CMOS process. The output of the chip is a compressed bit stream. The test chip occupies a silicon area of 2.60 mm x 5.96 mm which includes an 80 X 44 APS array. Tests of the fabricated chip demonstrate the validity of the design.

Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

2014-12-01

Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.

Passive forensics for copy-move image forgery using a method based on DCT and SVD.

PubMed

Zhao, Jie; Guo, Jichang

2013-12-10

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common post-processing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided non-overlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Digital Model of Fourier and Fresnel Quantized Holograms

NASA Astrophysics Data System (ADS)

Boriskevich, Anatoly A.; Erokhovets, Valery K.; Tkachenko, Vadim V.

Some models schemes of Fourier and Fresnel quantized protective holograms with visual effects are suggested. The condition to arrive at optimum relationship between the quality of reconstructed images, and the coefficient of data reduction about a hologram, and quantity of iterations in the reconstructing hologram process has been estimated through computer model. Higher protection level is achieved by means of greater number both bi-dimensional secret keys (more than 2128) in form of pseudorandom amplitude and phase encoding matrixes, and one-dimensional encoding key parameters for every image of single-layer or superimposed holograms.

Multipurpose image watermarking algorithm based on multistage vector quantization.

PubMed

Lu, Zhe-Ming; Xu, Dian-Guo; Sun, Sheng-He

2005-06-01

The rapid growth of digital multimedia and Internet technologies has made copyright protection, copy protection, and integrity verification three important issues in the digital world. To solve these problems, the digital watermarking technique has been presented and widely researched. Traditional watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform, discrete Fourier transform (DFT), and discrete wavelet transform (DWT). Most of these algorithms are good for only one purpose. Recently, some multipurpose digital watermarking methods have been presented, which can achieve the goal of content authentication and copyright protection simultaneously. However, they are based on DWT or DFT. Lately, several robust watermarking schemes based on vector quantization (VQ) have been presented, but they can only be used for copyright protection. In this paper, we present a novel multipurpose digital image watermarking method based on the multistage vector quantizer structure, which can be applied to image authentication and copyright protection. In the proposed method, the semi-fragile watermark and the robust watermark are embedded in different VQ stages using different techniques, and both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.

[Glossary of terms used by radiologists in image processing].

PubMed

Rolland, Y; Collorec, R; Bruno, A; Ramée, A; Morcet, N; Haigron, P

1995-01-01

We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.

Vector Quantization Algorithm Based on Associative Memories

NASA Astrophysics Data System (ADS)

Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo

This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Codestream-Based Identification of JPEG 2000 Images with Different Coding Parameters

NASA Astrophysics Data System (ADS)

Watanabe, Osamu; Fukuhara, Takahiro; Kiya, Hitoshi

A method of identifying JPEG 2000 images with different coding parameters, such as code-block sizes, quantization-step sizes, and resolution levels, is presented. It does not produce false-negative matches regardless of different coding parameters (compression rate, code-block size, and discrete wavelet transform (DWT) resolutions levels) or quantization step sizes. This feature is not provided by conventional methods. Moreover, the proposed approach is fast because it uses the number of zero-bit-planes that can be extracted from the JPEG 2000 codestream by only parsing the header information without embedded block coding with optimized truncation (EBCOT) decoding. The experimental results revealed the effectiveness of image identification based on the new method.

Low bit rate coding of Earth science images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1993-01-01

In this paper, the authors discuss compression based on some new ideas in vector quantization and their incorporation in a sub-band coding framework. Several variations are considered, which collectively address many of the individual compression needs within the earth science community. The approach taken in this work is based on some recent advances in the area of variable rate residual vector quantization (RVQ). This new RVQ method is considered separately and in conjunction with sub-band image decomposition. Very good results are achieved in coding a variety of earth science images. The last section of the paper provides some comparisons that illustrate the improvement in performance attributable to this approach relative the the JPEG coding standard.

New scheme for color confinement and violation of the non-Abelian Bianchi identities

NASA Astrophysics Data System (ADS)

Suzuki, Tsuneo; Ishiguro, Katsuya; Bornyakov, Vitaly

2018-02-01

A new scheme for color confinement in QCD due to violation of the non-Abelian Bianchi identities is proposed. The violation of the non-Abelian Bianchi identities (VNABI) Jμ is equal to Abelian-like monopole currents kμ defined by the violation of the Abelian-like Bianchi identities. Although VNABI is an adjoint operator satisfying the covariant conservation law DμJμ=0 , it satisfies, at the same time, the Abelian-like conservation law ∂μJμ=0 . The Abelian-like conservation law ∂μJμ=0 is also gauge-covariant. There are N2-1 conserved magnetic charges in the case of color S U (N ). The charge of each component of VNABI is quantized à la Dirac. The color-invariant eigenvalues λμ of VNABI also satisfy the Abelian conservation law ∂μλμ=0 and the magnetic charges of the eigenvalues are also quantized à la Dirac. If the color invariant eigenvalues condense in the QCD vacuum, each color component of the non-Abelian electric field Ea is squeezed by the corresponding color component of the solenoidal current Jμa. Then only the color singlets alone can survive as a physical state and non-Abelian color confinement is realized. This confinement picture is completely new in comparison with the previously studied monopole confinement scenario based on an Abelian projection after some partial gauge-fixing, where Abelian neutral states can survive as physical. To check if the scenario is realized in nature, numerical studies are done in the framework of lattice field theory by adopting pure S U (2 ) gauge theory for simplicity. Considering Jμ(x )=kμ(x ) in the continuum formulation, we adopt an Abelian-like definition of a monopole following DeGrand-Toussaint as a lattice version of VNABI, since the Dirac quantization condition of the magnetic charge is satisfied on lattice partially. To reduce severe lattice artifacts, we introduce various techniques of smoothing the thermalized vacuum. Smooth gauge fixings such as the maximal center gauge (MCG), block-spin transformations of Abelian-like monopoles and extraction of physically important infrared long monopole loops are adopted. We also employ the tree-level tadpole improved gauge action of S U (2 ) gluodynamics. With these various improvements, we measure the density of lattice VNABI: ρ (a (β ),n )=∑ μ ,sn √{∑ a (kμa(sn))2 }/(4 √{3 }Vnb3) , where kμa(sn) is an n blocked monopole in the color direction a , n is the number of blocking steps, Vn=V /n4 (b =n a (β )) is the lattice volume (spacing) of the blocked lattice. Beautiful and convincing scaling behaviors are seen when we plot the density ρ (a (β ),n ) versus b =n a (β ). A single universal curve ρ (b ) is found from n =1 to n =12 , which suggests that ρ (a (β ),n ) is a function of b =n a (β ) alone. The universal curve seems independent of a gauge fixing procedure used to smooth the lattice vacuum since the scaling is obtained in all gauges adopted. The scaling, if it exists also for n →∞ , shows that the lattice definition of VNABI has the continuum limit and the new confinement scenario is realized.

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

NASA Technical Reports Server (NTRS)

Jaggi, S.

1993-01-01

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Convolutional neural network-based classification system design with compressed wireless sensor network images.

PubMed

Ahn, Jungmo; Park, JaeYeon; Park, Donghwan; Paek, Jeongyeup; Ko, JeongGil

2018-01-01

With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.

Subband Image Coding with Jointly Optimized Quantizers

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith Mark J. T.

1995-01-01

An iterative design algorithm for the joint design of complexity- and entropy-constrained subband quantizers and associated entropy coders is proposed. Unlike conventional subband design algorithms, the proposed algorithm does not require the use of various bit allocation algorithms. Multistage residual quantizers are employed here because they provide greater control of the complexity-performance tradeoffs, and also because they allow efficient and effective high-order statistical modeling. The resulting subband coder exploits statistical dependencies within subbands, across subbands, and across stages, mainly through complexity-constrained high-order entropy coding. Experimental results demonstrate that the complexity-rate-distortion performance of the new subband coder is exceptional.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

A simplified Integer Cosine Transform and its application in image compression

NASA Technical Reports Server (NTRS)

Costa, M.; Tong, K.

1994-01-01

A simplified version of the integer cosine transform (ICT) is described. For practical reasons, the transform is considered jointly with the quantization of its coefficients. It differs from conventional ICT algorithms in that the combined factors for normalization and quantization are approximated by powers of two. In conventional algorithms, the normalization/quantization stage typically requires as many integer divisions as the number of transform coefficients. By restricting the factors to powers of two, these divisions can be performed by variable shifts in the binary representation of the coefficients, with speed and cost advantages to the hardware implementation of the algorithm. The error introduced by the factor approximations is compensated for in the inverse ICT operation, executed with floating point precision. The simplified ICT algorithm has potential applications in image-compression systems with disparate cost and speed requirements in the encoder and decoder ends. For example, in deep space image telemetry, the image processors on board the spacecraft could take advantage of the simplified, faster encoding operation, which would be adjusted on the ground, with high-precision arithmetic. A dual application is found in compressed video broadcasting. Here, a fast, high-performance processor at the transmitter would precompensate for the factor approximations in the inverse ICT operation, to be performed in real time, at a large number of low-cost receivers.

Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

NASA Astrophysics Data System (ADS)

Daly, Scott J.

1989-08-01

The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

A multistage framework for dismount spectral verification in the VNIR

NASA Astrophysics Data System (ADS)

Rosario, Dalton

2013-05-01

A multistage algorithm suite is proposed for a specific target detection/verification scenario, where a visible/near infrared hyperspectral (HS) sample is assumed to be available as the only cue from a reference image frame. The target is a suspicious dismount. The suite first applies a biometric based human skin detector to focus the attention of the search. Using as reference all of the bands in the spectral cue, the suite follows with a Bayesian Lasso inference stage designed to isolate pixels representing the specific material type cued by the user and worn by the human target (e.g., hat, jacket). In essence, the search focuses on testing material types near skin pixels. The third stage imposes an additional constraint through RGB color quantization and distance metric checking, limiting even further the search for material types in the scene having visible color similar to the target visible color. Using the proposed cumulative evidence strategy produced some encouraging range-invariant results on real HS imagery, dramatically reducing to zero the false alarm rate on the example dataset. These results were in contrast to the results independently produced by each one of the suite's stages, as the spatial areas of each stage's high false alarm outcome were mutually exclusive in the imagery. These conclusions also apply to results produced by other standard methods, in particular the kernel SVDD (support vector data description) and matched filter, as shown in the paper.

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Digital Signal Processing For Low Bit Rate TV Image Codecs

NASA Astrophysics Data System (ADS)

Rao, K. R.

1987-06-01

In view of the 56 KBPS digital switched network services and the ISDN, low bit rate codecs for providing real time full motion color video are under various stages of development. Some companies have already brought the codecs into the market. They are being used by industry and some Federal Agencies for video teleconferencing. In general, these codecs have various features such as multiplexing audio and data, high resolution graphics, encryption, error detection and correction, self diagnostics, freezeframe, split video, text overlay etc. To transmit the original color video on a 56 KBPS network requires bit rate reduction of the order of 1400:1. Such a large scale bandwidth compression can be realized only by implementing a number of sophisticated,digital signal processing techniques. This paper provides an overview of such techniques and outlines the newer concepts that are being investigated. Before resorting to the data compression techniques, various preprocessing operations such as noise filtering, composite-component transformation and horizontal and vertical blanking interval removal are to be implemented. Invariably spatio-temporal subsampling is achieved by appropriate filtering. Transform and/or prediction coupled with motion estimation and strengthened by adaptive features are some of the tools in the arsenal of the data reduction methods. Other essential blocks in the system are quantizer, bit allocation, buffer, multiplexer, channel coding etc.

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.

1994-01-01

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

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

Markov Random Fields, Stochastic Quantization and Image Analysis

DTIC Science & Technology

1990-01-01

Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as a-priori models for the...of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis , Statistical Mechanics and Lattice-based Euclidean Quantum Field Theory.

Perceptual Image Compression in Telemedicine

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ahumada, Albert J., Jr.; Eckstein, Miguel; Null, Cynthia H. (Technical Monitor)

1996-01-01

The next era of space exploration, especially the "Mission to Planet Earth" will generate immense quantities of image data. For example, the Earth Observing System (EOS) is expected to generate in excess of one terabyte/day. NASA confronts a major technical challenge in managing this great flow of imagery: in collection, pre-processing, transmission to earth, archiving, and distribution to scientists at remote locations. Expected requirements in most of these areas clearly exceed current technology. Part of the solution to this problem lies in efficient image compression techniques. For much of this imagery, the ultimate consumer is the human eye. In this case image compression should be designed to match the visual capacities of the human observer. We have developed three techniques for optimizing image compression for the human viewer. The first consists of a formula, developed jointly with IBM and based on psychophysical measurements, that computes a DCT quantization matrix for any specified combination of viewing distance, display resolution, and display brightness. This DCT quantization matrix is used in most recent standards for digital image compression (JPEG, MPEG, CCITT H.261). The second technique optimizes the DCT quantization matrix for each individual image, based on the contents of the image. This is accomplished by means of a model of visual sensitivity to compression artifacts. The third technique extends the first two techniques to the realm of wavelet compression. Together these two techniques will allow systematic perceptual optimization of image compression in NASA imaging systems. Many of the image management challenges faced by NASA are mirrored in the field of telemedicine. Here too there are severe demands for transmission and archiving of large image databases, and the imagery is ultimately used primarily by human observers, such as radiologists. In this presentation I will describe some of our preliminary explorations of the applications of our technology to the special problems of telemedicine.

Characteristic extraction and matching algorithms of ballistic missile in near-space by hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Liu, Shihua; Zhang, Xianzhi

2014-10-01

The ballistic missile hyperspectral data of imaging spectrometer from the near-space platform are generated by numerical method. The characteristic of the ballistic missile hyperspectral data is extracted and matched based on two different kinds of algorithms, which called transverse counting and quantization coding, respectively. The simulation results show that two algorithms extract the characteristic of ballistic missile adequately and accurately. The algorithm based on the transverse counting has the low complexity and can be implemented easily compared to the algorithm based on the quantization coding does. The transverse counting algorithm also shows the good immunity to the disturbance signals and speed up the matching and recognition of subsequent targets.

Studies on image compression and image reconstruction

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Nori, Sekhar; Araj, A.

1994-01-01

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Fabrication and characterization of a co-planar detector in diamond for low energy single ion implantation

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

Abraham, John Bishoy Sam; Pacheco, Jose L.; Aguirre, Brandon Adrian

2016-08-09

We demonstrate low energy single ion detection using a co-planar detector fabricated on a diamond substrate and characterized by ion beam induced charge collection. Histograms are taken with low fluence ion pulses illustrating quantized ion detection down to a single ion with a signal-to-noise ratio of approximately 10. We anticipate that this detection technique can serve as a basis to optimize the yield of single color centers in diamond. In conclusion, the ability to count ions into a diamond substrate is expected to reduce the uncertainty in the yield of color center formation by removing Poisson statistics from the implantationmore » process.« less

An analog gamma correction scheme for high dynamic range CMOS logarithmic image sensors.

PubMed

Cao, Yuan; Pan, Xiaofang; Zhao, Xiaojin; Wu, Huisi

2014-12-15

In this paper, a novel analog gamma correction scheme with a logarithmic image sensor dedicated to minimize the quantization noise of the high dynamic applications is presented. The proposed implementation exploits a non-linear voltage-controlled-oscillator (VCO) based analog-to-digital converter (ADC) to perform the gamma correction during the analog-to-digital conversion. As a result, the quantization noise does not increase while the same high dynamic range of logarithmic image sensor is preserved. Moreover, by combining the gamma correction with the analog-to-digital conversion, the silicon area and overall power consumption can be greatly reduced. The proposed gamma correction scheme is validated by the reported simulation results and the experimental results measured for our designed test structure, which is fabricated with 0.35 μm standard complementary-metal-oxide-semiconductor (CMOS) process.

An Analog Gamma Correction Scheme for High Dynamic Range CMOS Logarithmic Image Sensors

PubMed Central

Cao, Yuan; Pan, Xiaofang; Zhao, Xiaojin; Wu, Huisi

2014-01-01

In this paper, a novel analog gamma correction scheme with a logarithmic image sensor dedicated to minimize the quantization noise of the high dynamic applications is presented. The proposed implementation exploits a non-linear voltage-controlled-oscillator (VCO) based analog-to-digital converter (ADC) to perform the gamma correction during the analog-to-digital conversion. As a result, the quantization noise does not increase while the same high dynamic range of logarithmic image sensor is preserved. Moreover, by combining the gamma correction with the analog-to-digital conversion, the silicon area and overall power consumption can be greatly reduced. The proposed gamma correction scheme is validated by the reported simulation results and the experimental results measured for our designed test structure, which is fabricated with 0.35 μm standard complementary-metal-oxide-semiconductor (CMOS) process. PMID:25517692

Learning binary code via PCA of angle projection for image retrieval

NASA Astrophysics Data System (ADS)

Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

2018-01-01

With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

Optimal block cosine transform image coding for noisy channels

NASA Technical Reports Server (NTRS)

Vaishampayan, V.; Farvardin, N.

1986-01-01

The two dimensional block transform coding scheme based on the discrete cosine transform was studied extensively for image coding applications. While this scheme has proven to be efficient in the absence of channel errors, its performance degrades rapidly over noisy channels. A method is presented for the joint source channel coding optimization of a scheme based on the 2-D block cosine transform when the output of the encoder is to be transmitted via a memoryless design of the quantizers used for encoding the transform coefficients. This algorithm produces a set of locally optimum quantizers and the corresponding binary code assignment for the assumed transform coefficient statistics. To determine the optimum bit assignment among the transform coefficients, an algorithm was used based on the steepest descent method, which under certain convexity conditions on the performance of the channel optimized quantizers, yields the optimal bit allocation. Comprehensive simulation results for the performance of this locally optimum system over noisy channels were obtained and appropriate comparisons against a reference system designed for no channel error were rendered.

Real-time demonstration hardware for enhanced DPCM video compression algorithm

NASA Technical Reports Server (NTRS)

Bizon, Thomas P.; Whyte, Wayne A., Jr.; Marcopoli, Vincent R.

1992-01-01

The lack of available wideband digital links as well as the complexity of implementation of bandwidth efficient digital video CODECs (encoder/decoder) has worked to keep the cost of digital television transmission too high to compete with analog methods. Terrestrial and satellite video service providers, however, are now recognizing the potential gains that digital video compression offers and are proposing to incorporate compression systems to increase the number of available program channels. NASA is similarly recognizing the benefits of and trend toward digital video compression techniques for transmission of high quality video from space and therefore, has developed a digital television bandwidth compression algorithm to process standard National Television Systems Committee (NTSC) composite color television signals. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a non-adaptive predictor, non-uniform quantizer and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The non-adaptive predictor and multilevel Huffman coder combine to set this technique apart from other DPCM encoding algorithms. All processing is done on a intra-field basis to prevent motion degradation and minimize hardware complexity. Computer simulations have shown the algorithm will produce broadcast quality reconstructed video at an average transmission rate of 1.8 bits/pixel. Hardware implementation of the DPCM circuit, non-adaptive predictor and non-uniform quantizer has been completed, providing realtime demonstration of the image quality at full video rates. Video sampling/reconstruction circuits have also been constructed to accomplish the analog video processing necessary for the real-time demonstration. Performance results for the completed hardware compare favorably with simulation results. Hardware implementation of the multilevel Huffman encoder/decoder is currently under development along with implementation of a buffer control algorithm to accommodate the variable data rate output of the multilevel Huffman encoder. A video CODEC of this type could be used to compress NTSC color television signals where high quality reconstruction is desirable (e.g., Space Station video transmission, transmission direct-to-the-home via direct broadcast satellite systems or cable television distribution to system headends and direct-to-the-home).

Comparing features sets for content-based image retrieval in a medical-case database

NASA Astrophysics Data System (ADS)

Muller, Henning; Rosset, Antoine; Vallee, Jean-Paul; Geissbuhler, Antoine

2004-04-01

Content-based image retrieval systems (CBIRSs) have frequently been proposed for the use in medical image databases and PACS. Still, only few systems were developed and used in a real clinical environment. It rather seems that medical professionals define their needs and computer scientists develop systems based on data sets they receive with little or no interaction between the two groups. A first study on the diagnostic use of medical image retrieval also shows an improvement in diagnostics when using CBIRSs which underlines the potential importance of this technique. This article explains the use of an open source image retrieval system (GIFT - GNU Image Finding Tool) for the retrieval of medical images in the medical case database system CasImage that is used in daily, clinical routine in the university hospitals of Geneva. Although the base system of GIFT shows an unsatisfactory performance, already little changes in the feature space show to significantly improve the retrieval results. The performance of variations in feature space with respect to color (gray level) quantizations and changes in texture analysis (Gabor filters) is compared. Whereas stock photography relies mainly on colors for retrieval, medical images need a large number of gray levels for successful retrieval, especially when executing feedback queries. The results also show that a too fine granularity in the gray levels lowers the retrieval quality, especially with single-image queries. For the evaluation of the retrieval peformance, a subset of the entire case database of more than 40,000 images is taken with a total of 3752 images. Ground truth was generated by a user who defined the expected query result of a perfect system by selecting images relevant to a given query image. The results show that a smaller number of gray levels (32 - 64) leads to a better retrieval performance, especially when using relevance feedback. The use of more scales and directions for the Gabor filters in the texture analysis also leads to improved results but response time is going up equally due to the larger feature space. CBIRSs can be of great use in managing large medical image databases. They allow to find images that might otherwise be lost for research and publications. They also give students students the possibility to navigate within large image repositories. In the future, CBIR might also become more important in case-based reasoning and evidence-based medicine to support the diagnostics because first studies show good results.

Statistical characterization of speckle noise in coherent imaging systems

NASA Astrophysics Data System (ADS)

Yaroslavsky, Leonid; Shefler, A.

2003-05-01

Speckle noise imposes fundamental limitation on image quality in coherent radiation based imaging and optical metrology systems. Speckle noise phenomena are associated with properties of objects to diffusely scatter irradiation and with the fact that in recording the wave field, a number of signal distortions inevitably occur due to technical limitations inherent to hologram sensors. The statistical theory of speckle noise was developed with regard to only limited resolving power of coherent imaging devices. It is valid only asymptotically as much as the central limit theorem of the probability theory can be applied. In applications this assumption is not always applicable. Moreover, in treating speckle noise problem one should also consider other sources of the hologram deterioration. In the paper, statistical properties of speckle due to the limitation of hologram size, dynamic range and hologram signal quantization are studied by Monte-Carlo simulation for holograms recorded in near and far diffraction zones. The simulation experiments have shown that, for limited resolving power of the imaging system, widely accepted opinion that speckle contrast is equal to one holds only for rather severe level of the hologram size limitation. For moderate limitations, speckle contrast changes gradually from zero for no limitation to one for limitation to less than about 20% of hologram size. The results obtained for the limitation of the hologram sensor"s dynamic range and hologram signal quantization reveal that speckle noise due to these hologram signal distortions is not multiplicative and is directly associated with the severity of the limitation and quantization. On the base of the simulation results, analytical models are suggested.

A joint source-channel distortion model for JPEG compressed images.

PubMed

Sabir, Muhammad F; Sheikh, Hamid Rahim; Heath, Robert W; Bovik, Alan C

2006-06-01

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.

On the relationships between higher and lower bit-depth system measurements

NASA Astrophysics Data System (ADS)

Burks, Stephen D.; Haefner, David P.; Doe, Joshua M.

2018-04-01

The quality of an imaging system can be assessed through controlled laboratory objective measurements. Currently, all imaging measurements require some form of digitization in order to evaluate a metric. Depending on the device, the amount of bits available, relative to a fixed dynamic range, will exhibit quantization artifacts. From a measurement standpoint, measurements are desired to be performed at the highest possible bit-depth available. In this correspondence, we described the relationship between higher and lower bit-depth measurements. The limits to which quantization alters the observed measurements will be presented. Specifically, we address dynamic range, MTF, SiTF, and noise. Our results provide guidelines to how systems of lower bit-depth should be characterized and the corresponding experimental methods.

Image coding using entropy-constrained residual vector quantization

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Barnes, Christopher F.

1993-01-01

The residual vector quantization (RVQ) structure is exploited to produce a variable length codeword RVQ. Necessary conditions for the optimality of this RVQ are presented, and a new entropy-constrained RVQ (ECRVQ) design algorithm is shown to be very effective in designing RVQ codebooks over a wide range of bit rates and vector sizes. The new EC-RVQ has several important advantages. It can outperform entropy-constrained VQ (ECVQ) in terms of peak signal-to-noise ratio (PSNR), memory, and computation requirements. It can also be used to design high rate codebooks and codebooks with relatively large vector sizes. Experimental results indicate that when the new EC-RVQ is applied to image coding, very high quality is achieved at relatively low bit rates.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

Adaptive time-sequential binary sensing for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Hu, Chenhui; Lu, Yue M.

2012-06-01

We present a novel image sensor for high dynamic range imaging. The sensor performs an adaptive one-bit quantization at each pixel, with the pixel output switched from 0 to 1 only if the number of photons reaching that pixel is greater than or equal to a quantization threshold. With an oracle knowledge of the incident light intensity, one can pick an optimal threshold (for that light intensity) and the corresponding Fisher information contained in the output sequence follows closely that of an ideal unquantized sensor over a wide range of intensity values. This observation suggests the potential gains one may achieve by adaptively updating the quantization thresholds. As the main contribution of this work, we propose a time-sequential threshold-updating rule that asymptotically approaches the performance of the oracle scheme. With every threshold mapped to a number of ordered states, the dynamics of the proposed scheme can be modeled as a parametric Markov chain. We show that the frequencies of different thresholds converge to a steady-state distribution that is concentrated around the optimal choice. Moreover, numerical experiments show that the theoretical performance measures (Fisher information and Craḿer-Rao bounds) can be achieved by a maximum likelihood estimator, which is guaranteed to find globally optimal solution due to the concavity of the log-likelihood functions. Compared with conventional image sensors and the strategy that utilizes a constant single-photon threshold considered in previous work, the proposed scheme attains orders of magnitude improvement in terms of sensor dynamic ranges.

Study of communications data compression methods

NASA Technical Reports Server (NTRS)

Jones, H. W.

1978-01-01

A simple monochrome conditional replenishment system was extended to higher compression and to higher motion levels, by incorporating spatially adaptive quantizers and field repeating. Conditional replenishment combines intraframe and interframe compression, and both areas are investigated. The gain of conditional replenishment depends on the fraction of the image changing, since only changed parts of the image need to be transmitted. If the transmission rate is set so that only one fourth of the image can be transmitted in each field, greater change fractions will overload the system. A computer simulation was prepared which incorporated (1) field repeat of changes, (2) a variable change threshold, (3) frame repeat for high change, and (4) two mode, variable rate Hadamard intraframe quantizers. The field repeat gives 2:1 compression in moving areas without noticeable degradation. Variable change threshold allows some flexibility in dealing with varying change rates, but the threshold variation must be limited for acceptable performance.

Steganalysis based on JPEG compatibility

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav; Du, Rui

2001-11-01

In this paper, we introduce a new forensic tool that can reliably detect modifications in digital images, such as distortion due to steganography and watermarking, in images that were originally stored in the JPEG format. The JPEG compression leave unique fingerprints and serves as a fragile watermark enabling us to detect changes as small as modifying the LSB of one randomly chosen pixel. The detection of changes is based on investigating the compatibility of 8x8 blocks of pixels with JPEG compression with a given quantization matrix. The proposed steganalytic method is applicable to virtually all steganongraphic and watermarking algorithms with the exception of those that embed message bits into the quantized JPEG DCT coefficients. The method can also be used to estimate the size of the secret message and identify the pixels that carry message bits. As a consequence of our steganalysis, we strongly recommend avoiding using images that have been originally stored in the JPEG format as cover-images for spatial-domain steganography.

Automatic and quantitative measurement of laryngeal video stroboscopic images.

PubMed

Kuo, Chung-Feng Jeffrey; Kuo, Joseph; Hsiao, Shang-Wun; Lee, Chi-Lung; Lee, Jih-Chin; Ke, Bo-Han

2017-01-01

The laryngeal video stroboscope is an important instrument for physicians to analyze abnormalities and diseases in the glottal area. Stroboscope has been widely used around the world. However, without quantized indices, physicians can only make subjective judgment on glottal images. We designed a new laser projection marking module and applied it onto the laryngeal video stroboscope to provide scale conversion reference parameters for glottal imaging and to convert the physiological parameters of glottis. Image processing technology was used to segment the important image regions of interest. Information of the glottis was quantified, and the vocal fold image segmentation system was completed to assist clinical diagnosis and increase accuracy. Regarding image processing, histogram equalization was used to enhance glottis image contrast. The center weighted median filters image noise while retaining the texture of the glottal image. Statistical threshold determination was used for automatic segmentation of a glottal image. As the glottis image contains saliva and light spots, which are classified as the noise of the image, noise was eliminated by erosion, expansion, disconnection, and closure techniques to highlight the vocal area. We also used image processing to automatically identify an image of vocal fold region in order to quantify information from the glottal image, such as glottal area, vocal fold perimeter, vocal fold length, glottal width, and vocal fold angle. The quantized glottis image database was created to assist physicians in diagnosing glottis diseases more objectively.

Optimal Compression Methods for Floating-point Format Images

NASA Technical Reports Server (NTRS)

Pence, W. D.; White, R. L.; Seaman, R.

2009-01-01

We report on the results of a comparison study of different techniques for compressing FITS images that have floating-point (real*4) pixel values. Standard file compression methods like GZIP are generally ineffective in this case (with compression ratios only in the range 1.2 - 1.6), so instead we use a technique of converting the floating-point values into quantized scaled integers which are compressed using the Rice algorithm. The compressed data stream is stored in FITS format using the tiled-image compression convention. This is technically a lossy compression method, since the pixel values are not exactly reproduced, however all the significant photometric and astrometric information content of the image can be preserved while still achieving file compression ratios in the range of 4 to 8. We also show that introducing dithering, or randomization, when assigning the quantized pixel-values can significantly improve the photometric and astrometric precision in the stellar images in the compressed file without adding additional noise. We quantify our results by comparing the stellar magnitudes and positions as measured in the original uncompressed image to those derived from the same image after applying successively greater amounts of compression.

Semiclassical Models for Virtual Antiparticle Pairs, the Unit of Charge e, and the QCD Coupling alpha(sub s)

NASA Technical Reports Server (NTRS)

Batchelor, David; Zukor, Dorothy (Technical Monitor)

2001-01-01

New semiclassical models of virtual antiparticle pairs are used to compute the pair lifetimes, and good agreement with the Heisenberg lifetimes from quantum field theory (QFT) is found. The modeling method applies to both the electromagnetic and color forces. Evaluation of the action integral of potential field fluctuation for each interaction potential yields approximately Planck's constant/2 for both electromagnetic and color fluctuations, in agreement with QFT. Thus each model is a quantized semiclassical representation for such virtual antiparticle pairs, to good approximation. When the results of the new models and QFT are combined, formulae for e and alpha(sub s)(q) are derived in terms of only Planck's constant and c.

An IBM-compatible program for interactive three-dimensional gravity modeling

NASA Astrophysics Data System (ADS)

Broome, John

1992-04-01

G3D is a 3-D interactive gravity modeling program for IBM-compatible microcomputers. The program allows a model to be created interactively by defining multiple tabular bodies with horizontal tops and bottoms. The resulting anomaly is calculated using Plouff's algorithm at up to 2000 predefined random or regularly located points. In order to display the anomaly as a color image, the point data are interpolated onto a regular grid and quantized into discrete intervals. Observed and residual gravity field images also can be generated. Adjustments to the model are made using a graphics cursor to move, insert, and delete body points or whole bodies. To facilitate model changes, planview body outlines can be overlain on any of the gravity field images during editing. The model's geometry can be displayed in planview or along a user-defined vertical section. G3D is written in Microsoft® FORTRAN and utilizes the Halo-Professional® (or Halo-88®) graphics subroutine library. The program is written for use on an IBM-compatible microcomputer equipped with hard disk, numeric coprocessor, and VGA, Number Nine Revolution (Halo-88® only), or TIGA® compatible graphics cards. A mouse or digitizing tablet is recommended for cursor positioning. Program source code, a user's guide, and sample data are available as Geological Survey of Canada Open File (G3D: A Three-dimensional Gravity Modeling Program for IBM-compatible Microcomputers).

Genetic Algorithms Evolve Optimized Transforms for Signal Processing Applications

DTIC Science & Technology

2005-04-01

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

Vector coding of wavelet-transformed images

NASA Astrophysics Data System (ADS)

Zhou, Jun; Zhi, Cheng; Zhou, Yuanhua

1998-09-01

Wavelet, as a brand new tool in signal processing, has got broad recognition. Using wavelet transform, we can get octave divided frequency band with specific orientation which combines well with the properties of Human Visual System. In this paper, we discuss the classified vector quantization method for multiresolution represented image.

Visualization of JPEG Metadata

NASA Astrophysics Data System (ADS)

Malik Mohamad, Kamaruddin; Deris, Mustafa Mat

There are a lot of information embedded in JPEG image than just graphics. Visualization of its metadata would benefit digital forensic investigator to view embedded data including corrupted image where no graphics can be displayed in order to assist in evidence collection for cases such as child pornography or steganography. There are already available tools such as metadata readers, editors and extraction tools but mostly focusing on visualizing attribute information of JPEG Exif. However, none have been done to visualize metadata by consolidating markers summary, header structure, Huffman table and quantization table in a single program. In this paper, metadata visualization is done by developing a program that able to summarize all existing markers, header structure, Huffman table and quantization table in JPEG. The result shows that visualization of metadata helps viewing the hidden information within JPEG more easily.

Comparison of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Earth Observing One (EO-1) Advanced Land Imager

NASA Technical Reports Server (NTRS)

Pedelty, Jeffrey A.; Morisette, Jeffrey T.; Smith, James A.

2004-01-01

We compare images from the Enhanced Thematic Mapper Plus (ETM+) sensor on Landsat-7 and the Advanced Land Imager (ALI) instrument on Earth Observing One (EO-1) over a test site in Rochester, New York. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, and grass fields, to urban areas. Nearly coincident cloud-free images were collected one minute apart on 25 August 2001. We also compare images of a forest site near Howland, Maine, that were collected on 7 September, 2001. We atmospherically corrected each pair of images with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmosphere model, using aerosol optical thickness and water vapor column density measured by in situ Cimel sun photometers within the Aerosol Robotic Network (AERONET), along with ozone density derived from the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. We present true-color composites from each instrument that show excellent qualitative agreement between the multispectral sensors, along with grey-scale images that demonstrate a significantly improved ALI panchromatic band. We quantitatively compare ALI and ETM+ reflectance spectra of a grassy field in Rochester and find < or equal to 6% differences in the visible/near infrared and approx. 2% differences in the short wave infrared. Spectral comparisons of forest sites in Rochester and Howland yield similar percentage agreement except for band 1, which has very low reflectance. Principal component analyses and comparison of normalized difference vegetation index histograms for each sensor indicate that the ALI is able to reproduce the information content in the ETM+ but with superior signal-to-noise performance due to its increased 12-bit quantization.

A constrained joint source/channel coder design and vector quantization of nonstationary sources

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Chen, Y. C.; Nori, S.; Araj, A.

1993-01-01

The emergence of broadband ISDN as the network for the future brings with it the promise of integration of all proposed services in a flexible environment. In order to achieve this flexibility, asynchronous transfer mode (ATM) has been proposed as the transfer technique. During this period a study was conducted on the bridging of network transmission performance and video coding. The successful transmission of variable bit rate video over ATM networks relies on the interaction between the video coding algorithm and the ATM networks. Two aspects of networks that determine the efficiency of video transmission are the resource allocation algorithm and the congestion control algorithm. These are explained in this report. Vector quantization (VQ) is one of the more popular compression techniques to appear in the last twenty years. Numerous compression techniques, which incorporate VQ, have been proposed. While the LBG VQ provides excellent compression, there are also several drawbacks to the use of the LBG quantizers including search complexity and memory requirements, and a mismatch between the codebook and the inputs. The latter mainly stems from the fact that the VQ is generally designed for a specific rate and a specific class of inputs. In this work, an adaptive technique is proposed for vector quantization of images and video sequences. This technique is an extension of the recursively indexed scalar quantization (RISQ) algorithm.

Real-Time Adaptive Color Segmentation by Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2004-01-01

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Choice of word length in the design of a specialized hardware for lossless wavelet compression of medical images

NASA Astrophysics Data System (ADS)

Urriza, Isidro; Barragan, Luis A.; Artigas, Jose I.; Garcia, Jose I.; Navarro, Denis

1997-11-01

Image compression plays an important role in the archiving and transmission of medical images. Discrete cosine transform (DCT)-based compression methods are not suitable for medical images because of block-like image artifacts that could mask or be mistaken for pathology. Wavelet transforms (WTs) are used to overcome this problem. When implementing WTs in hardware, finite precision arithmetic introduces quantization errors. However, lossless compression is usually required in the medical image field. Thus, the hardware designer must look for the optimum register length that, while ensuring the lossless accuracy criteria, will also lead to a high-speed implementation with small chip area. In addition, wavelet choice is a critical issue that affects image quality as well as system design. We analyze the filters best suited to image compression that appear in the literature. For them, we obtain the maximum quantization errors produced in the calculation of the WT components. Thus, we deduce the minimum word length required for the reconstructed image to be numerically identical to the original image. The theoretical results are compared with experimental results obtained from algorithm simulations on random test images. These results enable us to compare the hardware implementation cost of the different filter banks. Moreover, to reduce the word length, we have analyzed the case of increasing the integer part of the numbers while maintaining constant the word length when the scale increases.

Near-Infrared Coloring via a Contrast-Preserving Mapping Model.

PubMed

Chang-Hwan Son; Xiao-Ping Zhang

2017-11-01

Near-infrared gray images captured along with corresponding visible color images have recently proven useful for image restoration and classification. This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model. A naive coloring method directly adds the colors from the visible color image to the near-infrared gray image. However, this method results in an unrealistic image because of the discrepancies in the brightness and image structure between the captured near-infrared gray image and the visible color image. To solve the discrepancy problem, first, we present a new contrast-preserving mapping model to create a new near-infrared gray image with a similar appearance in the luminance plane to the visible color image, while preserving the contrast and details of the captured near-infrared gray image. Then, we develop a method to derive realistic colors that can be added to the newly created near-infrared gray image based on the proposed contrast-preserving mapping model. Experimental results show that the proposed new method not only preserves the local contrast and details of the captured near-infrared gray image, but also transfers the realistic colors from the visible color image to the newly created near-infrared gray image. It is also shown that the proposed near-infrared coloring can be used effectively for noise and haze removal, as well as local contrast enhancement.

Parametric binary dissection

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.; Crockett, Thomas W.; Nicol, David M.

1993-01-01

Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.

A novel method for characterizing harmful algal blooms in the Persian Gulf using MODIS measurements

NASA Astrophysics Data System (ADS)

Ghanea, Mohsen; Moradi, Masoud; Kabiri, Keivan

2016-10-01

Biophysical properties of water undergo meaningful variations under red tide (RT) outbreak. A massive Cochlodinium polykrikoids RT began in the eastern Persian Gulf (PG) in October 2008 and extended to the northern PG in December 2008. It killed large fish and hampered marine industries and water desalination appliances. Yet monthly averages of satellite-derived Chl-a (Chlorophyll-a), nFLH (normalized Fluorescence Line Height), and Kd490 (diffuse attenuation coefficient at 490 nm) have not been compared in the PG. MODIS (MODerate Resolution Imaging Spectroradiometer) sensor provides global coverage, with short revisit time, and accessible, well validated ocean color products. This study compares the behavior of MODIS Chl-a, nFLH, and Kd490 in both normal and RT conditions. In doing so, their color maps are shown during normal and RT periods. Then, monthly variations of these products are shown as time-series between 2002 and 2008. HOCI (Hybrid Ocean Color Index) is defined by integrating these products to detect RT affected areas. The results gained from 100 locations in the PG show that HOCI >0.18 mW cm-2 μm-1 sr-1 mg m-4 and nFLH >0.04 mW cm-2 μm-1 sr-1 discriminates non-bloom waters from algal blooms. Rrs(443)/Rrs(412) > 1 is a proper statement to separate Trichodesmium erythtraeum from Noctiluca millaris, Noctiluca scintillans, and diatoms. Rrs(667)/Rrs(443) > 1 can differentiate Cochlodinium polykrikoids from T. erythtraeum, N. millaris, N. scintillans, and diatoms as well. So, the combination of HOCI and Rrs(667)/Rrs(443) ratio is useful for detection and quantization of C. polykrikoids.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

PubMed

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Scalets, wavelets and (complex) turning point quantization

NASA Astrophysics Data System (ADS)

Handy, C. R.; Brooks, H. A.

2001-05-01

Despite the many successes of wavelet analysis in image and signal processing, the incorporation of continuous wavelet transform theory within quantum mechanics has lacked a compelling, first principles, motivating analytical framework, until now. For arbitrary one-dimensional rational fraction Hamiltonians, we develop a simple, unified formalism, which clearly underscores the complementary, and mutually interdependent, role played by moment quantization theory (i.e. via scalets, as defined herein) and wavelets. This analysis involves no approximation of the Hamiltonian within the (equivalent) wavelet space, and emphasizes the importance of (complex) multiple turning point contributions in the quantization process. We apply the method to three illustrative examples. These include the (double-well) quartic anharmonic oscillator potential problem, V(x) = Z2x2 + gx4, the quartic potential, V(x) = x4, and the very interesting and significant non-Hermitian potential V(x) = -(ix)3, recently studied by Bender and Boettcher.

Displaying radiologic images on personal computers: image storage and compression--Part 2.

PubMed

Gillespy, T; Rowberg, A H

1994-02-01

This is part 2 of our article on image storage and compression, the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Image compression is classified as lossless (nondestructive) or lossy (destructive). Common lossless compression algorithms include variable-length bit codes (Huffman codes and variants), dictionary-based compression (Lempel-Ziv variants), and arithmetic coding. Huffman codes and the Lempel-Ziv-Welch (LZW) algorithm are commonly used for image compression. All of these compression methods are enhanced if the image has been transformed into a differential image based on a differential pulse-code modulation (DPCM) algorithm. The LZW compression after the DPCM image transformation performed the best on our example images, and performed almost as well as the best of the three commercial compression programs tested. Lossy compression techniques are capable of much higher data compression, but reduced image quality and compression artifacts may be noticeable. Lossy compression is comprised of three steps: transformation, quantization, and coding. Two commonly used transformation methods are the discrete cosine transformation and discrete wavelet transformation. In both methods, most of the image information is contained in a relatively few of the transformation coefficients. The quantization step reduces many of the lower order coefficients to 0, which greatly improves the efficiency of the coding (compression) step. In fractal-based image compression, image patterns are stored as equations that can be reconstructed at different levels of resolution.

Introduction to Color Imaging Science

NASA Astrophysics Data System (ADS)

Lee, Hsien-Che

2005-04-01

Color imaging technology has become almost ubiquitous in modern life in the form of monitors, liquid crystal screens, color printers, scanners, and digital cameras. This book is a comprehensive guide to the scientific and engineering principles of color imaging. It covers the physics of light and color, how the eye and physical devices capture color images, how color is measured and calibrated, and how images are processed. It stresses physical principles and includes a wealth of real-world examples. The book will be of value to scientists and engineers in the color imaging industry and, with homework problems, can also be used as a text for graduate courses on color imaging.

A fast and efficient segmentation scheme for cell microscopic image.

PubMed

Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

2007-04-27

Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

Wavelet-based image compression using shuffling and bit plane correlation

NASA Astrophysics Data System (ADS)

Kim, Seungjong; Jeong, Jechang

2000-12-01

In this paper, we propose a wavelet-based image compression method using shuffling and bit plane correlation. The proposed method improves coding performance in two steps: (1) removing the sign bit plane by shuffling process on quantized coefficients, (2) choosing the arithmetic coding context according to maximum correlation direction. The experimental results are comparable or superior for some images with low correlation, to existing coders.

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

PubMed

Zaghetto, Alexandre; de Queiroz, Ricardo L

2007-07-01

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

Pseudo color ghost coding imaging with pseudo thermal light

NASA Astrophysics Data System (ADS)

Duan, De-yang; Xia, Yun-jie

2018-04-01

We present a new pseudo color imaging scheme named pseudo color ghost coding imaging based on ghost imaging but with multiwavelength source modulated by a spatial light modulator. Compared with conventional pseudo color imaging where there is no nondegenerate wavelength spatial correlations resulting in extra monochromatic images, the degenerate wavelength and nondegenerate wavelength spatial correlations between the idle beam and signal beam can be obtained simultaneously. This scheme can obtain more colorful image with higher quality than that in conventional pseudo color coding techniques. More importantly, a significant advantage of the scheme compared to the conventional pseudo color coding imaging techniques is the image with different colors can be obtained without changing the light source and spatial filter.

Design and evaluation of sparse quantization index modulation watermarking schemes

NASA Astrophysics Data System (ADS)

Cornelis, Bruno; Barbarien, Joeri; Dooms, Ann; Munteanu, Adrian; Cornelis, Jan; Schelkens, Peter

2008-08-01

In the past decade the use of digital data has increased significantly. The advantages of digital data are, amongst others, easy editing, fast, cheap and cross-platform distribution and compact storage. The most crucial disadvantages are the unauthorized copying and copyright issues, by which authors and license holders can suffer considerable financial losses. Many inexpensive methods are readily available for editing digital data and, unlike analog information, the reproduction in the digital case is simple and robust. Hence, there is great interest in developing technology that helps to protect the integrity of a digital work and the copyrights of its owners. Watermarking, which is the embedding of a signal (known as the watermark) into the original digital data, is one method that has been proposed for the protection of digital media elements such as audio, video and images. In this article, we examine watermarking schemes for still images, based on selective quantization of the coefficients of a wavelet transformed image, i.e. sparse quantization-index modulation (QIM) watermarking. Different grouping schemes for the wavelet coefficients are evaluated and experimentally verified for robustness against several attacks. Wavelet tree-based grouping schemes yield a slightly improved performance over block-based grouping schemes. Additionally, the impact of the deployment of error correction codes on the most promising configurations is examined. The utilization of BCH-codes (Bose, Ray-Chaudhuri, Hocquenghem) results in an improved robustness as long as the capacity of the error codes is not exceeded (cliff-effect).

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

Chen, Li; He, Yu; Yap, Kim-Hui

2011-01-01

This paper proposes a new regularization scheme to address blind color image deconvolution. Color images generally have a significant correlation among the red, green, and blue channels. Conventional blind monochromatic deconvolution algorithms handle each color image channels independently, thereby ignoring the interchannel correlation present in the color images. In view of this, a unified regularization scheme for image is developed to recover edges of color images and reduce color artifacts. In addition, by using the color image properties, a spectral-based regularization operator is adopted to impose constraints on the blurs. Further, this paper proposes a reinforcement regularization framework that integrates a soft parametric learning term in addressing blind color image deconvolution. A blur modeling scheme is developed to evaluate the relevance of manifold parametric blur structures, and the information is integrated into the deconvolution scheme. An optimization procedure called alternating minimization is then employed to iteratively minimize the image- and blur-domain cost functions. Experimental results show that the method is able to achieve satisfactory restored color images under different blurring conditions.

Mutual friction in a cold color-flavor-locked superfluid and r-mode instabilities in compact stars.

PubMed

Mannarelli, Massimo; Manuel, Cristina; Sa'd, Basil A

2008-12-12

Dissipative processes acting in rotating neutron stars are essential in preventing the growth of the r-mode instability. We estimate the damping time of r modes of a hypothetical compact quark star made up by color-flavor-locked quark matter at a temperature T < or approximately 0.01 MeV. The dissipation that we consider is due to the mutual friction force between the normal and the superfluid component arising from the elastic scattering of phonons with quantized vortices. This process is the dominant one for temperatures T < or approximately 0.01 MeV, where the mean free path of phonons due to their self-interactions is larger than the radius of the star. We find that r-mode oscillations are efficiently damped by this mechanism for pulsars rotating at frequencies of the order of 1 Hz at most. Our analysis rules out the possibility that cold pulsars rotating at higher frequencies are entirely made up by color-flavor-locked quark matter.

Study on Mosaic and Uniform Color Method of Satellite Image Fusion in Large Srea

NASA Astrophysics Data System (ADS)

Liu, S.; Li, H.; Wang, X.; Guo, L.; Wang, R.

2018-04-01

Due to the improvement of satellite radiometric resolution and the color difference for multi-temporal satellite remote sensing images and the large amount of satellite image data, how to complete the mosaic and uniform color process of satellite images is always an important problem in image processing. First of all using the bundle uniform color method and least squares mosaic method of GXL and the dodging function, the uniform transition of color and brightness can be realized in large area and multi-temporal satellite images. Secondly, using Color Mapping software to color mosaic images of 16bit to mosaic images of 8bit based on uniform color method with low resolution reference images. At last, qualitative and quantitative analytical methods are used respectively to analyse and evaluate satellite image after mosaic and uniformity coloring. The test reflects the correlation of mosaic images before and after coloring is higher than 95 % and image information entropy increases, texture features are enhanced which have been proved by calculation of quantitative indexes such as correlation coefficient and information entropy. Satellite image mosaic and color processing in large area has been well implemented.

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

NASA Astrophysics Data System (ADS)

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

2013-09-01

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

Internet Color Imaging

DTIC Science & Technology

2000-07-01

UNCLASSIFIED Defense Technical Information Center Compilation Part Notice ADPO1 1348 TITLE: Internet Color Imaging DISTRIBUTION: Approved for public...Paper Internet Color Imaging Hsien-Che Lee Imaging Science and Technology Laboratory Eastman Kodak Company, Rochester, New York 14650-1816 USA...ABSTRACT The sharing and exchange of color images over the Internet pose very challenging problems to color science and technology . Emerging color standards

Multimodal digital color imaging system for facial skin lesion analysis

NASA Astrophysics Data System (ADS)

Bae, Youngwoo; Lee, Youn-Heum; Jung, Byungjo

2008-02-01

In dermatology, various digital imaging modalities have been used as an important tool to quantitatively evaluate the treatment effect of skin lesions. Cross-polarization color image was used to evaluate skin chromophores (melanin and hemoglobin) information and parallel-polarization image to evaluate skin texture information. In addition, UV-A induced fluorescent image has been widely used to evaluate various skin conditions such as sebum, keratosis, sun damages, and vitiligo. In order to maximize the evaluation efficacy of various skin lesions, it is necessary to integrate various imaging modalities into an imaging system. In this study, we propose a multimodal digital color imaging system, which provides four different digital color images of standard color image, parallel and cross-polarization color image, and UV-A induced fluorescent color image. Herein, we describe the imaging system and present the examples of image analysis. By analyzing the color information and morphological features of facial skin lesions, we are able to comparably and simultaneously evaluate various skin lesions. In conclusion, we are sure that the multimodal color imaging system can be utilized as an important assistant tool in dermatology.

Pixel-based image fusion with false color mapping

NASA Astrophysics Data System (ADS)

Zhao, Wei; Mao, Shiyi

2003-06-01

In this paper, we propose a pixel-based image fusion algorithm that combines the gray-level image fusion method with the false color mapping. This algorithm integrates two gray-level images presenting different sensor modalities or at different frequencies and produces a fused false-color image. The resulting image has higher information content than each of the original images. The objects in the fused color image are easy to be recognized. This algorithm has three steps: first, obtaining the fused gray-level image of two original images; second, giving the generalized high-boost filtering images between fused gray-level image and two source images respectively; third, generating the fused false-color image. We use the hybrid averaging and selection fusion method to obtain the fused gray-level image. The fused gray-level image will provide better details than two original images and reduce noise at the same time. But the fused gray-level image can't contain all detail information in two source images. At the same time, the details in gray-level image cannot be discerned as easy as in a color image. So a color fused image is necessary. In order to create color variation and enhance details in the final fusion image, we produce three generalized high-boost filtering images. These three images are displayed through red, green and blue channel respectively. A fused color image is produced finally. This method is used to fuse two SAR images acquired on the San Francisco area (California, USA). The result shows that fused false-color image enhances the visibility of certain details. The resolution of the final false-color image is the same as the resolution of the input images.

Color line scan camera technology and machine vision: requirements to consider

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.

1997-08-01

Color machine vision has shown a dynamic uptrend in use within the past few years as the introduction of new cameras and scanner technologies itself underscores. In the future, the movement from monochrome imaging to color will hasten, as machine vision system users demand more knowledge about their product stream. As color has come to the machine vision, certain requirements for the equipment used to digitize color images are needed. Color machine vision needs not only a good color separation but also a high dynamic range and a good linear response from the camera used. Good dynamic range and linear response is necessary for color machine vision. The importance of these features becomes even more important when the image is converted to another color space. There is always lost some information when converting integer data to another form. Traditionally the color image processing has been much slower technique than the gray level image processing due to the three times greater data amount per image. The same has applied for the three times more memory needed. The advancements in computers, memory and processing units has made it possible to handle even large color images today cost efficiently. In some cases he image analysis in color images can in fact even be easier and faster than with a similar gray level image because of more information per pixel. Color machine vision sets new requirements for lighting, too. High intensity and white color light is required in order to acquire good images for further image processing or analysis. New development in lighting technology is bringing eventually solutions for color imaging.

PHASE QUANTIZATION STUDY OF SPATIAL LIGHT MODULATOR FOR EXTREME HIGH-CONTRAST IMAGING

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

Dou, Jiangpei; Ren, Deqing, E-mail: jpdou@niaot.ac.cn, E-mail: jiangpeidou@gmail.com

2016-11-20

Direct imaging of exoplanets by reflected starlight is extremely challenging due to the large luminosity ratio to the primary star. Wave-front control is a critical technique to attenuate the speckle noise in order to achieve an extremely high contrast. We present a phase quantization study of a spatial light modulator (SLM) for wave-front control to meet the contrast requirement of detection of a terrestrial planet in the habitable zone of a solar-type star. We perform the numerical simulation by employing the SLM with different phase accuracy and actuator numbers, which are related to the achievable contrast. We use an optimizationmore » algorithm to solve the quantization problems that is matched to the controllable phase step of the SLM. Two optical configurations are discussed with the SLM located before and after the coronagraph focal plane mask. The simulation result has constrained the specification for SLM phase accuracy in the above two optical configurations, which gives us a phase accuracy of 0.4/1000 and 1/1000 waves to achieve a contrast of 10{sup -10}. Finally, we have demonstrated that an SLM with more actuators can deliver a competitive contrast performance on the order of 10{sup -10} in comparison to that by using a deformable mirror.« less

Phase Quantization Study of Spatial Light Modulator for Extreme High-contrast Imaging

NASA Astrophysics Data System (ADS)

Dou, Jiangpei; Ren, Deqing

2016-11-01

Direct imaging of exoplanets by reflected starlight is extremely challenging due to the large luminosity ratio to the primary star. Wave-front control is a critical technique to attenuate the speckle noise in order to achieve an extremely high contrast. We present a phase quantization study of a spatial light modulator (SLM) for wave-front control to meet the contrast requirement of detection of a terrestrial planet in the habitable zone of a solar-type star. We perform the numerical simulation by employing the SLM with different phase accuracy and actuator numbers, which are related to the achievable contrast. We use an optimization algorithm to solve the quantization problems that is matched to the controllable phase step of the SLM. Two optical configurations are discussed with the SLM located before and after the coronagraph focal plane mask. The simulation result has constrained the specification for SLM phase accuracy in the above two optical configurations, which gives us a phase accuracy of 0.4/1000 and 1/1000 waves to achieve a contrast of 10-10. Finally, we have demonstrated that an SLM with more actuators can deliver a competitive contrast performance on the order of 10-10 in comparison to that by using a deformable mirror.

Accelerating simulation for the multiple-point statistics algorithm using vector quantization

NASA Astrophysics Data System (ADS)

Zuo, Chen; Pan, Zhibin; Liang, Hao

2018-03-01

Multiple-point statistics (MPS) is a prominent algorithm to simulate categorical variables based on a sequential simulation procedure. Assuming training images (TIs) as prior conceptual models, MPS extracts patterns from TIs using a template and records their occurrences in a database. However, complex patterns increase the size of the database and require considerable time to retrieve the desired elements. In order to speed up simulation and improve simulation quality over state-of-the-art MPS methods, we propose an accelerating simulation for MPS using vector quantization (VQ), called VQ-MPS. First, a variable representation is presented to make categorical variables applicable for vector quantization. Second, we adopt a tree-structured VQ to compress the database so that stationary simulations are realized. Finally, a transformed template and classified VQ are used to address nonstationarity. A two-dimensional (2D) stationary channelized reservoir image is used to validate the proposed VQ-MPS. In comparison with several existing MPS programs, our method exhibits significantly better performance in terms of computational time, pattern reproductions, and spatial uncertainty. Further demonstrations consist of a 2D four facies simulation, two 2D nonstationary channel simulations, and a three-dimensional (3D) rock simulation. The results reveal that our proposed method is also capable of solving multifacies, nonstationarity, and 3D simulations based on 2D TIs.

Utilizing typical color appearance models to represent perceptual brightness and colorfulness for digital images

NASA Astrophysics Data System (ADS)

Gong, Rui; Wang, Qing; Shao, Xiaopeng; Zhou, Conghao

2016-12-01

This study aims to expand the applications of color appearance models to representing the perceptual attributes for digital images, which supplies more accurate methods for predicting image brightness and image colorfulness. Two typical models, i.e., the CIELAB model and the CIECAM02, were involved in developing algorithms to predict brightness and colorfulness for various images, in which three methods were designed to handle pixels of different color contents. Moreover, massive visual data were collected from psychophysical experiments on two mobile displays under three lighting conditions to analyze the characteristics of visual perception on these two attributes and to test the prediction accuracy of each algorithm. Afterward, detailed analyses revealed that image brightness and image colorfulness were predicted well by calculating the CIECAM02 parameters of lightness and chroma; thus, the suitable methods for dealing with different color pixels were determined for image brightness and image colorfulness, respectively. This study supplies an example of enlarging color appearance models to describe image perception.

Color reproduction and processing algorithm based on real-time mapping for endoscopic images.

PubMed

Khan, Tareq H; Mohammed, Shahed K; Imtiaz, Mohammad S; Wahid, Khan A

2016-01-01

In this paper, we present a real-time preprocessing algorithm for image enhancement for endoscopic images. A novel dictionary based color mapping algorithm is used for reproducing the color information from a theme image. The theme image is selected from a nearby anatomical location. A database of color endoscopy image for different location is prepared for this purpose. The color map is dynamic as its contents change with the change of the theme image. This method is used on low contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. It can also be applied to enhance the tone of color images. The statistic visual representation and universal image quality measures show that the proposed method can highlight the mucosa structure compared to other methods. The color similarity has been verified using Delta E color difference, structure similarity index, mean structure similarity index and structure and hue similarity. The color enhancement was measured using color enhancement factor that shows considerable improvements. The proposed algorithm has low and linear time complexity, which results in higher execution speed than other related works.

Color segmentation in the HSI color space using the K-means algorithm

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.

Image authentication using distributed source coding.

PubMed

Lin, Yao-Chung; Varodayan, David; Girod, Bernd

2012-01-01

We present a novel approach using distributed source coding for image authentication. The key idea is to provide a Slepian-Wolf encoded quantized image projection as authentication data. This version can be correctly decoded with the help of an authentic image as side information. Distributed source coding provides the desired robustness against legitimate variations while detecting illegitimate modification. The decoder incorporating expectation maximization algorithms can authenticate images which have undergone contrast, brightness, and affine warping adjustments. Our authentication system also offers tampering localization by using the sum-product algorithm.

Image segmentation using fuzzy LVQ clustering networks

NASA Technical Reports Server (NTRS)

Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

1992-01-01

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma

NASA Astrophysics Data System (ADS)

Kawamura, Harumi; Yonemura, Shunichi; Ohya, Jun; Kojima, Akira

2013-02-01

A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Influence of imaging resolution on color fidelity in digital archiving.

PubMed

Zhang, Pengchang; Toque, Jay Arre; Ide-Ektessabi, Ari

2015-11-01

Color fidelity is of paramount importance in digital archiving. In this paper, the relationship between color fidelity and imaging resolution was explored by calculating the color difference of an IT8.7/2 color chart with a CIELAB color difference formula for scanning and simulation images. Microscopic spatial sampling was used in selecting the image pixels for the calculations to highlight the loss of color information. A ratio, called the relative imaging definition (RID), was defined to express the correlation between image resolution and color fidelity. The results show that in order for color differences to remain unrecognizable, the imaging resolution should be at least 10 times higher than the physical dimension of the smallest feature in the object being studied.

Advanced microlens and color filter process technology for the high-efficiency CMOS and CCD image sensors

NASA Astrophysics Data System (ADS)

Fan, Yang-Tung; Peng, Chiou-Shian; Chu, Cheng-Yu

2000-12-01

New markets are emerging for digital electronic image device, especially in visual communications, PC camera, mobile/cell phone, security system, toys, vehicle image system and computer peripherals for document capture. To enable one-chip image system that image sensor is with a full digital interface, can make image capture devices in our daily lives. Adding a color filter to such image sensor in a pattern of mosaics pixel or wide stripes can make image more real and colorful. We can say 'color filter makes the life more colorful color filter is? Color filter means can filter image light source except the color with specific wavelength and transmittance that is same as color filter itself. Color filter process is coating and patterning green, red and blue (or cyan, magenta and yellow) mosaic resists onto matched pixel in image sensing array pixels. According to the signal caught from each pixel, we can figure out the environment image picture. Widely use of digital electronic camera and multimedia applications today makes the feature of color filter becoming bright. Although it has challenge but it is very worthy to develop the process of color filter. We provide the best service on shorter cycle time, excellent color quality, high and stable yield. The key issues of advanced color process have to be solved and implemented are planarization and micro-lens technology. Lost of key points of color filter process technology have to consider will also be described in this paper.

Image subregion querying using color correlograms

DOEpatents

Huang, Jing; Kumar, Shanmugasundaram Ravi; Mitra, Mandar; Zhu, Wei-Jing

2002-01-01

A color correlogram (10) is a representation expressing the spatial correlation of color and distance between pixels in a stored image. The color correlogram (10) may be used to distinguish objects in an image as well as between images in a plurality of images. By intersecting a color correlogram of an image object with correlograms of images to be searched, those images which contain the objects are identified by the intersection correlogram.

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Multiple Auto-Adapting Color Balancing for Large Number of Images

NASA Astrophysics Data System (ADS)

Zhou, X.

2015-04-01

This paper presents a powerful technology of color balance between images. It does not only work for small number of images but also work for unlimited large number of images. Multiple adaptive methods are used. To obtain color seamless mosaic dataset, local color is adjusted adaptively towards the target color. Local statistics of the source images are computed based on the so-called adaptive dodging window. The adaptive target colors are statistically computed according to multiple target models. The gamma function is derived from the adaptive target and the adaptive source local stats. It is applied to the source images to obtain the color balanced output images. Five target color surface models are proposed. They are color point (or single color), color grid, 1st, 2nd and 3rd 2D polynomials. Least Square Fitting is used to obtain the polynomial target color surfaces. Target color surfaces are automatically computed based on all source images or based on an external target image. Some special objects such as water and snow are filtered by percentage cut or a given mask. Excellent results are achieved. The performance is extremely fast to support on-the-fly color balancing for large number of images (possible of hundreds of thousands images). Detailed algorithm and formulae are described. Rich examples including big mosaic datasets (e.g., contains 36,006 images) are given. Excellent results and performance are presented. The results show that this technology can be successfully used in various imagery to obtain color seamless mosaic. This algorithm has been successfully using in ESRI ArcGis.

Robust image region descriptor using local derivative ordinal binary pattern

NASA Astrophysics Data System (ADS)

Shang, Jun; Chen, Chuanbo; Pei, Xiaobing; Liang, Hu; Tang, He; Sarem, Mudar

2015-05-01

Binary image descriptors have received a lot of attention in recent years, since they provide numerous advantages, such as low memory footprint and efficient matching strategy. However, they utilize intermediate representations and are generally less discriminative than floating-point descriptors. We propose an image region descriptor, namely local derivative ordinal binary pattern, for object recognition and image categorization. In order to preserve more local contrast and edge information, we quantize the intensity differences between the central pixels and their neighbors of the detected local affine covariant regions in an adaptive way. These differences are then sorted and mapped into binary codes and histogrammed with a weight of the sum of the absolute value of the differences. Furthermore, the gray level of the central pixel is quantized to further improve the discriminative ability. Finally, we combine them to form a joint histogram to represent the features of the image. We observe that our descriptor preserves more local brightness and edge information than traditional binary descriptors. Also, our descriptor is robust to rotation, illumination variations, and other geometric transformations. We conduct extensive experiments on the standard ETHZ and Kentucky datasets for object recognition and PASCAL for image classification. The experimental results show that our descriptor outperforms existing state-of-the-art methods.

A Novel Texture-Quantization-Based Reversible Multiple Watermarking Scheme Applied to Health Information System.

PubMed

Turuk, Mousami; Dhande, Ashwin

2018-04-01

The recent innovations in information and communication technologies have appreciably changed the panorama of health information system (HIS). These advances provide new means to process, handle, and share medical images and also augment the medical image security issues in terms of confidentiality, reliability, and integrity. Digital watermarking has emerged as new era that offers acceptable solutions to the security issues in HIS. Texture is a significant feature to detect the embedding sites in an image, which further leads to substantial improvement in the robustness. However, considering the perspective of digital watermarking, this feature has received meager attention in the reported literature. This paper exploits the texture property of an image and presents a novel hybrid texture-quantization-based approach for reversible multiple watermarking. The watermarked image quality has been accessed by peak signal to noise ratio (PSNR), structural similarity measure (SSIM), and universal image quality index (UIQI), and the obtained results are superior to the state-of-the-art methods. The algorithm has been evaluated on a variety of medical imaging modalities (CT, MRA, MRI, US) and robustness has been verified, considering various image processing attacks including JPEG compression. The proposed scheme offers additional security using repetitive embedding of BCH encoded watermarks and ADM encrypted ECG signal. Experimental results achieved a maximum of 22,616 bits hiding capacity with PSNR of 53.64 dB.

Noise-Coupled Image Rejection Architecture of Complex Bandpass ΔΣAD Modulator

NASA Astrophysics Data System (ADS)

San, Hao; Kobayashi, Haruo

This paper proposes a new realization technique of image rejection function by noise-coupling architecture, which is used for a complex bandpass ΔΣAD modulator. The complex bandpass ΔΣAD modulator processes just input I and Q signals, not image signals, and the AD conversion can be realized with low power dissipation. It realizes an asymmetric noise-shaped spectra, which is desirable for such low-IF receiver applications. However, the performance of the complex bandpass ΔΣAD modulator suffers from the mismatch between internal analog I and Q paths. I/Q path mismatch causes an image signal, and the quantization noise of the mirror image band aliases into the desired signal band, which degrades the SQNDR (Signal to Quantization Noise and Distortion Ratio) of the modulator. In our proposed modulator architecture, an extra notch for image rejection is realized by noise-coupled topology. We just add some passive capacitors and switches to the modulator; the additional integrator circuit composed of an operational amplifier in the conventional image rejection realization is not necessary. Therefore, the performance of the complex modulator can be effectively raised without additional power dissipation. We have performed simulation with MATLAB to confirm the validity of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of image-rejection effectively, and improve the SQNDR of the complex bandpass ΔΣAD modulator.

Color standardization in whole slide imaging using a color calibration slide

PubMed Central

Bautista, Pinky A.; Hashimoto, Noriaki; Yagi, Yukako

2014-01-01

Background: Color consistency in histology images is still an issue in digital pathology. Different imaging systems reproduced the colors of a histological slide differently. Materials and Methods: Color correction was implemented using the color information of the nine color patches of a color calibration slide. The inherent spectral colors of these patches along with their scanned colors were used to derive a color correction matrix whose coefficients were used to convert the pixels’ colors to their target colors. Results: There was a significant reduction in the CIELAB color difference, between images of the same H & E histological slide produced by two different whole slide scanners by 3.42 units, P < 0.001 at 95% confidence level. Conclusion: Color variations in histological images brought about by whole slide scanning can be effectively normalized with the use of the color calibration slide. PMID:24672739

Automatic color preference correction for color reproduction

NASA Astrophysics Data System (ADS)

Tsukada, Masato; Funayama, Chisato; Tajima, Johji

2000-12-01

The reproduction of natural objects in color images has attracted a great deal of attention. Reproduction more pleasing colors of natural objects is one of the methods available to improve image quality. We developed an automatic color correction method to maintain preferred color reproduction for three significant categories: facial skin color, green grass and blue sky. In this method, a representative color in an object area to be corrected is automatically extracted from an input image, and a set of color correction parameters is selected depending on the representative color. The improvement in image quality for reproductions of natural image was more than 93 percent in subjective experiments. These results show the usefulness of our automatic color correction method for the reproduction of preferred colors.

Stereo matching image processing by synthesized color and the characteristic area by the synthesized color

NASA Astrophysics Data System (ADS)

Akiyama, Akira; Mutoh, Eiichiro; Kumagai, Hideo

2014-09-01

We have developed the stereo matching image processing by synthesized color and the corresponding area by the synthesized color for ranging the object and image recognition. The typical images from a pair of the stereo imagers may have some image disagreement each other due to the size change, missed place, appearance change and deformation of characteristic area. We constructed the synthesized color and corresponding color area with the same synthesized color to make the distinct stereo matching. We constructed the synthesized color and corresponding color area with the same synthesized color by the 3 steps. The first step is making binary edge image by differentiating the focused image from each imager and verifying that differentiated image has normal density of frequency distribution to find the threshold level of binary procedure. We used Daubechies wavelet transformation for the procedures of differentiating in this study. The second step is deriving the synthesized color by averaging color brightness between binary edge points with respect to horizontal direction and vertical direction alternatively. The averaging color procedure was done many times until the fluctuation of averaged color become negligible with respect to 256 levels in brightness. The third step is extracting area with same synthesized color by collecting the pixel of same synthesized color and grouping these pixel points by 4 directional connectivity relations. The matching areas for the stereo matching are determined by using synthesized color areas. The matching point is the center of gravity of each synthesized color area. The parallax between a pair of images is derived by the center of gravity of synthesized color area easily. The experiment of this stereo matching was done for the object of the soccer ball toy. From this experiment we showed that stereo matching by the synthesized color technique are simple and effective.

Simultaneous observation of the quantization and the interference pattern of a plasmonic near-field

DOE PAGES

Piazza, L.; Lummen, T. T. A.; Quiñonez, E.; ...

2015-03-02

Surface plasmon polaritons can confine electromagnetic fields in subwavelength spaces and are of interest for photonics, optical data storage devices and biosensing applications. In analogy to photons, they exhibit wave–particle duality, whose different aspects have recently been observed in separate tailored experiments. Here we demonstrate the ability of ultrafast transmission electron microscopy to simultaneously image both the spatial interference and the quantization of such confined plasmonic fields. Our experiments are accomplished by spatiotemporally overlapping electron and light pulses on a single nanowire suspended on a graphene film. The resulting energy exchange between single electrons and the quanta of the photoinducedmore » near-field is imaged synchronously with its spatial interference pattern. In conclusion, this methodology enables the control and visualization of plasmonic fields at the nanoscale, providing a promising tool for understanding the fundamental properties of confined electromagnetic fields and the development of advanced photonic circuits.« less

Simultaneous observation of the quantization and the interference pattern of a plasmonic near-field

PubMed Central

Piazza, L; Lummen, T.T.A.; Quiñonez, E; Murooka, Y; Reed, B.W.; Barwick, B; Carbone, F

2015-01-01

Surface plasmon polaritons can confine electromagnetic fields in subwavelength spaces and are of interest for photonics, optical data storage devices and biosensing applications. In analogy to photons, they exhibit wave–particle duality, whose different aspects have recently been observed in separate tailored experiments. Here we demonstrate the ability of ultrafast transmission electron microscopy to simultaneously image both the spatial interference and the quantization of such confined plasmonic fields. Our experiments are accomplished by spatiotemporally overlapping electron and light pulses on a single nanowire suspended on a graphene film. The resulting energy exchange between single electrons and the quanta of the photoinduced near-field is imaged synchronously with its spatial interference pattern. This methodology enables the control and visualization of plasmonic fields at the nanoscale, providing a promising tool for understanding the fundamental properties of confined electromagnetic fields and the development of advanced photonic circuits. PMID:25728197

Computational efficiency improvements for image colorization

NASA Astrophysics Data System (ADS)

Yu, Chao; Sharma, Gaurav; Aly, Hussein

2013-03-01

We propose an efficient algorithm for colorization of greyscale images. As in prior work, colorization is posed as an optimization problem: a user specifies the color for a few scribbles drawn on the greyscale image and the color image is obtained by propagating color information from the scribbles to surrounding regions, while maximizing the local smoothness of colors. In this formulation, colorization is obtained by solving a large sparse linear system, which normally requires substantial computation and memory resources. Our algorithm improves the computational performance through three innovations over prior colorization implementations. First, the linear system is solved iteratively without explicitly constructing the sparse matrix, which significantly reduces the required memory. Second, we formulate each iteration in terms of integral images obtained by dynamic programming, reducing repetitive computation. Third, we use a coarseto- fine framework, where a lower resolution subsampled image is first colorized and this low resolution color image is upsampled to initialize the colorization process for the fine level. The improvements we develop provide significant speedup and memory savings compared to the conventional approach of solving the linear system directly using off-the-shelf sparse solvers, and allow us to colorize images with typical sizes encountered in realistic applications on typical commodity computing platforms.

Development of a novel 2D color map for interactive segmentation of histological images.

PubMed

Chaudry, Qaiser; Sharma, Yachna; Raza, Syed H; Wang, May D

2012-05-01

We present a color segmentation approach based on a two-dimensional color map derived from the input image. Pathologists stain tissue biopsies with various colored dyes to see the expression of biomarkers. In these images, because of color variation due to inconsistencies in experimental procedures and lighting conditions, the segmentation used to analyze biological features is usually ad-hoc. Many algorithms like K-means use a single metric to segment the image into different color classes and rarely provide users with powerful color control. Our 2D color map interactive segmentation technique based on human color perception information and the color distribution of the input image, enables user control without noticeable delay. Our methodology works for different staining types and different types of cancer tissue images. Our proposed method's results show good accuracy with low response and computational time making it a feasible method for user interactive applications involving segmentation of histological images.

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.

Color filter array pattern identification using variance of color difference image

NASA Astrophysics Data System (ADS)

Shin, Hyun Jun; Jeon, Jong Ju; Eom, Il Kyu

2017-07-01

A color filter array is placed on the image sensor of a digital camera to acquire color images. Each pixel uses only one color, since the image sensor can measure only one color per pixel. Therefore, empty pixels are filled using an interpolation process called demosaicing. The original and the interpolated pixels have different statistical characteristics. If the image is modified by manipulation or forgery, the color filter array pattern is altered. This pattern change can be a clue for image forgery detection. However, most forgery detection algorithms have the disadvantage of assuming the color filter array pattern. We present an identification method of the color filter array pattern. Initially, the local mean is eliminated to remove the background effect. Subsequently, the color difference block is constructed to emphasize the difference between the original pixel and the interpolated pixel. The variance measure of the color difference image is proposed as a means of estimating the color filter array configuration. The experimental results show that the proposed method is effective in identifying the color filter array pattern. Compared with conventional methods, our method provides superior performance.

Qualitative evaluations and comparisons of six night-vision colorization methods

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Reese, Kristopher; Blasch, Erik; McManamon, Paul

2013-05-01

Current multispectral night vision (NV) colorization techniques can manipulate images to produce colorized images that closely resemble natural scenes. The colorized NV images can enhance human perception by improving observer object classification and reaction times especially for low light conditions. This paper focuses on the qualitative (subjective) evaluations and comparisons of six NV colorization methods. The multispectral images include visible (Red-Green- Blue), near infrared (NIR), and long wave infrared (LWIR) images. The six colorization methods are channel-based color fusion (CBCF), statistic matching (SM), histogram matching (HM), joint-histogram matching (JHM), statistic matching then joint-histogram matching (SM-JHM), and the lookup table (LUT). Four categries of quality measurements are used for the qualitative evaluations, which are contrast, detail, colorfulness, and overall quality. The score of each measurement is rated from 1 to 3 scale to represent low, average, and high quality, respectively. Specifically, high contrast (of rated score 3) means an adequate level of brightness and contrast. The high detail represents high clarity of detailed contents while maintaining low artifacts. The high colorfulness preserves more natural colors (i.e., closely resembles the daylight image). Overall quality is determined from the NV image compared to the reference image. Nine sets of multispectral NV images were used in our experiments. For each set, the six colorized NV images (produced from NIR and LWIR images) are concurrently presented to users along with the reference color (RGB) image (taken at daytime). A total of 67 subjects passed a screening test ("Ishihara Color Blindness Test") and were asked to evaluate the 9-set colorized images. The experimental results showed the quality order of colorization methods from the best to the worst: CBCF < SM < SM-JHM < LUT < JHM < HM. It is anticipated that this work will provide a benchmark for NV colorization and for quantitative evaluation using an objective metric such as objective evaluation index (OEI).

White-Light Optical Information Processing and Holography.

DTIC Science & Technology

1983-05-03

Processing, White-Light Holography, Image Subtraction, Image Deblurring , Coherence Requirement, Apparent Transfer Function, Source Encoding, Signal...in this period, also demonstrated several color image processing capabilities. Among those are broadband color image deblurring and color image...Broadband Image Deblurring ..... ......... 6 2.5 Color Image Subtraction ............... 7 2.6 Rainbow Holographic Aberrations . . ..... 7 2.7

Distance preservation in color image transforms

NASA Astrophysics Data System (ADS)

Santini, Simone

1999-12-01

Most current image processing systems work on color images, and color is a precious perceptual clue for determining image similarity. Working with color images, however, is not the sam thing as working with images taking values in a 3D Euclidean space. Not only are color spaces bounded, but the characteristics of the observer endow the space with a 'perceptual' metric that in general does not correspond to the metric naturally inherited from R3. This paper studies the problem of filtering color images abstractly. It begins by determining the properties of the color sum and color product operations such that he desirable properties of orthonormal bases will be preserved. The paper then defines a general scheme, based on the action of the additive group on the color space, by which operations that satisfy the required properties can be defined.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

MUNSELL COLOR ANALYSIS OF LANDSAT COLOR-RATIO-COMPOSITE IMAGES OF LIMONITIC AREAS IN SOUTHWEST NEW MEXICO.

USGS Publications Warehouse

Kruse, Fred A.

1984-01-01

Green areas on Landsat 4/5 - 4/6 - 6/7 (red - blue - green) color-ratio-composite (CRC) images represent limonite on the ground. Color variation on such images was analyzed to determine the causes of the color differences within and between the green areas. Digital transformation of the CRC data into the modified cylindrical Munsell color coordinates - hue, value, and saturation - was used to correlate image color characteristics with properties of surficial materials. The amount of limonite visible to the sensor is the primary cause of color differences in green areas on the CRCs. Vegetation density is a secondary cause of color variation of green areas on Landsat CRC images. Digital color analysis of Landsat CRC images can be used to map unknown areas. Color variations of green pixels allows discrimination among limonitic bedrock, nonlimonitic bedrock, nonlimonitic alluvium, and limonitic alluvium.

An image assessment study of image acceptability of the Galileo low gain antenna mission

NASA Technical Reports Server (NTRS)

Chuang, S. L.; Haines, R. F.; Grant, T.; Gold, Yaron; Cheung, Kar-Ming

1994-01-01

This paper describes a study conducted by NASA Ames Research Center (ARC) in collaboration with the Jet Propulsion Laboratory (JPL), Pasadena, California on the image acceptability of the Galileo Low Gain Antenna mission. The primary objective of the study is to determine the impact of the Integer Cosine Transform (ICT) compression algorithm on Galilean images of atmospheric bodies, moons, asteroids and Jupiter's rings. The approach involved fifteen volunteer subjects representing twelve institutions involved with the Galileo Solid State Imaging (SSI) experiment. Four different experiment specific quantization tables (q-table) and various compression stepsizes (q-factor) to achieve different compression ratios were used. It then determined the acceptability of the compressed monochromatic astronomical images as evaluated by Galileo SSI mission scientists. Fourteen different images were evaluated. Each observer viewed two versions of the same image side by side on a high resolution monitor, each was compressed using a different quantization stepsize. They were requested to select which image had the highest overall quality to support them in carrying out their visual evaluations of image content. Then they rated both images using a scale from one to five on its judged degree of usefulness. Up to four pre-selected types of images were presented with and without noise to each subject based upon results of a previously administered survey of their image preferences. Fourteen different images in seven image groups were studied. The results showed that: (1) acceptable compression ratios vary widely with the type of images; (2) noisy images detract greatly from image acceptability and acceptable compression ratios; and (3) atmospheric images of Jupiter seem to have higher compression ratios of 4 to 5 times that of some clear surface satellite images.

Observer performance assessment of JPEG-compressed high-resolution chest images

NASA Astrophysics Data System (ADS)

Good, Walter F.; Maitz, Glenn S.; King, Jill L.; Gennari, Rose C.; Gur, David

1999-05-01

The JPEG compression algorithm was tested on a set of 529 chest radiographs that had been digitized at a spatial resolution of 100 micrometer and contrast sensitivity of 12 bits. Images were compressed using five fixed 'psychovisual' quantization tables which produced average compression ratios in the range 15:1 to 61:1, and were then printed onto film. Six experienced radiologists read all cases from the laser printed film, in each of the five compressed modes as well as in the non-compressed mode. For comparison purposes, observers also read the same cases with reduced pixel resolutions of 200 micrometer and 400 micrometer. The specific task involved detecting masses, pneumothoraces, interstitial disease, alveolar infiltrates and rib fractures. Over the range of compression ratios tested, for images digitized at 100 micrometer, we were unable to demonstrate any statistically significant decrease (p greater than 0.05) in observer performance as measured by ROC techniques. However, the observers' subjective assessments of image quality did decrease significantly as image resolution was reduced and suggested a decreasing, but nonsignificant, trend as the compression ratio was increased. The seeming discrepancy between our failure to detect a reduction in observer performance, and other published studies, is likely due to: (1) the higher resolution at which we digitized our images; (2) the higher signal-to-noise ratio of our digitized films versus typical CR images; and (3) our particular choice of an optimized quantization scheme.

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern

PubMed Central

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-01-01

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method. PMID:28657602

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

PubMed

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

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.

Color camera computed tomography imaging spectrometer for improved spatial-spectral image accuracy

NASA Technical Reports Server (NTRS)

Wilson, Daniel W. (Inventor); Bearman, Gregory H. (Inventor); Johnson, William R. (Inventor)

2011-01-01

Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.

White Rock in False Color

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image shows the wind eroded deposit in Pollack Crater called 'White Rock'. This image was collected during the Southern Fall Season.

Image information: VIS instrument. Latitude -8, Longitude 25.2 East (334.8 West). 0 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

An interactive tool for gamut masking

NASA Astrophysics Data System (ADS)

Song, Ying; Lau, Cheryl; Süsstrunk, Sabine

2014-02-01

Artists often want to change the colors of an image to achieve a particular aesthetic goal. For example, they might limit colors to a warm or cool color scheme to create an image with a certain mood or feeling. Gamut masking is a technique that artists use to limit the set of colors they can paint with. They draw a mask over a color wheel and only use the hues within the mask. However, creating the color palette from the mask and applying the colors to the image requires skill. We propose an interactive tool for gamut masking that allows amateur artists to create an image with a desired mood or feeling. Our system extracts a 3D color gamut from the 2D user-drawn mask and maps the image to this gamut. The user can draw a different gamut mask or locally refine the image colors. Our voxel grid gamut representation allows us to represent gamuts of any shape, and our cluster-based image representation allows the user to change colors locally.

True color scanning laser ophthalmoscopy and optical coherence tomography handheld probe

PubMed Central

LaRocca, Francesco; Nankivil, Derek; Farsiu, Sina; Izatt, Joseph A.

2014-01-01

Scanning laser ophthalmoscopes (SLOs) are able to achieve superior contrast and axial sectioning capability compared to fundus photography. However, SLOs typically use monochromatic illumination and are thus unable to extract color information of the retina. Previous color SLO imaging techniques utilized multiple lasers or narrow band sources for illumination, which allowed for multiple color but not “true color” imaging as done in fundus photography. We describe the first “true color” SLO, handheld color SLO, and combined color SLO integrated with a spectral domain optical coherence tomography (OCT) system. To achieve accurate color imaging, the SLO was calibrated with a color test target and utilized an achromatizing lens when imaging the retina to correct for the eye’s longitudinal chromatic aberration. Color SLO and OCT images from volunteers were then acquired simultaneously with a combined power under the ANSI limit. Images from this system were then compared with those from commercially available SLOs featuring multiple narrow-band color imaging. PMID:25401032

Color image encryption based on color blend and chaos permutation in the reality-preserving multiple-parameter fractional Fourier transform domain

NASA Astrophysics Data System (ADS)

Lang, Jun

2015-03-01

In this paper, we propose a novel color image encryption method by using Color Blend (CB) and Chaos Permutation (CP) operations in the reality-preserving multiple-parameter fractional Fourier transform (RPMPFRFT) domain. The original color image is first exchanged and mixed randomly from the standard red-green-blue (RGB) color space to R‧G‧B‧ color space by rotating the color cube with a random angle matrix. Then RPMPFRFT is employed for changing the pixel values of color image, three components of the scrambled RGB color space are converted by RPMPFRFT with three different transform pairs, respectively. Comparing to the complex output transform, the RPMPFRFT transform ensures that the output is real which can save storage space of image and convenient for transmission in practical applications. To further enhance the security of the encryption system, the output of the former steps is scrambled by juxtaposition of sections of the image in the reality-preserving multiple-parameter fractional Fourier domains and the alignment of sections is determined by two coupled chaotic logistic maps. The parameters in the Color Blend, Chaos Permutation and the RPMPFRFT transform are regarded as the key in the encryption algorithm. The proposed color image encryption can also be applied to encrypt three gray images by transforming the gray images into three RGB color components of a specially constructed color image. Numerical simulations are performed to demonstrate that the proposed algorithm is feasible, secure, sensitive to keys and robust to noise attack and data loss.

Optimized nonorthogonal transforms for image compression.

PubMed

Guleryuz, O G; Orchard, M T

1997-01-01

The transform coding of images is analyzed from a common standpoint in order to generate a framework for the design of optimal transforms. It is argued that all transform coders are alike in the way they manipulate the data structure formed by transform coefficients. A general energy compaction measure is proposed to generate optimized transforms with desirable characteristics particularly suited to the simple transform coding operation of scalar quantization and entropy coding. It is shown that the optimal linear decoder (inverse transform) must be an optimal linear estimator, independent of the structure of the transform generating the coefficients. A formulation that sequentially optimizes the transforms is presented, and design equations and algorithms for its computation provided. The properties of the resulting transform systems are investigated. In particular, it is shown that the resulting basis are nonorthogonal and complete, producing energy compaction optimized, decorrelated transform coefficients. Quantization issues related to nonorthogonal expansion coefficients are addressed with a simple, efficient algorithm. Two implementations are discussed, and image coding examples are given. It is shown that the proposed design framework results in systems with superior energy compaction properties and excellent coding results.

Portable real-time color night vision

NASA Astrophysics Data System (ADS)

Toet, Alexander; Hogervorst, Maarten A.

2008-03-01

We developed a simple and fast lookup-table based method to derive and apply natural daylight colors to multi-band night-time images. The method deploys an optimal color transformation derived from a set of samples taken from a daytime color reference image. The colors in the resulting colorized multiband night-time images closely resemble the colors in the daytime color reference image. Also, object colors remain invariant under panning operations and are independent of the scene content. Here we describe the implementation of this method in two prototype portable dual band realtime night vision systems. One system provides co-aligned visual and near-infrared bands of two image intensifiers, the other provides co-aligned images from a digital image intensifier and an uncooled longwave infrared microbolometer. The co-aligned images from both systems are further processed by a notebook computer. The color mapping is implemented as a realtime lookup table transform. The resulting colorised video streams can be displayed in realtime on head mounted displays and stored on the hard disk of the notebook computer. Preliminary field trials demonstrate the potential of these systems for applications like surveillance, navigation and target detection.

Quantized visual awareness.

PubMed

Escobar, W A

2013-01-01

The proposed model holds that, at its most fundamental level, visual awareness is quantized. That is to say that visual awareness arises as individual bits of awareness through the action of neural circuits with hundreds to thousands of neurons in at least the human striate cortex. Circuits with specific topologies will reproducibly result in visual awareness that correspond to basic aspects of vision like color, motion, and depth. These quanta of awareness (qualia) are produced by the feedforward sweep that occurs through the geniculocortical pathway but are not integrated into a conscious experience until recurrent processing from centers like V4 or V5 select the appropriate qualia being produced in V1 to create a percept. The model proposed here has the potential to shift the focus of the search for visual awareness to the level of microcircuits and these likely exist across the kingdom Animalia. Thus establishing qualia as the fundamental nature of visual awareness will not only provide a deeper understanding of awareness, but also allow for a more quantitative understanding of the evolution of visual awareness throughout the animal kingdom.

Continuing Through Iani Chaos

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image continues the northward trend through the Iani Chaos region. Compare this image to Monday's and Tuesday's. This image was collected during the Southern Fall season.

Image information: VIS instrument. Latitude -0.1 Longitude 342.6 East (17.4 West). 19 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Aureum Chaos: Another View

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image is located in a different part of Aureum Chaos. Compare the surface textures with yesterday's image. This image was collected during the Southern Fall season.

Image information: VIS instrument. Latitude -4.1, Longitude 333.9 East (26.1 West). 35 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Joint sparse coding based spatial pyramid matching for classification of color medical image.

PubMed

Shi, Jun; Li, Yi; Zhu, Jie; Sun, Haojie; Cai, Yin

2015-04-01

Although color medical images are important in clinical practice, they are usually converted to grayscale for further processing in pattern recognition, resulting in loss of rich color information. The sparse coding based linear spatial pyramid matching (ScSPM) and its variants are popular for grayscale image classification, but cannot extract color information. In this paper, we propose a joint sparse coding based SPM (JScSPM) method for the classification of color medical images. A joint dictionary can represent both the color information in each color channel and the correlation between channels. Consequently, the joint sparse codes calculated from a joint dictionary can carry color information, and therefore this method can easily transform a feature descriptor originally designed for grayscale images to a color descriptor. A color hepatocellular carcinoma histological image dataset was used to evaluate the performance of the proposed JScSPM algorithm. Experimental results show that JScSPM provides significant improvements as compared with the majority voting based ScSPM and the original ScSPM for color medical image classification. Copyright © 2014 Elsevier Ltd. All rights reserved.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

PubMed

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Colored Chaos

NASA Technical Reports Server (NTRS)

2004-01-01

[figure removed for brevity, see original site]

Released 7 May 2004 This daytime visible color image was collected on May 30, 2002 during the Southern Fall season in Atlantis Chaos.

The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

Image information: VIS instrument. Latitude -34.5, Longitude 183.6 East (176.4 West). 38 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Iani Chaos in False Color

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image of a portion of the Iani Chaos region was collected during the Southern Fall season.

Image information: VIS instrument. Latitude -2.6 Longitude 342.4 East (17.6 West). 36 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Polar Cap Colors

NASA Technical Reports Server (NTRS)

2004-01-01

[figure removed for brevity, see original site]

Released 12 May 2004 This daytime visible color image was collected on June 6, 2003 during the Southern Spring season near the South Polar Cap Edge.

The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

Image information: VIS instrument. Latitude -77.8, Longitude 195 East (165 West). 38 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Selective document image data compression technique

DOEpatents

Fu, C.Y.; Petrich, L.I.

1998-05-19

A method of storing information from filled-in form-documents comprises extracting the unique user information in the foreground from the document form information in the background. The contrast of the pixels is enhanced by a gamma correction on an image array, and then the color value of each of pixel is enhanced. The color pixels lying on edges of an image are converted to black and an adjacent pixel is converted to white. The distance between black pixels and other pixels in the array is determined, and a filled-edge array of pixels is created. User information is then converted to a two-color format by creating a first two-color image of the scanned image by converting all pixels darker than a threshold color value to black. All the pixels that are lighter than the threshold color value to white. Then a second two-color image of the filled-edge file is generated by converting all pixels darker than a second threshold value to black and all pixels lighter than the second threshold color value to white. The first two-color image and the second two-color image are then combined and filtered to smooth the edges of the image. The image may be compressed with a unique Huffman coding table for that image. The image file is also decimated to create a decimated-image file which can later be interpolated back to produce a reconstructed image file using a bilinear interpolation kernel. 10 figs.

Selective document image data compression technique

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1998-01-01

A method of storing information from filled-in form-documents comprises extracting the unique user information in the foreground from the document form information in the background. The contrast of the pixels is enhanced by a gamma correction on an image array, and then the color value of each of pixel is enhanced. The color pixels lying on edges of an image are converted to black and an adjacent pixel is converted to white. The distance between black pixels and other pixels in the array is determined, and a filled-edge array of pixels is created. User information is then converted to a two-color format by creating a first two-color image of the scanned image by converting all pixels darker than a threshold color value to black. All the pixels that are lighter than the threshold color value to white. Then a second two-color image of the filled-edge file is generated by converting all pixels darker than a second threshold value to black and all pixels lighter than the second threshold color value to white. The first two-color image and the second two-color image are then combined and filtered to smooth the edges of the image. The image may be compressed with a unique Huffman coding table for that image. The image file is also decimated to create a decimated-image file which can later be interpolated back to produce a reconstructed image file using a bilinear interpolation kernel.--(235 words)

Color calibration and fusion of lens-free and mobile-phone microscopy images for high-resolution and accurate color reproduction

NASA Astrophysics Data System (ADS)

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2016-06-01

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed “digital color fusion microscopy” (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available.

Color calibration and fusion of lens-free and mobile-phone microscopy images for high-resolution and accurate color reproduction

PubMed Central

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2016-01-01

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed “digital color fusion microscopy” (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available. PMID:27283459

Color calibration and fusion of lens-free and mobile-phone microscopy images for high-resolution and accurate color reproduction.

PubMed

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2016-06-10

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed "digital color fusion microscopy" (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available.

A robust hidden Markov Gauss mixture vector quantizer for a noisy source.

PubMed

Pyun, Kyungsuk Peter; Lim, Johan; Gray, Robert M

2009-07-01

Noise is ubiquitous in real life and changes image acquisition, communication, and processing characteristics in an uncontrolled manner. Gaussian noise and Salt and Pepper noise, in particular, are prevalent in noisy communication channels, camera and scanner sensors, and medical MRI images. It is not unusual for highly sophisticated image processing algorithms developed for clean images to malfunction when used on noisy images. For example, hidden Markov Gauss mixture models (HMGMM) have been shown to perform well in image segmentation applications, but they are quite sensitive to image noise. We propose a modified HMGMM procedure specifically designed to improve performance in the presence of noise. The key feature of the proposed procedure is the adjustment of covariance matrices in Gauss mixture vector quantizer codebooks to minimize an overall minimum discrimination information distortion (MDI). In adjusting covariance matrices, we expand or shrink their elements based on the noisy image. While most results reported in the literature assume a particular noise type, we propose a framework without assuming particular noise characteristics. Without denoising the corrupted source, we apply our method directly to the segmentation of noisy sources. We apply the proposed procedure to the segmentation of aerial images with Salt and Pepper noise and with independent Gaussian noise, and we compare our results with those of the median filter restoration method and the blind deconvolution-based method, respectively. We show that our procedure has better performance than image restoration-based techniques and closely matches to the performance of HMGMM for clean images in terms of both visual segmentation results and error rate.

Color image enhancement of medical images using alpha-rooting and zonal alpha-rooting methods on 2D QDFT

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.; John, Aparna; Agaian, Sos S.

2017-03-01

2-D quaternion discrete Fourier transform (2-D QDFT) is the Fourier transform applied to color images when the color images are considered in the quaternion space. The quaternion numbers are four dimensional hyper-complex numbers. Quaternion representation of color image allows us to see the color of the image as a single unit. In quaternion approach of color image enhancement, each color is seen as a vector. This permits us to see the merging effect of the color due to the combination of the primary colors. The color images are used to be processed by applying the respective algorithm onto each channels separately, and then, composing the color image from the processed channels. In this article, the alpha-rooting and zonal alpha-rooting methods are used with the 2-D QDFT. In the alpha-rooting method, the alpha-root of the transformed frequency values of the 2-D QDFT are determined before taking the inverse transform. In the zonal alpha-rooting method, the frequency spectrum of the 2-D QDFT is divided by different zones and the alpha-rooting is applied with different alpha values for different zones. The optimization of the choice of alpha values is done with the genetic algorithm. The visual perception of 3-D medical images is increased by changing the reference gray line.

Mawrth Valles

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image of an old channel floor and surrounding highlands is located in the lower reach of Mawrth Valles. This image was collected during the Northern Spring season.

Image information: VIS instrument. Latitude 25.7, Longitude 341.2 East (18.8 West). 35 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Perceived assessment metrics for visible and infrared color fused image quality without reference image

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Chen, Qian; Gu, Guohua; Ren, Jianle; Sui, Xiubao

2015-02-01

Designing objective quality assessment of color-fused image is a very demanding and challenging task. We propose four no-reference metrics based on human visual system characteristics for objectively evaluating the quality of false color fusion image. The perceived edge metric (PEM) is defined based on visual perception model and color image gradient similarity between the fused image and the source images. The perceptual contrast metric (PCM) is established associating multi-scale contrast and varying contrast sensitivity filter (CSF) with color components. The linear combination of the standard deviation and mean value over the fused image construct the image colorfulness metric (ICM). The color comfort metric (CCM) is designed by the average saturation and the ratio of pixels with high and low saturation. The qualitative and quantitative experimental results demonstrate that the proposed metrics have a good agreement with subjective perception.

Color correction with blind image restoration based on multiple images using a low-rank model

NASA Astrophysics Data System (ADS)

Li, Dong; Xie, Xudong; Lam, Kin-Man

2014-03-01

We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

Active Planning, Sensing and Recognition Using a Resource-Constrained Discriminant POMDP

DTIC Science & Technology

2014-06-28

classes of military vehicles, with sample images shown in Fig. 1. The vehicles were captured from various angles. 4785 images with depression angles 17...and 30◦ are used for training, and 4351 images with depression angles 15◦ and 45◦ are used for testing. The azimuth angles are quantized into 12...selection by collecting the engine sounds for the 8 vehicle classes from the Youtube . The sounds are attenuated differently in 6 view directions

Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

PubMed

Park, Chulhee; Kang, Moon Gi

2016-05-18

A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition

PubMed Central

Park, Chulhee; Kang, Moon Gi

2016-01-01

A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors. PMID:27213381

Single Channel Quantum Color Image Encryption Algorithm Based on HSI Model and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Gong, Li-Hua; He, Xiang-Tao; Tan, Ru-Chao; Zhou, Zhi-Hong

2018-01-01

In order to obtain high-quality color images, it is important to keep the hue component unchanged while emphasize the intensity or saturation component. As a public color model, Hue-Saturation Intensity (HSI) model is commonly used in image processing. A new single channel quantum color image encryption algorithm based on HSI model and quantum Fourier transform (QFT) is investigated, where the color components of the original color image are converted to HSI and the logistic map is employed to diffuse the relationship of pixels in color components. Subsequently, quantum Fourier transform is exploited to fulfill the encryption. The cipher-text is a combination of a gray image and a phase matrix. Simulations and theoretical analyses demonstrate that the proposed single channel quantum color image encryption scheme based on the HSI model and quantum Fourier transform is secure and effective.

Optimal chroma-like channel design for passive color image splicing detection

NASA Astrophysics Data System (ADS)

Zhao, Xudong; Li, Shenghong; Wang, Shilin; Li, Jianhua; Yang, Kongjin

2012-12-01

Image splicing is one of the most common image forgeries in our daily life and due to the powerful image manipulation tools, image splicing is becoming easier and easier. Several methods have been proposed for image splicing detection and all of them worked on certain existing color channels. However, the splicing artifacts vary in different color channels and the selection of color model is important for image splicing detection. In this article, instead of finding an existing color model, we propose a color channel design method to find the most discriminative channel which is referred to as optimal chroma-like channel for a given feature extraction method. Experimental results show that both spatial and frequency features extracted from the designed channel achieve higher detection rate than those extracted from traditional color channels.

Color image guided depth image super resolution using fusion filter

NASA Astrophysics Data System (ADS)

He, Jin; Liang, Bin; He, Ying; Yang, Jun

2018-04-01

Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

Auream Chaos

NASA Technical Reports Server (NTRS)

2005-01-01

[figure removed for brevity, see original site]

The THEMIS VIS camera is capable of capturing color images of the Martian surface using five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from using multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

This false color image was collected during Southern Fall and shows part of the Aureum Chaos.

Image information: VIS instrument. Latitude -3.6, Longitude 332.9 East (27.1 West). 35 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Northern Polar Cap

NASA Technical Reports Server (NTRS)

2004-01-01

[figure removed for brevity, see original site]

Released 13 May 2004 This nighttime visible color image was collected on November 26, 2002 during the Northern Summer season near the North Polar Cap Edge.

The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

Image information: VIS instrument. Latitude 80, Longitude 43.2 East (316.8 West). 38 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

Wavelet subband coding of computer simulation output using the A++ array class library

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

Bradley, J.N.; Brislawn, C.M.; Quinlan, D.J.

1995-07-01

The goal of the project is to produce utility software for off-line compression of existing data and library code that can be called from a simulation program for on-line compression of data dumps as the simulation proceeds. Naturally, we would like the amount of CPU time required by the compression algorithm to be small in comparison to the requirements of typical simulation codes. We also want the algorithm to accomodate a wide variety of smooth, multidimensional data types. For these reasons, the subband vector quantization (VQ) approach employed in has been replaced by a scalar quantization (SQ) strategy using amore » bank of almost-uniform scalar subband quantizers in a scheme similar to that used in the FBI fingerprint image compression standard. This eliminates the considerable computational burdens of training VQ codebooks for each new type of data and performing nearest-vector searches to encode the data. The comparison of subband VQ and SQ algorithms in indicated that, in practice, there is relatively little additional gain from using vector as opposed to scalar quantization on DWT subbands, even when the source imagery is from a very homogeneous population, and our subjective experience with synthetic computer-generated data supports this stance. It appears that a careful study is needed of the tradeoffs involved in selecting scalar vs. vector subband quantization, but such an analysis is beyond the scope of this paper. Our present work is focused on the problem of generating wavelet transform/scalar quantization (WSQ) implementations that can be ported easily between different hardware environments. This is an extremely important consideration given the great profusion of different high-performance computing architectures available, the high cost associated with learning how to map algorithms effectively onto a new architecture, and the rapid rate of evolution in the world of high-performance computing.« less

Autographic theme extraction

USGS Publications Warehouse

Edson, D.; Colvocoresses, Alden P.

1973-01-01

Remote-sensor images, including aerial and space photographs, are generally recorded on film, where the differences in density create the image of the scene. With panchromatic and multiband systems the density differences are recorded in shades of gray. On color or color infrared film, with the emulsion containing dyes sensitive to different wavelengths, a color image is created by a combination of color densities. The colors, however, can be separated by filtering or other techniques, and the color image reduced to monochromatic images in which each of the separated bands is recorded as a function of the gray scale.

Nonlinear Multiscale Transformations: From Synchronization to Error Control

DTIC Science & Technology

2001-07-01

transformation (plus the quantization step) has taken place, a lossless Lempel - Ziv compression algorithm is applied to reduce the size of the transformed... compressed data are all very close, however the visual quality of the reconstructed image is significantly better for the EC compression algorithm ...used in recent times in the first step of transform coding algorithms for image compression . Ideally, a multiscale transformation allows for an

Brain MR image segmentation using NAMS in pseudo-color.

PubMed

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

Demosaiced pixel super-resolution for multiplexed holographic color imaging

PubMed Central

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2016-01-01

To synthesize a holographic color image, one can sequentially take three holograms at different wavelengths, e.g., at red (R), green (G) and blue (B) parts of the spectrum, and digitally merge them. To speed up the imaging process by a factor of three, a Bayer color sensor-chip can also be used to demultiplex three wavelengths that simultaneously illuminate the sample and digitally retrieve individual set of holograms using the known transmission spectra of the Bayer color filters. However, because the pixels of different channels (R, G, B) on a Bayer color sensor are not at the same physical location, conventional demosaicing techniques generate color artifacts in holographic imaging using simultaneous multi-wavelength illumination. Here we demonstrate that pixel super-resolution can be merged into the color de-multiplexing process to significantly suppress the artifacts in wavelength-multiplexed holographic color imaging. This new approach, termed Demosaiced Pixel Super-Resolution (D-PSR), generates color images that are similar in performance to sequential illumination at three wavelengths, and therefore improves the speed of holographic color imaging by 3-fold. D-PSR method is broadly applicable to holographic microscopy applications, where high-resolution imaging and multi-wavelength illumination are desired. PMID:27353242

Comparison of lossless compression techniques for prepress color images

NASA Astrophysics Data System (ADS)

Van Assche, Steven; Denecker, Koen N.; Philips, Wilfried R.; Lemahieu, Ignace L.

1998-12-01

In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. In this paper we present a comparison of three state-of-the-art lossless compression techniques which exploit such color redundancies: IEP (Inter- color Error Prediction) and a KLT-based technique, which are both linear color decorrelation techniques, and Interframe CALIC, which uses a non-linear approach to color decorrelation. It is shown that these techniques are able to exploit color redundancies and that color decorrelation can be done effectively and efficiently. The linear color decorrelators provide a considerable coding gain (about 2 bpp) on some typical prepress images. The non-linear interframe CALIC predictor does not yield better results, but the full interframe CALIC technique does.

Virtual Antiparticle Pairs, the Unit of Charge Epsilon and the QCD Coupling Alpha(sub s)

NASA Technical Reports Server (NTRS)

Batchelor, David

2001-01-01

New semi-classical models of virtual antiparticle pairs are used to compute the pair lifetimes, and good agreement with the Heisenberg lifetimes from quantum field theory (QFT) is found. When the results of the new models and QFT are combined, formulae for e and alpha(sub s)(q) are derived in terms of only h and c. The modeling method applies to both the electromagnetic and color forces. Evaluation of the action integral of potential field fluctuation for each interaction potential yields approx. = h/2 for both electromagnetic and color fluctuations, in agreement with QFT. Thus each model is a quantized semiclassical representation for such virtual antiparticle pairs, to good approximation. This work reduces the number of arbitrary parameters of the Standard Model by two from 18 to 16. These are remarkable, unexpected results from a basically classical method.

A study of glasses-type color CGH using a color filter considering reduction of blurring

NASA Astrophysics Data System (ADS)

Iwami, Saki; Sakamoto, Yuji

2009-02-01

We have developed a glasses-type color computer generated hologram (CGH) by using a color filter. The proposed glasses consist of two "lenses" made of overlapping holograms and color filters. The holograms, which are calculated to reconstruct images in each primary color, are divided to small areas, which we called cells, and superimposed on one hologram. In the same way, colors of the filter correspond to the hologram cells. We can configure it very simply without a complex optical system, and the configuration yields a small and light weight system suitable for glasses. When the cell is small enough, the colors are mixed and reconstructed color images are observed. In addition, color expression of reconstruction images improves, too. However, using small cells blurrs reconstructed images because of the following reasons: (1) interference between cells because of the correlation with the cells, and (2) reduction of resolution caused by the size of the cell hologram. We are investigating in order to make a hologram that has high resolution reconstructed color images without ghost images. In this paper, we discuss (1) the details of the proposed glasses-type color CGH, (2) appropriate cell size for an eye system, (3) effects of cell shape on the reconstructed images, and (4) a new method to reduce the blurring of the images.

A robust color image fusion for low light level and infrared images

NASA Astrophysics Data System (ADS)

Liu, Chao; Zhang, Xiao-hui; Hu, Qing-ping; Chen, Yong-kang

2016-09-01

The low light level and infrared color fusion technology has achieved great success in the field of night vision, the technology is designed to make the hot target of fused image pop out with intenser colors, represent the background details with a nearest color appearance to nature, and improve the ability in target discovery, detection and identification. The low light level images have great noise under low illumination, and that the existing color fusion methods are easily to be influenced by low light level channel noise. To be explicit, when the low light level image noise is very large, the quality of the fused image decreases significantly, and even targets in infrared image would be submerged by the noise. This paper proposes an adaptive color night vision technology, the noise evaluation parameters of low light level image is introduced into fusion process, which improve the robustness of the color fusion. The color fuse results are still very good in low-light situations, which shows that this method can effectively improve the quality of low light level and infrared fused image under low illumination conditions.

Luminance contours can gate afterimage colors and "real" colors.

PubMed

Anstis, Stuart; Vergeer, Mark; Van Lier, Rob

2012-09-06

It has long been known that colored images may elicit afterimages in complementary colors. We have already shown (Van Lier, Vergeer, & Anstis, 2009) that one and the same adapting image may result in different afterimage colors, depending on the test contours presented after the colored image. The color of the afterimage depends on two adapting colors, those both inside and outside the test. Here, we further explore this phenomenon and show that the color-contour interactions shown for afterimage colors also occur for "real" colors. We argue that similar mechanisms apply for both types of stimulation.

Application of passive imaging polarimetry in the discrimination and detection of different color targets of identical shapes using color-blind imaging sensors

NASA Astrophysics Data System (ADS)

El-Saba, A. M.; Alam, M. S.; Surpanani, A.

2006-05-01

Important aspects of automatic pattern recognition systems are their ability to efficiently discriminate and detect proper targets with low false alarms. In this paper we extend the applications of passive imaging polarimetry to effectively discriminate and detect different color targets of identical shapes using color-blind imaging sensor. For this case of study we demonstrate that traditional color-blind polarization-insensitive imaging sensors that rely only on the spatial distribution of targets suffer from high false detection rates, especially in scenarios where multiple identical shape targets are present. On the other hand we show that color-blind polarization-sensitive imaging sensors can successfully and efficiently discriminate and detect true targets based on their color only. We highlight the main advantages of using our proposed polarization-encoded imaging sensor.

Lightness modification of color image for protanopia and deuteranopia

NASA Astrophysics Data System (ADS)

Tanaka, Go; Suetake, Noriaki; Uchino, Eiji

2010-01-01

In multimedia content, colors play important roles in conveying visual information. However, color information cannot always be perceived uniformly by all people. People with a color vision deficiency, such as dichromacy, cannot recognize and distinguish certain color combinations. In this paper, an effective lightness modification method, which enables barrier-free color vision for people with dichromacy, especially protanopia or deuteranopia, while preserving the color information in the original image for people with standard color vision, is proposed. In the proposed method, an optimization problem concerning lightness components is first defined by considering color differences in an input image. Then a perceptible and comprehensible color image for both protanopes and viewers with no color vision deficiency or both deuteranopes and viewers with no color vision deficiency is obtained by solving the optimization problem. Through experiments, the effectiveness of the proposed method is illustrated.

Quantifying nonhomogeneous colors in agricultural materials part I: method development.

PubMed

Balaban, M O

2008-11-01

Measuring the color of food and agricultural materials using machine vision (MV) has advantages not available by other measurement methods such as subjective tests or use of color meters. The perception of consumers may be affected by the nonuniformity of colors. For relatively uniform colors, average color values similar to those given by color meters can be obtained by MV. For nonuniform colors, various image analysis methods (color blocks, contours, and "color change index"[CCI]) can be applied to images obtained by MV. The degree of nonuniformity can be quantified, depending on the level of detail desired. In this article, the development of the CCI concept is presented. For images with a wide range of hue values, the color blocks method quantifies well the nonhomogeneity of colors. For images with a narrow hue range, the CCI method is a better indicator of color nonhomogeneity.

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

Kimpe, T; Marchessoux, C; Rostang, J

Purpose: Use of color images in medical imaging has increased significantly the last few years. As of today there is no agreed standard on how color information needs to be visualized on medical color displays, resulting into large variability of color appearance and it making consistency and quality assurance a challenge. This paper presents a proposal for an extension of DICOM GSDF towards color. Methods: Visualization needs for several color modalities (multimodality imaging, nuclear medicine, digital pathology, quantitative imaging applications…) have been studied. On this basis a proposal was made for desired color behavior of color medical display systems andmore » its behavior and effect on color medical images was analyzed. Results: Several medical color modalities could benefit from perceptually linear color visualization for similar reasons as why GSDF was put in place for greyscale medical images. An extension of the GSDF (Greyscale Standard Display Function) to color is proposed: CSDF (color standard display function). CSDF is based on deltaE2000 and offers a perceptually linear color behavior. CSDF uses GSDF as its neutral grey behavior. A comparison between sRGB/GSDF and CSDF confirms that CSDF significantly improves perceptual color linearity. Furthermore, results also indicate that because of the improved perceptual linearity, CSDF has the potential to increase perceived contrast of clinically relevant color features. Conclusion: There is a need for an extension of GSDF towards color visualization in order to guarantee consistency and quality. A first proposal (CSDF) for such extension has been made. Behavior of a CSDF calibrated display has been characterized and compared with sRGB/GSDF behavior. First results indicate that CSDF could have a positive influence on perceived contrast of clinically relevant color features and could offer benefits for quantitative imaging applications. Authors are employees of Barco Healthcare.« less

Color transfer method preserving perceived lightness

NASA Astrophysics Data System (ADS)

Ueda, Chiaki; Azetsu, Tadahiro; Suetake, Noriaki; Uchino, Eiji

2016-06-01

Color transfer originally proposed by Reinhard et al. is a method to change the color appearance of an input image by using the color information of a reference image. The purpose of this study is to modify color transfer so that it works well even when the scenes of the input and reference images are not similar. Concretely, a color transfer method with lightness correction and color gamut adjustment is proposed. The lightness correction is applied to preserve the perceived lightness which is explained by the Helmholtz-Kohlrausch (H-K) effect. This effect is the phenomenon that vivid colors are perceived as brighter than dull colors with the same lightness. Hence, when the chroma is changed by image processing, the perceived lightness is also changed even if the physical lightness is preserved after the image processing. In the proposed method, by considering the H-K effect, color transfer that preserves the perceived lightness after processing is realized. Furthermore, color gamut adjustment is introduced to address the color gamut problem, which is caused by color space conversion. The effectiveness of the proposed method is verified by performing some experiments.

The Constancy of Colored After-Images

PubMed Central

Zeki, Semir; Cheadle, Samuel; Pepper, Joshua; Mylonas, Dimitris

2017-01-01

We undertook psychophysical experiments to determine whether the color of the after-image produced by viewing a colored patch which is part of a complex multi-colored scene depends on the wavelength-energy composition of the light reflected from that patch. Our results show that it does not. The after-image, just like the color itself, depends on the ratio of light of different wavebands reflected from it and its surrounds. Hence, traditional accounts of after-images as being the result of retinal adaptation or the perceptual result of physiological opponency, are inadequate. We propose instead that the color of after-images is generated after colors themselves are generated in the visual brain. PMID:28539878

Image and Video Compression with VLSI Neural Networks

NASA Technical Reports Server (NTRS)

Fang, W.; Sheu, B.

1993-01-01

An advanced motion-compensated predictive video compression system based on artificial neural networks has been developed to effectively eliminate the temporal and spatial redundancy of video image sequences and thus reduce the bandwidth and storage required for the transmission and recording of the video signal. The VLSI neuroprocessor for high-speed high-ratio image compression based upon a self-organization network and the conventional algorithm for vector quantization are compared. The proposed method is quite efficient and can achieve near-optimal results.

Estimation of color modification in digital images by CFA pattern change.

PubMed

Choi, Chang-Hee; Lee, Hae-Yeoun; Lee, Heung-Kyu

2013-03-10

Extensive studies have been carried out for detecting image forgery such as copy-move, re-sampling, blurring, and contrast enhancement. Although color modification is a common forgery technique, there is no reported forensic method for detecting this type of manipulation. In this paper, we propose a novel algorithm for estimating color modification in images acquired from digital cameras when the images are modified. Most commercial digital cameras are equipped with a color filter array (CFA) for acquiring the color information of each pixel. As a result, the images acquired from such digital cameras include a trace from the CFA pattern. This pattern is composed of the basic red green blue (RGB) colors, and it is changed when color modification is carried out on the image. We designed an advanced intermediate value counting method for measuring the change in the CFA pattern and estimating the extent of color modification. The proposed method is verified experimentally by using 10,366 test images. The results confirmed the ability of the proposed method to estimate color modification with high accuracy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

A new apparatus for studies of quantized vortex dynamics in dilute-gas Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Newman, Zachary L.

The presence of quantized vortices and a high level of control over trap geometries and other system parameters make dilute-gas Bose-Einstein condensates (BECs) a natural environment for studies of vortex dynamics and quantum turbulence in superfluids, primary interests of the BEC group at the University of Arizona. Such research may lead to deeper understanding of the nature of quantum fluid dynamics and far-from-equilbrium phenomena. Despite the importance of quantized vortex dynamics in the fields of superfluidity, superconductivity and quantum turbulence, direct imaging of vortices in trapped BECs remains a significant technical challenge. This is primarily due to the small size of the vortex core in a trapped gas, which is typically a few hundred nanometers in diameter. In this dissertation I present the design and construction of a new 87Rb BEC apparatus with the goal of studying vortex dynamics in trapped BECs. The heart of the apparatus is a compact vacuum chamber with a custom, all-glass science cell designed to accommodate the use of commercial high-numerical-aperture microscope objectives for in situ imaging of vortices. The designs for the new system are, in part, based on prior work in our group on in situ imaging of vortices. Here I review aspects of our prior work and discuss some of the successes and limitations that are relevant to the new apparatus. The bulk of the thesis is used to described the major subsystems of the new apparatus which include the vacuum chamber, the laser systems, the magnetic transfer system and the final magnetic trap for the atoms. Finally, I demonstrate the creation of a BEC of ˜ 2 x 106 87Rb atoms in our new system and show that the BEC can be transferred into a weak, spherical, magnetic trap with a well defined magnetic field axis that may be useful for future vortex imaging studies.

Recognition memory for colored and black-and-white scenes in normal and color deficient observers (dichromats).

PubMed

Brédart, Serge; Cornet, Alyssa; Rakic, Jean-Marie

2014-01-01

Color deficient (dichromat) and normal observers' recognition memory for colored and black-and-white natural scenes was evaluated through several parameters: the rate of recognition, discrimination (A'), response bias (B"D), response confidence, and the proportion of conscious recollections (Remember responses) among hits. At the encoding phase, 36 images of natural scenes were each presented for 1 sec. Half of the images were shown in color and half in black-and-white. At the recognition phase, these 36 pictures were intermixed with 36 new images. The participants' task was to indicate whether an image had been presented or not at the encoding phase, to rate their level of confidence in his her/his response, and in the case of a positive response, to classify the response as a Remember, a Know or a Guess response. Results indicated that accuracy, response discrimination, response bias and confidence ratings were higher for colored than for black-and-white images; this advantage for colored images was similar in both groups of participants. Rates of Remember responses were not higher for colored images than for black-and-white ones, whatever the group. However, interestingly, Remember responses were significantly more often based on color information for colored than for black-and-white images in normal observers only, not in dichromats.

South Polar Cap

NASA Technical Reports Server (NTRS)

2004-01-01

[figure removed for brevity, see original site]

Released 28 May 2004 This image was collected February 29, 2004 during the end of southern summer season. The local time at the location of the image was about 2 pm. The image shows an area in the South Polar region.

The THEMIS VIS camera is capable of capturing color images of the martian surface using its five different color filters. In this mode of operation, the spatial resolution and coverage of the image must be reduced to accommodate the additional data volume produced from the use of multiple filters. To make a color image, three of the five filter images (each in grayscale) are selected. Each is contrast enhanced and then converted to a red, green, or blue intensity image. These three images are then combined to produce a full color, single image. Because the THEMIS color filters don't span the full range of colors seen by the human eye, a color THEMIS image does not represent true color. Also, because each single-filter image is contrast enhanced before inclusion in the three-color image, the apparent color variation of the scene is exaggerated. Nevertheless, the color variation that does appear is representative of some change in color, however subtle, in the actual scene. Note that the long edges of THEMIS color images typically contain color artifacts that do not represent surface variation.

Image information: VIS instrument. Latitude -84.7, Longitude 9.3 East (350.7 West). 38 meter/pixel resolution.

Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.

NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.

A novel false color mapping model-based fusion method of visual and infrared images

NASA Astrophysics Data System (ADS)

Qi, Bin; Kun, Gao; Tian, Yue-xin; Zhu, Zhen-yu

2013-12-01

A fast and efficient image fusion method is presented to generate near-natural colors from panchromatic visual and thermal imaging sensors. Firstly, a set of daytime color reference images are analyzed and the false color mapping principle is proposed according to human's visual and emotional habits. That is, object colors should remain invariant after color mapping operations, differences between infrared and visual images should be enhanced and the background color should be consistent with the main scene content. Then a novel nonlinear color mapping model is given by introducing the geometric average value of the input visual and infrared image gray and the weighted average algorithm. To determine the control parameters in the mapping model, the boundary conditions are listed according to the mapping principle above. Fusion experiments show that the new fusion method can achieve the near-natural appearance of the fused image, and has the features of enhancing color contrasts and highlighting the infrared brilliant objects when comparing with the traditional TNO algorithm. Moreover, it owns the low complexity and is easy to realize real-time processing. So it is quite suitable for the nighttime imaging apparatus.

Visual wetness perception based on image color statistics.

PubMed

Sawayama, Masataka; Adelson, Edward H; Nishida, Shin'ya

2017-05-01

Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage). However, we argue that color vision can inform us about much more than color alone. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color can help us recognize complex material qualities. Here we show that human vision uses color statistics of an image for the perception of an ecologically important surface condition (i.e., wetness). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tended to make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation, is consistent with actual optical changes produced by surface wetting. Furthermore, we found that the wetness enhancing transformation operator was more effective for the images with many colors (large hue entropy) than for those with few colors (small hue entropy). The hue entropy may be used to separate surface wetness from other surface states having similar optical properties. While surface wetness and surface color might seem to be independent, there are higher order color statistics that can influence wetness judgments, in accord with the ecological statistics. The present findings indicate that the visual system uses color image statistics in an elegant way to help estimate the complex physical status of a scene.

Color Sparse Representations for Image Processing: Review, Models, and Prospects.

PubMed

Barthélemy, Quentin; Larue, Anthony; Mars, Jérôme I

2015-11-01

Sparse representations have been extended to deal with color images composed of three channels. A review of dictionary-learning-based sparse representations for color images is made here, detailing the differences between the models, and comparing their results on the real and simulated data. These models are considered in a unifying framework that is based on the degrees of freedom of the linear filtering/transformation of the color channels. Moreover, this allows it to be shown that the scalar quaternionic linear model is equivalent to constrained matrix-based color filtering, which highlights the filtering implicitly applied through this model. Based on this reformulation, the new color filtering model is introduced, using unconstrained filters. In this model, spatial morphologies of color images are encoded by atoms, and colors are encoded by color filters. Color variability is no longer captured in increasing the dictionary size, but with color filters, this gives an efficient color representation.

Specialized Color Targets for Spectral Reflectance Reconstruction of Magnified Images

NASA Astrophysics Data System (ADS)

Kruschwitz, Jennifer D. T.

Digital images are used almost exclusively instead of film to capture visual information across many scientific fields. The colorimetric color representation within these digital images can be relayed from the digital counts produced by the camera with the use of a known color target. In image capture of magnified images, there is currently no reliable color target that can be used at multiple magnifications and give the user a solid understanding of the color ground truth within those images. The first part of this dissertation included the design, fabrication, and testing of a color target produced with optical interference coated microlenses for use in an off-axis illumination, compound microscope. An ideal target was designed to increase the color gamut for colorimetric imaging and provide the necessary "Block Dye" spectral reflectance profiles across the visible spectrum to reduce the number of color patches necessary for multiple filter imaging systems that rely on statistical models for spectral reflectance reconstruction. There are other scientific disciplines that can benefit from a specialized color target to determine the color ground truth in their magnified images and perform spectral estimation. Not every discipline has the luxury of having a multi-filter imaging system. The second part of this dissertation developed two unique ways of using an interference coated color mirror target: one that relies on multiple light-source angles, and one that leverages a dynamic color change with time. The source multi-angle technique would be used for the microelectronic discipline where the reconstructed spectral reflectance would be used to determine a dielectric film thickness on a silicon substrate, and the time varying technique would be used for a biomedical example to determine the thickness of human tear film.

Chern Numbers Hiding in Time of Flight Images

NASA Astrophysics Data System (ADS)

Satija, Indubala; Zhao, Erhai; Ghosh, Parag; Bray-Ali, Noah

2011-03-01

Since the experimental realization of synthetic magnetic fields in neural ultracold atoms, transport measurement such as quantized Hall conductivity remains an open challenge. Here we propose a novel and feasible scheme to measure the topological invariants, namely the chern numbers, in the time of flight images. We study both the commensurate and the incommensurate flux, with the later being the main focus here. The central concept underlying our proposal is the mapping between the chern numbers and the size of the dimerized states that emerge when the two-dimensional hopping is tuned to the highly anisotropic limit. In a uncoupled double quantum Hall system exhibiting time reversal invariance, only odd-sized dimer correlation functions are non-zero and hence encode quantized spin current. Finally, we illustrate that inspite of highly fragmented spectrum, a finite set of chern numbers are meaningful. Our results are supported by direct numerical computation of transverse conductivity. NBA acknowledges support from a National Research Council postdoctoral research associateship.

Quantitative Evaluation of Surface Color of Tomato Fruits Cultivated in Remote Farm Using Digital Camera Images

NASA Astrophysics Data System (ADS)

Hashimoto, Atsushi; Suehara, Ken-Ichiro; Kameoka, Takaharu

To measure the quantitative surface color information of agricultural products with the ambient information during cultivation, a color calibration method for digital camera images and a remote monitoring system of color imaging using the Web were developed. Single-lens reflex and web digital cameras were used for the image acquisitions. The tomato images through the post-ripening process were taken by the digital camera in both the standard image acquisition system and in the field conditions from the morning to evening. Several kinds of images were acquired with the standard RGB color chart set up just behind the tomato fruit on a black matte, and a color calibration was carried out. The influence of the sunlight could be experimentally eliminated, and the calibrated color information consistently agreed with the standard ones acquired in the system through the post-ripening process. Furthermore, the surface color change of the tomato on the tree in a greenhouse was remotely monitored during maturation using the digital cameras equipped with the Field Server. The acquired digital color images were sent from the Farm Station to the BIFE Laboratory of Mie University via VPN. The time behavior of the tomato surface color change during the maturing process could be measured using the color parameter calculated based on the obtained and calibrated color images along with the ambient atmospheric record. This study is a very important step in developing the surface color analysis for both the simple and rapid evaluation of the crop vigor in the field and to construct an ambient and networked remote monitoring system for food security, precision agriculture, and agricultural research.

The Artist, the Color Copier, and Digital Imaging.

ERIC Educational Resources Information Center

Witte, Mary Stieglitz

The impact that color-copying technology and digital imaging have had on art, photography, and design are explored. Color copiers have provided new opportunities for direct and spontaneous image making an the potential for new transformations in art. The current generation of digital color copiers permits new directions in imaging, but the…

Chemistry of the Konica Dry Color System

NASA Astrophysics Data System (ADS)

Suda, Yoshihiko; Ohbayashi, Keiji; Onodera, Kaoru

1991-08-01

While silver halide photosensitive materials offer superiority in image quality -- both in color and black-and-white -- they require chemical solutions for processing, and this can be a drawback. To overcome this, researchers turned to the thermal development of silver halide photographic materials, and met their first success with black-and-white images. Later, with the development of the Konica Dry Color System, color images were finally obtained from a completely dry thermal development system, without the use of water or chemical solutions. The dry color system is characterized by a novel chromogenic color image-forming technology and comprises four processes. (1) With the application of heat, a color developer precursor (CDP) decomposes to generate a p-phenylenediamine color developer (CD). (2) The CD then develops silver salts. (3) Oxidized CD then reacts with couplers to generate color image dyes. (4) Finally, the dyes diffuse from the system's photosensitive sheet to its image-receiving sheet. The authors have analyzed the kinetics of each of the system's four processes. In this paper, they report the kinetics of the system's first process, color developer (CD) generation.

Image Classification of Ribbed Smoked Sheet using Learning Vector Quantization

NASA Astrophysics Data System (ADS)

Rahmat, R. F.; Pulungan, A. F.; Faza, S.; Budiarto, R.

2017-01-01

Natural rubber is an important export commodity in Indonesia, which can be a major contributor to national economic development. One type of rubber used as rubber material exports is Ribbed Smoked Sheet (RSS). The quantity of RSS exports depends on the quality of RSS. RSS rubber quality has been assigned in SNI 06-001-1987 and the International Standards of Quality and Packing for Natural Rubber Grades (The Green Book). The determination of RSS quality is also known as the sorting process. In the rubber factones, the sorting process is still done manually by looking and detecting at the levels of air bubbles on the surface of the rubber sheet by naked eyes so that the result is subjective and not so good. Therefore, a method is required to classify RSS rubber automatically and precisely. We propose some image processing techniques for the pre-processing, zoning method for feature extraction and Learning Vector Quantization (LVQ) method for classifying RSS rubber into two grades, namely RSS1 and RSS3. We used 120 RSS images as training dataset and 60 RSS images as testing dataset. The result shows that our proposed method can give 89% of accuracy and the best perform epoch is in the fifteenth epoch.

Chromatic Modulator for High Resolution CCD or APS Devices

NASA Technical Reports Server (NTRS)

Hartley, Frank T. (Inventor); Hull, Anthony B. (Inventor)

2003-01-01

A system for providing high-resolution color separation in electronic imaging. Comb drives controllably oscillate a red-green-blue (RGB) color strip filter system (or otherwise) over an electronic imaging system such as a charge-coupled device (CCD) or active pixel sensor (APS). The color filter is modulated over the imaging array at a rate three or more times the frame rate of the imaging array. In so doing, the underlying active imaging elements are then able to detect separate color-separated images, which are then combined to provide a color-accurate frame which is then recorded as the representation of the recorded image. High pixel resolution is maintained. Registration is obtained between the color strip filter and the underlying imaging array through the use of electrostatic comb drives in conjunction with a spring suspension system.

A review of color blindness for microscopists: guidelines and tools for accommodating and coping with color vision deficiency.

PubMed

Keene, Douglas R

2015-04-01

"Color blindness" is a variable trait, including individuals with just slight color vision deficiency to those rare individuals with a complete lack of color perception. Approximately 75% of those with color impairment are green diminished; most of those remaining are red diminished. Red-Green color impairment is sex linked with the vast majority being male. The deficiency results in reds and greens being perceived as shades of yellow; therefore red-green images presented to the public will not illustrate regions of distinction to these individuals. Tools are available to authors wishing to accommodate those with color vision deficiency; most notable are components in FIJI (an extension of ImageJ) and Adobe Photoshop. Using these tools, hues of magenta may be substituted for red in red-green images resulting in striking definition for both the color sighted and color impaired. Web-based tools may be used (importantly) by color challenged individuals to convert red-green images archived in web-accessible journal articles into two-color images, which they may then discern.

A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2015-07-01

In digital histopathology, tasks of segmentation and disease diagnosis are achieved by quantitative analysis of image content. However, color variation in image samples makes it challenging to produce reliable results. This paper introduces a complete normalization scheme to address the problem of color variation in histopathology images jointly caused by inconsistent biopsy staining and nonstandard imaging condition. Method : Different from existing normalization methods that either address partial cause of color variation or lump them together, our method identifies causes of color variation based on a microscopic imaging model and addresses inconsistency in biopsy imaging and staining by an illuminant normalization module and a spectral normalization module, respectively. In evaluation, we use two public datasets that are representative of histopathology images commonly received in clinics to examine the proposed method from the aspects of robustness to system settings, performance consistency against achromatic pixels, and normalization effectiveness in terms of histological information preservation. As the saturation-weighted statistics proposed in this study generates stable and reliable color cues for stain normalization, our scheme is robust to system parameters and insensitive to image content and achromatic colors. Extensive experimentation suggests that our approach outperforms state-of-the-art normalization methods as the proposed method is the only approach that succeeds to preserve histological information after normalization. The proposed color normalization solution would be useful to mitigate effects of color variation in pathology images on subsequent quantitative analysis.

Graphics-Printing Program For The HP Paintjet Printer

NASA Technical Reports Server (NTRS)

Atkins, Victor R.

1993-01-01

IMPRINT utility computer program developed to print graphics specified in raster files by use of Hewlett-Packard Paintjet(TM) color printer. Reads bit-mapped images from files on UNIX-based graphics workstation and prints out three different types of images: wire-frame images, solid-color images, and gray-scale images. Wire-frame images are in continuous tone or, in case of low resolution, in random gray scale. In case of color images, IMPRINT also prints by use of default palette of solid colors. Written in C language.

Earth and Moon as viewed from Mars

NASA Technical Reports Server (NTRS)

2003-01-01

MGS MOC Release No. MOC2-368, 22 May 2003

[figure removed for brevity, see original site] Globe diagram illustrates the Earth's orientation as viewed from Mars (North and South America were in view).

Earth/Moon: This is the first image of Earth ever taken from another planet that actually shows our home as a planetary disk. Because Earth and the Moon are closer to the Sun than Mars, they exhibit phases, just as the Moon, Venus, and Mercury do when viewed from Earth. As seen from Mars by MGS on 8 May 2003 at 13:00 GMT (6:00 AM PDT), Earth and the Moon appeared in the evening sky. The MOC Earth/Moon image has been specially processed to allow both Earth (with an apparent magnitude of -2.5) and the much darker Moon (with an apparent magnitude of +0.9) to be visible together. The bright area at the top of the image of Earth is cloud cover over central and eastern North America. Below that, a darker area includes Central America and the Gulf of Mexico. The bright feature near the center-right of the crescent Earth consists of clouds over northern South America. The image also shows the Earth-facing hemisphere of the Moon, since the Moon was on the far side of Earth as viewed from Mars. The slightly lighter tone of the lower portion of the image of the Moon results from the large and conspicuous ray system associated with the crater Tycho.

A note about the coloring process: The MGS MOC high resolution camera only takes grayscale (black-and-white) images. To 'colorize' the image, a Mariner 10 Earth/Moon image taken in 1973 was used to color the MOC Earth and Moon picture. The procedure used was as follows: the Mariner 10 image was converted from 24-bit color to 8-bit color using a JPEG to GIF conversion program. The 8-bit color image was converted to 8-bit grayscale and an associated lookup table mapping each gray value of the image to a red-green-blue color triplet (RGB). Each color triplet was root-sum-squared (RSS), and sorted in increasing RSS value. These sorted lists were brightness-to-color maps for the images. Each brightness-to-color map was then used to convert the 8-bit grayscale MOC image to an 8-bit color image. This 8-bit color image was then converted to a 24-bit color image. The color image was edited to return the background to black.

A multispectral photon-counting double random phase encoding scheme for image authentication.

PubMed

Yi, Faliu; Moon, Inkyu; Lee, Yeon H

2014-05-20

In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI) and double random phase encoding (DRPE) schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color) in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

Memory-efficient decoding of LDPC codes

NASA Technical Reports Server (NTRS)

Kwok-San Lee, Jason; Thorpe, Jeremy; Hawkins, Jon

2005-01-01

We present a low-complexity quantization scheme for the implementation of regular (3,6) LDPC codes. The quantization parameters are optimized to maximize the mutual information between the source and the quantized messages. Using this non-uniform quantized belief propagation algorithm, we have simulated that an optimized 3-bit quantizer operates with 0.2dB implementation loss relative to a floating point decoder, and an optimized 4-bit quantizer operates less than 0.1dB quantization loss.

Color enhancement and image defogging in HSI based on Retinex model

NASA Astrophysics Data System (ADS)

Gao, Han; Wei, Ping; Ke, Jun

2015-08-01

Retinex is a luminance perceptual algorithm based on color consistency. It has a good performance in color enhancement. But in some cases, the traditional Retinex algorithms, both Single-Scale Retinex(SSR) and Multi-Scale Retinex(MSR) in RGB color space, do not work well and will cause color deviation. To solve this problem, we present improved SSR and MSR algorithms. Compared to other Retinex algorithms, we implement Retinex algorithms in HSI(Hue, Saturation, Intensity) color space, and use a parameter αto improve quality of the image. Moreover, the algorithms presented in this paper has a good performance in image defogging. Contrasted with traditional Retinex algorithms, we use intensity channel to obtain reflection information of an image. The intensity channel is processed using a Gaussian center-surround image filter to get light information, which should be removed from intensity channel. After that, we subtract the light information from intensity channel to obtain the reflection image, which only includes the attribute of the objects in image. Using the reflection image and a parameter α, which is an arbitrary scale factor set manually, we improve the intensity channel, and complete the color enhancement. Our experiments show that this approach works well compared with existing methods for color enhancement. Besides a better performance in color deviation problem and image defogging, a visible improvement in the image quality for human contrast perception is also observed.

Detecting double compressed MPEG videos with the same quantization matrix and synchronized group of pictures structure

NASA Astrophysics Data System (ADS)

Aghamaleki, Javad Abbasi; Behrad, Alireza

2018-01-01

Double compression detection is a crucial stage in digital image and video forensics. However, the detection of double compressed videos is challenging when the video forger uses the same quantization matrix and synchronized group of pictures (GOP) structure during the recompression history to conceal tampering effects. A passive approach is proposed for detecting double compressed MPEG videos with the same quantization matrix and synchronized GOP structure. To devise the proposed algorithm, the effects of recompression on P frames are mathematically studied. Then, based on the obtained guidelines, a feature vector is proposed to detect double compressed frames on the GOP level. Subsequently, sparse representations of the feature vectors are used for dimensionality reduction and enrich the traces of recompression. Finally, a support vector machine classifier is employed to detect and localize double compression in temporal domain. The experimental results show that the proposed algorithm achieves the accuracy of more than 95%. In addition, the comparisons of the results of the proposed method with those of other methods reveal the efficiency of the proposed algorithm.

Melas Chasma - False Color

NASA Image and Video Library

2015-10-08

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of the floor of Melas Chasma. The dark blue region in this false color image is sand dunes. Orbit Number: 12061 Latitude: -12.2215 Longitude: 289.105 Instrument: VIS Captured: 2004-09-02 10:11 http://photojournal.jpl.nasa.gov/catalog/PIA19793

Calibration Image of Earth by Mars Color Imager

NASA Technical Reports Server (NTRS)

2005-01-01

Three days after the Mars Reconnaissance Orbiter's Aug. 12, 2005, launch, the NASA spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of color and ultraviolet images of Earth and the Moon. When it gets to Mars, the Mars Color Imager's main objective will be to obtain daily global color and ultraviolet images of the planet to observe martian meteorology by documenting the occurrence of dust storms, clouds, and ozone. This camera will also observe how the martian surface changes over time, including changes in frost patterns and surface brightness caused by dust storms and dust devils.

The purpose of acquiring an image of Earth and the Moon just three days after launch was to help the Mars Color Imager science team obtain a measure, in space, of the instrument's sensitivity, as well as to check that no contamination occurred on the camera during launch. Prior to launch, the team determined that, three days out from Earth, the planet would only be about 4.77 pixels across, and the Moon would be less than one pixel in size, as seen from the Mars Color Imager's wide-angle perspective. If the team waited any longer than three days to test the camera's performance in space, Earth would be too small to obtain meaningful results.

The images were acquired by turning Mars Reconnaissance Orbiter toward Earth, then slewing the spacecraft so that the Earth and Moon would pass before each of the five color and two ultraviolet filters of the Mars Color Imager. The distance to Earth was about 1,170,000 kilometers (about 727,000 miles).

This image shows a color composite view of Mars Color Imager's image of Earth. As expected, it covers only five pixels. This color view has been enlarged five times. The Sun was illuminating our planet from the left, thus only one quarter of Earth is seen from this perspective. North America was in daylight and facing toward the camera at the time the picture was taken; the data from the camera were being transmitted in real time to the Deep Space Network antennas in Goldstone, California.

New false color mapping for image fusion

NASA Astrophysics Data System (ADS)

Toet, Alexander; Walraven, Jan

1996-03-01

A pixel-based color-mapping algorithm is presented that produces a fused false color rendering of two gray-level images representing different sensor modalities. The resulting images have a higher information content than each of the original images and retain sensor-specific image information. The unique component of each image modality is enhanced in the resulting fused color image representation. First, the common component of the two original input images is determined. Second, the common component is subtracted from the original images to obtain the unique component of each image. Third, the unique component of each image modality is subtracted from the image of the other modality. This step serves to enhance the representation of sensor-specific details in the final fused result. Finally, a fused color image is produced by displaying the images resulting from the last step through, respectively, the red and green channels of a color display. The method is applied to fuse thermal and visual images. The results show that the color mapping enhances the visibility of certain details and preserves the specificity of the sensor information. The fused images also have a fairly natural appearance. The fusion scheme involves only operations on corresponding pixels. The resolution of a fused image is therefore directly related to the resolution of the input images. Before fusing, the contrast of the images can be enhanced and their noise can be reduced by standard image- processing techniques. The color mapping algorithm is computationally simple. This implies that the investigated approaches can eventually be applied in real time and that the hardware needed is not too complicated or too voluminous (an important consideration when it has to fit in an airplane, for instance).

Quantifying the effect of colorization enhancement on mammogram images

NASA Astrophysics Data System (ADS)

Wojnicki, Paul J.; Uyeda, Elizabeth; Micheli-Tzanakou, Evangelia

2002-04-01

Current methods of radiological displays provide only grayscale images of mammograms. The limitation of the image space to grayscale provides only luminance differences and textures as cues for object recognition within the image. However, color can be an important and significant cue in the detection of shapes and objects. Increasing detection ability allows the radiologist to interpret the images in more detail, improving object recognition and diagnostic accuracy. Color detection experiments using our stimulus system, have demonstrated that an observer can only detect an average of 140 levels of grayscale. An optimally colorized image can allow a user to distinguish 250 - 1000 different levels, hence increasing potential image feature detection by 2-7 times. By implementing a colorization map, which follows the luminance map of the original grayscale images, the luminance profile is preserved and color is isolated as the enhancement mechanism. The effect of this enhancement mechanism on the shape, frequency composition and statistical characteristics of the Visual Evoked Potential (VEP) are analyzed and presented. Thus, the effectiveness of the image colorization is measured quantitatively using the Visual Evoked Potential (VEP).

True color blood flow imaging using a high-speed laser photography system

NASA Astrophysics Data System (ADS)

Liu, Chien-Sheng; Lin, Cheng-Hsien; Sun, Yung-Nien; Ho, Chung-Liang; Hsu, Chung-Chi

2012-10-01

Physiological changes in the retinal vasculature are commonly indicative of such disorders as diabetic retinopathy, glaucoma, and age-related macular degeneration. Thus, various methods have been developed for noninvasive clinical evaluation of ocular hemodynamics. However, to the best of our knowledge, current ophthalmic instruments do not provide a true color blood flow imaging capability. Accordingly, we propose a new method for the true color imaging of blood flow using a high-speed pulsed laser photography system. In the proposed approach, monochromatic images of the blood flow are acquired using a system of three cameras and three color lasers (red, green, and blue). A high-quality true color image of the blood flow is obtained by assembling the monochromatic images by means of image realignment and color calibration processes. The effectiveness of the proposed approach is demonstrated by imaging the flow of mouse blood within a microfluidic channel device. The experimental results confirm the proposed system provides a high-quality true color blood flow imaging capability, and therefore has potential for noninvasive clinical evaluation of ocular hemodynamics.

Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Liu, Ti C.; Mitra, Sunanda

1996-06-01

Image compression plays a crucial role in many important and diverse applications requiring efficient storage and transmission. This work mainly focuses on a wavelet transform (WT) based compression of fingerprint images and the subsequent classification of the reconstructed images. The algorithm developed involves multiresolution wavelet decomposition, uniform scalar quantization, entropy and run- length encoder/decoder and K-means clustering of the invariant moments as fingerprint features. The performance of the WT-based compression algorithm has been compared with JPEG current image compression standard. Simulation results show that WT outperforms JPEG in high compression ratio region and the reconstructed fingerprint image yields proper classification.

Improvement to the scanning electron microscope image adaptive Canny optimization colorization by pseudo-mapping.

PubMed

Lo, T Y; Sim, K S; Tso, C P; Nia, M E

2014-01-01

An improvement to the previously proposed adaptive Canny optimization technique for scanning electron microscope image colorization is reported. The additional feature, called pseudo-mapping technique, is that the grayscale markings are temporarily mapped to a set of pre-defined pseudo-color map as a mean to instill color information for grayscale colors in chrominance channels. This allows the presence of grayscale markings to be identified; hence optimization colorization of grayscale colors is made possible. This additional feature enhances the flexibility of scanning electron microscope image colorization by providing wider range of possible color enhancement. Furthermore, the nature of this technique also allows users to adjust the luminance intensities of selected region from the original image within certain extent. © 2014 Wiley Periodicals, Inc.

[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

PubMed

Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

2015-06-01

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Full-color high-definition CGH reconstructing hybrid scenes of physical and virtual objects

NASA Astrophysics Data System (ADS)

Tsuchiyama, Yasuhiro; Matsushima, Kyoji; Nakahara, Sumio; Yamaguchi, Masahiro; Sakamoto, Yuji

2017-03-01

High-definition CGHs can reconstruct high-quality 3D images that are comparable to that in conventional optical holography. However, it was difficult to exhibit full-color images reconstructed by these high-definition CGHs, because three CGHs for RGB colors and a bulky image combiner were needed to produce full-color images. Recently, we reported a novel technique for full-color reconstruction using RGB color filters, which are similar to that used for liquid-crystal panels. This technique allows us to produce full-color high-definition CGHs composed of a single plate and place them on exhibition. By using the technique, we demonstrate full-color CGHs that reconstruct hybrid scenes comprised of real-existing physical objects and CG-modeled virtual objects in this paper. Here, the wave field of the physical object are obtained from dense multi-viewpoint images by employing the ray-sampling (RS) plane technique. In addition to the technique for full-color capturing and reconstruction of real object fields, the principle and simulation technique for full- color CGHs using RGB color filters are presented.

Quantum Color Image Encryption Algorithm Based on A Hyper-Chaotic System and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Tan, Ru-Chao; Lei, Tong; Zhao, Qing-Min; Gong, Li-Hua; Zhou, Zhi-Hong

2016-12-01

To improve the slow processing speed of the classical image encryption algorithms and enhance the security of the private color images, a new quantum color image encryption algorithm based on a hyper-chaotic system is proposed, in which the sequences generated by the Chen's hyper-chaotic system are scrambled and diffused with three components of the original color image. Sequentially, the quantum Fourier transform is exploited to fulfill the encryption. Numerical simulations show that the presented quantum color image encryption algorithm possesses large key space to resist illegal attacks, sensitive dependence on initial keys, uniform distribution of gray values for the encrypted image and weak correlation between two adjacent pixels in the cipher-image.

A natural-color mapping for single-band night-time image based on FPGA

NASA Astrophysics Data System (ADS)

Wang, Yilun; Qian, Yunsheng

2018-01-01

A natural-color mapping for single-band night-time image method based on FPGA can transmit the color of the reference image to single-band night-time image, which is consistent with human visual habits and can help observers identify the target. This paper introduces the processing of the natural-color mapping algorithm based on FPGA. Firstly, the image can be transformed based on histogram equalization, and the intensity features and standard deviation features of reference image are stored in SRAM. Then, the real-time digital images' intensity features and standard deviation features are calculated by FPGA. At last, FPGA completes the color mapping through matching pixels between images using the features in luminance channel.

Astronomy with the color blind

NASA Astrophysics Data System (ADS)

Smith, Donald A.; Melrose, Justyn

2014-12-01

The standard method to create dramatic color images in astrophotography is to record multiple black and white images, each with a different color filter in the optical path, and then tint each frame with a color appropriate to the corresponding filter. When combined, the resulting image conveys information about the sources of emission in the field, although one should be cautious in assuming that such an image shows what the subject would "really look like" if a person could see it without the aid of a telescope. The details of how the eye processes light have a significant impact on how such images should be understood, and the step from perception to interpretation is even more problematic when the viewer is color blind. We report here on an approach to manipulating stacked tricolor images that, while abandoning attempts to portray the color distribution "realistically," do result in enabling those suffering from deuteranomaly (the most common form of color blindness) to perceive color distinctions they would otherwise not be able to see.

Accurate color synthesis of three-dimensional objects in an image

NASA Astrophysics Data System (ADS)

Xin, John H.; Shen, Hui-Liang

2004-05-01

Our study deals with color synthesis of a three-dimensional object in an image; i.e., given a single image, a target color can be accurately mapped onto the object such that the color appearance of the synthesized object closely resembles that of the actual one. As it is almost impossible to acquire the complete geometric description of the surfaces of an object in an image, this study attempted to recover the implicit description of geometry for the color synthesis. The description was obtained from either a series of spectral reflectances or the RGB signals at different surface positions on the basis of the dichromatic reflection model. The experimental results showed that this implicit image-based representation is related to the object geometry and is sufficient for accurate color synthesis of three-dimensional objects in an image. The method established is applicable to the color synthesis of both rigid and deformable objects and should contribute to color fidelity in virtual design, manufacturing, and retailing.

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images

PubMed Central

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K.; Schad, Lothar R.; Zöllner, Frank Gerrit

2015-01-01

Background Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. Methods and Results In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin—3,3’-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. Validation To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Context Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics. PMID:26717571

New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

PubMed

Kather, Jakob Nikolas; Weis, Cleo-Aron; Marx, Alexander; Schuster, Alexander K; Schad, Lothar R; Zöllner, Frank Gerrit

2015-01-01

Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions. In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images. To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images. Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.

Color model comparative analysis for breast cancer diagnosis using H and E stained images

NASA Astrophysics Data System (ADS)

Li, Xingyu; Plataniotis, Konstantinos N.

2015-03-01

Digital cancer diagnosis is a research realm where signal processing techniques are used to analyze and to classify color histopathology images. Different from grayscale image analysis of magnetic resonance imaging or X-ray, colors in histopathology images convey large amount of histological information and thus play significant role in cancer diagnosis. Though color information is widely used in histopathology works, as today, there is few study on color model selections for feature extraction in cancer diagnosis schemes. This paper addresses the problem of color space selection for digital cancer classification using H and E stained images, and investigates the effectiveness of various color models (RGB, HSV, CIE L*a*b*, and stain-dependent H and E decomposition model) in breast cancer diagnosis. Particularly, we build a diagnosis framework as a comparison benchmark and take specific concerns of medical decision systems into account in evaluation. The evaluation methodologies include feature discriminate power evaluation and final diagnosis performance comparison. Experimentation on a publicly accessible histopathology image set suggests that the H and E decomposition model outperforms other assessed color spaces. For reasons behind various performance of color spaces, our analysis via mutual information estimation demonstrates that color components in the H and E model are less dependent, and thus most feature discriminate power is collected in one channel instead of spreading out among channels in other color spaces.

Hepatitis Diagnosis Using Facial Color Image

NASA Astrophysics Data System (ADS)

Liu, Mingjia; Guo, Zhenhua

Facial color diagnosis is an important diagnostic method in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experi-ence-based nature, traditional facial color diagnosis has a very limited application in clinical medicine. To circumvent the subjective and qualitative problems of facial color diagnosis of Traditional Chinese Medicine, in this paper, we present a novel computer aided facial color diagnosis method (CAFCDM). The method has three parts: face Image Database, Image Preprocessing Module and Diagnosis Engine. Face Image Database is carried out on a group of 116 patients affected by 2 kinds of liver diseases and 29 healthy volunteers. The quantitative color feature is extracted from facial images by using popular digital image processing techni-ques. Then, KNN classifier is employed to model the relationship between the quantitative color feature and diseases. The results show that the method can properly identify three groups: healthy, severe hepatitis with jaundice and severe hepatitis without jaundice with accuracy higher than 73%.

Spatial transform coding of color images.

NASA Technical Reports Server (NTRS)

Pratt, W. K.

1971-01-01

The application of the transform-coding concept to the coding of color images represented by three primary color planes of data is discussed. The principles of spatial transform coding are reviewed and the merits of various methods of color-image representation are examined. A performance analysis is presented for the color-image transform-coding system. Results of a computer simulation of the coding system are also given. It is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation. If luminance coding is also employed, the average rate reduces to about 2.0 bits per element or less.

Color engineering in the age of digital convergence

NASA Astrophysics Data System (ADS)

MacDonald, Lindsay W.

1998-09-01

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

Efficient color correction method for smartphone camera-based health monitoring application.

PubMed

Duc Dang; Chae Ho Cho; Daeik Kim; Oh Seok Kwon; Jo Woon Chong

2017-07-01

Smartphone health monitoring applications are recently highlighted due to the rapid development of hardware and software performance of smartphones. However, color characteristics of images captured by different smartphone models are dissimilar each other and this difference may give non-identical health monitoring results when the smartphone health monitoring applications monitor physiological information using their embedded smartphone cameras. In this paper, we investigate the differences in color properties of the captured images from different smartphone models and apply a color correction method to adjust dissimilar color values obtained from different smartphone cameras. Experimental results show that the color corrected images using the correction method provide much smaller color intensity errors compared to the images without correction. These results can be applied to enhance the consistency of smartphone camera-based health monitoring applications by reducing color intensity errors among the images obtained from different smartphones.

Restoration of motion blurred images

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking †

PubMed Central

Kiku, Daisuke; Okutomi, Masatoshi

2017-01-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. PMID:29194407

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

PubMed

Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

2017-12-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

Spatial imaging in color and HDR: prometheus unchained

NASA Astrophysics Data System (ADS)

McCann, John J.

2013-03-01

The Human Vision and Electronic Imaging Conferences (HVEI) at the IS and T/SPIE Electronic Imaging meetings have brought together research in the fundamentals of both vision and digital technology. This conference has incorporated many color disciplines that have contributed to the theory and practice of today's imaging: color constancy, models of vision, digital output, high-dynamic-range imaging, and the understanding of perceptual mechanisms. Before digital imaging, silver halide color was a pixel-based mechanism. Color films are closely tied to colorimetry, the science of matching pixels in a black surround. The quanta catch of the sensitized silver salts determines the amount of colored dyes in the final print. The rapid expansion of digital imaging over the past 25 years has eliminated the limitations of using small local regions in forming images. Spatial interactions can now generate images more like vision. Since the 1950's, neurophysiology has shown that post-receptor neural processing is based on spatial interactions. These results reinforced the findings of 19th century experimental psychology. This paper reviews the role of HVEI in color, emphasizing the interaction of research on vision and the new algorithms and processes made possible by electronic imaging.

Image analysis of skin color heterogeneity focusing on skin chromophores and the age-related changes in facial skin.

PubMed

Kikuchi, Kumiko; Masuda, Yuji; Yamashita, Toyonobu; Kawai, Eriko; Hirao, Tetsuji

2015-05-01

Heterogeneity with respect to skin color tone is one of the key factors in visual perception of facial attractiveness and age. However, there have been few studies on quantitative analyses of the color heterogeneity of facial skin. The purpose of this study was to develop image evaluation methods for skin color heterogeneity focusing on skin chromophores and then characterize ethnic differences and age-related changes. A facial imaging system equipped with an illumination unit and a high-resolution digital camera was used to develop image evaluation methods for skin color heterogeneity. First, melanin and/or hemoglobin images were obtained using pigment-specific image-processing techniques, which involved conversion from Commission Internationale de l'Eclairage XYZ color values to melanin and/or hemoglobin indexes as measures of their contents. Second, a spatial frequency analysis with threshold settings was applied to the individual images. Cheek skin images of 194 healthy Asian and Caucasian female subjects were acquired using the imaging system. Applying this methodology, the skin color heterogeneity of Asian and Caucasian faces was characterized. The proposed pigment-specific image-processing techniques allowed visual discrimination of skin redness from skin pigmentation. In the heterogeneity analyses of cheek skin color, age-related changes in melanin were clearly detected in Asian and Caucasian skin. Furthermore, it was found that the heterogeneity indexes of hemoglobin were significantly higher in Caucasian skin than in Asian skin. We have developed evaluation methods for skin color heterogeneity by image analyses based on the major chromophores, melanin and hemoglobin, with special reference to their size. This methodology focusing on skin color heterogeneity should be useful for better understanding of aging and ethnic differences. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

High-chroma visual cryptography using interference color of high-order retarder films

NASA Astrophysics Data System (ADS)

Sugawara, Shiori; Harada, Kenji; Sakai, Daisuke

2015-08-01

Visual cryptography can be used as a method of sharing a secret image through several encrypted images. Conventional visual cryptography can display only monochrome images. We have developed a high-chroma color visual encryption technique using the interference color of high-order retarder films. The encrypted films are composed of a polarizing film and retarder films. The retarder films exhibit interference color when they are sandwiched between two polarizing films. We propose a stacking technique for displaying high-chroma interference color images. A prototype visual cryptography device using high-chroma interference color is developed.

High-intensity focused ultrasound ablation assisted using color Doppler imaging for the treatment of hepatocellular carcinomas.

PubMed

Fukuda, Hiroyuki; Numata, Kazushi; Nozaki, Akito; Kondo, Masaaki; Morimoto, Manabu; Maeda, Shin; Tanaka, Katsuaki; Ohto, Masao; Ito, Ryu; Ishibashi, Yoshiharu; Oshima, Noriyoshi; Ito, Ayao; Zhu, Hui; Wang, Zhi-Biao

2013-12-01

We evaluated the usefulness of color Doppler flow imaging to compensate for the inadequate resolution of the ultrasound (US) monitoring during high-intensity focused ultrasound (HIFU) for the treatment of hepatocellular carcinoma (HCC). US-guided HIFU ablation assisted using color Doppler flow imaging was performed in 11 patients with small HCC (<3 lesions, <3 cm in diameter). The HIFU system (Chongqing Haifu Tech) was used under US guidance. Color Doppler sonographic studies were performed using an HIFU 6150S US imaging unit system and a 2.7-MHz electronic convex probe. The color Doppler images were used because of the influence of multi-reflections and the emergence of hyperecho. In 1 of the 11 patients, multi-reflections were responsible for the poor visualization of the tumor. In 10 cases, the tumor was poorly visualized because of the emergence of a hyperecho. In these cases, the ability to identify the original tumor location on the monitor by referencing the color Doppler images of the portal vein and the hepatic vein was very useful. HIFU treatments were successfully performed in all 11 patients with the assistance of color Doppler imaging. Color Doppler imaging is useful for the treatment of HCC using HIFU, compensating for the occasionally poor visualization provided by B-mode conventional US imaging.

Calibration Image of Earth by Mars Color Imager

NASA Image and Video Library

2005-08-22

Three days after the Mars Reconnaissance Orbiter Aug. 12, 2005, launch, the NASA spacecraft was pointed toward Earth and the Mars Color Imager camera was powered up to acquire a suite of color and ultraviolet images of Earth and the Moon.

Gale Crater - False Color

NASA Image and Video Library

2017-02-15

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of Gale Crater. Basaltic sands are dark blue in this type of false color combination. The Curiosity Rover is located in another portion of Gale Crater, far southwest of this image. Orbit Number: 51803 Latitude: -4.39948 Longitude: 138.116 Instrument: VIS Captured: 2013-08-18 09:04 http://photojournal.jpl.nasa.gov/catalog/PIA21312

Adaptive enhancement for nonuniform illumination images via nonlinear mapping

NASA Astrophysics Data System (ADS)

Wang, Yanfang; Huang, Qian; Hu, Jing

2017-09-01

Nonuniform illumination images suffer from degenerated details because of underexposure, overexposure, or a combination of both. To improve the visual quality of color images, underexposure regions should be lightened, whereas overexposure areas need to be dimmed properly. However, discriminating between underexposure and overexposure is troublesome. Compared with traditional methods that produce a fixed demarcation value throughout an image, the proposed demarcation changes as local luminance varies, thus is suitable for manipulating complicated illumination. Based on this locally adaptive demarcation, a nonlinear modification is applied to image luminance. Further, with the modified luminance, we propose a nonlinear process to reconstruct a luminance-enhanced color image. For every pixel, this nonlinear process takes the luminance change and the original chromaticity into account, thus trying to avoid exaggerated colors at dark areas and depressed colors at highly bright regions. Finally, to improve image contrast, a local and image-dependent exponential technique is designed and applied to the RGB channels of the obtained color image. Experimental results demonstrate that our method produces good contrast and vivid color for both nonuniform illumination images and images with normal illumination.

Object knowledge changes visual appearance: semantic effects on color afterimages.

PubMed

Lupyan, Gary

2015-10-01

According to predictive coding models of perception, what we see is determined jointly by the current input and the priors established by previous experience, expectations, and other contextual factors. The same input can thus be perceived differently depending on the priors that are brought to bear during viewing. Here, I show that expected (diagnostic) colors are perceived more vividly than arbitrary or unexpected colors, particularly when color input is unreliable. Participants were tested on a version of the 'Spanish Castle Illusion' in which viewing a hue-inverted image renders a subsequently shown achromatic version of the image in vivid color. Adapting to objects with intrinsic colors (e.g., a pumpkin) led to stronger afterimages than adapting to arbitrarily colored objects (e.g., a pumpkin-colored car). Considerably stronger afterimages were also produced by scenes containing intrinsically colored elements (grass, sky) compared to scenes with arbitrarily colored objects (books). The differences between images with diagnostic and arbitrary colors disappeared when the association between the image and color priors was weakened by, e.g., presenting the image upside-down, consistent with the prediction that color appearance is being modulated by color knowledge. Visual inputs that conflict with prior knowledge appear to be phenomenologically discounted, but this discounting is moderated by input certainty, as shown by the final study which uses conventional images rather than afterimages. As input certainty is increased, unexpected colors can become easier to detect than expected ones, a result consistent with predictive-coding models. Copyright © 2015 Elsevier B.V. All rights reserved.

78 FR 18611 - Summit on Color in Medical Imaging; Cosponsored Public Workshop; Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-27

...] Summit on Color in Medical Imaging; Cosponsored Public Workshop; Request for Comments AGENCY: Food and...: The Food and Drug Administration (FDA) and cosponsor International Color Consortium (ICC) are announcing the following public workshop entitled ``Summit on Color in Medical Imaging: An International...

The Role of Color and Morphologic Characteristics in Dermoscopic Diagnosis.

PubMed

Bajaj, Shirin; Marchetti, Michael A; Navarrete-Dechent, Cristian; Dusza, Stephen W; Kose, Kivanc; Marghoob, Ashfaq A

2016-06-01

Both colors and structures are considered important in the dermoscopic evaluation of skin lesions but their relative significance is unknown. To determine if diagnostic accuracy for common skin lesions differs between gray-scale and color dermoscopic images. A convenience sample of 40 skin lesions (8 nevi, 8 seborrheic keratoses, 7 basal cell carcinomas, 7 melanomas, 4 hemangiomas, 4 dermatofibromas, 2 squamous cell carcinomas [SCCs]) was selected and shown to attendees of a dermoscopy course (2014 Memorial Sloan Kettering Cancer Center dermoscopy course). Twenty lesions were shown only once, either in gray-scale (n = 10) or color (n = 10) (nonpaired). Twenty lesions were shown twice, once in gray-scale (n = 20) and once in color (n = 20) (paired). Participants provided their diagnosis and confidence level for each of the 60 images. Of the 261 attendees, 158 participated (60.5%) in the study. Most were attending physicians (n = 76 [48.1%]). Most participants were practicing or training in dermatology (n = 144 [91.1%]). The median (interquartile range) experience evaluating skin lesions and using dermoscopy of participants was 6 (13.5) and 2 (4.0) years, respectively. Diagnostic accuracy and confidence level of participants evaluating gray-scale and color images. Two separate analyses were performed: (1) an unpaired evaluation comparing gray-scale and color images shown either once or for the first time, and (2) a paired evaluation comparing pairs of gray-scale and color images of the same lesion. In univariate analysis of unpaired images, color images were less likely to be diagnosed correctly compared with gray-scale images (odds ratio [OR], 0.8; P < .001). Using gray-scale images as the reference, multivariate analyses of both unpaired and paired images found no association between correct lesion diagnosis and use of color images (OR, 1.0; P = .99, and OR, 1.2; P = .82, respectively). Stratified analysis of paired images using a color by diagnosis interaction term showed that participants were more likely to make a correct diagnosis of SCC and hemangioma in color (P < .001 for both comparisons) and dermatofibroma in gray-scale (P < .001). Morphologic characteristics (ie, structures and patterns), not color, provide the primary diagnostic clue in dermoscopy. Use of gray-scale images may improve teaching of dermoscopy to novices by emphasizing the evaluation of morphology.

[Design and Implementation of Image Interpolation and Color Correction for Ultra-thin Electronic Endoscope on FPGA].

PubMed

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.

What's color got to do with it? The influence of color on visual attention in different categories.

PubMed

Frey, Hans-Peter; Honey, Christian; König, Peter

2008-10-23

Certain locations attract human gaze in natural visual scenes. Are there measurable features, which distinguish these locations from others? While there has been extensive research on luminance-defined features, only few studies have examined the influence of color on overt attention. In this study, we addressed this question by presenting color-calibrated stimuli and analyzing color features that are known to be relevant for the responses of LGN neurons. We recorded eye movements of 15 human subjects freely viewing colored and grayscale images of seven different categories. All images were also analyzed by the saliency map model (L. Itti, C. Koch, & E. Niebur, 1998). We find that human fixation locations differ between colored and grayscale versions of the same image much more than predicted by the saliency map. Examining the influence of various color features on overt attention, we find two extreme categories: while in rainforest images all color features are salient, none is salient in fractals. In all other categories, color features are selectively salient. This shows that the influence of color on overt attention depends on the type of image. Also, it is crucial to analyze neurophysiologically relevant color features for quantifying the influence of color on attention.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Effective method for detecting regions of given colors and the features of the region surfaces

NASA Astrophysics Data System (ADS)

Gong, Yihong; Zhang, HongJiang

1994-03-01

Color can be used as a very important cue for image recognition. In industrial and commercial areas, color is widely used as a trademark or identifying feature in objects, such as packaged goods, advertising signs, etc. In image database systems, one may retrieve an image of interest by specifying prominent colors and their locations in the image (image retrieval by contents). These facts enable us to detect or identify a target object using colors. However, this task depends mainly on how effectively we can identify a color and detect regions of the given color under possibly non-uniform illumination conditions such as shade, highlight, and strong contrast. In this paper, we present an effective method to detect regions matching given colors, along with the features of the region surfaces. We adopt the HVC color coordinates in the method because of its ability of completely separating the luminant and chromatic components of colors. Three basis functions functionally serving as the low-pass, high-pass, and band-pass filters, respectively, are introduced.

Color standardization and optimization in whole slide imaging.

PubMed

Yagi, Yukako

2011-03-30

Standardization and validation of the color displayed by digital slides is an important aspect of digital pathology implementation. While the most common reason for color variation is the variance in the protocols and practices in the histology lab, the color displayed can also be affected by variation in capture parameters (for example, illumination and filters), image processing and display factors in the digital systems themselves. We have been developing techniques for color validation and optimization along two paths. The first was based on two standard slides that are scanned and displayed by the imaging system in question. In this approach, one slide is embedded with nine filters with colors selected especially for H&E stained slides (looking like tiny Macbeth color chart); the specific color of the nine filters were determined in our previous study and modified for whole slide imaging (WSI). The other slide is an H&E stained mouse embryo. Both of these slides were scanned and the displayed images were compared to a standard. The second approach was based on our previous multispectral imaging research. As a first step, the two slide method (above) was used to identify inaccurate display of color and its cause, and to understand the importance of accurate color in digital pathology. We have also improved the multispectral-based algorithm for more consistent results in stain standardization. In near future, the results of the two slide and multispectral techniques can be combined and will be widely available. We have been conducting a series of researches and developing projects to improve image quality to establish Image Quality Standardization. This paper discusses one of most important aspects of image quality - color.

Medical Image Compression Using a New Subband Coding Method

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen; Tucker, Doug

1995-01-01

A recently introduced iterative complexity- and entropy-constrained subband quantization design algorithm is generalized and applied to medical image compression. In particular, the corresponding subband coder is used to encode Computed Tomography (CT) axial slice head images, where statistical dependencies between neighboring image subbands are exploited. Inter-slice conditioning is also employed for further improvements in compression performance. The subband coder features many advantages such as relatively low complexity and operation over a very wide range of bit rates. Experimental results demonstrate that the performance of the new subband coder is relatively good, both objectively and subjectively.

Research on image complexity evaluation method based on color information

NASA Astrophysics Data System (ADS)

Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

2017-11-01

In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment.

PubMed

Zhou, Mei; Jin, Kai; Wang, Shaoze; Ye, Juan; Qian, Dahong

2018-03-01

Many common eye diseases and cardiovascular diseases can be diagnosed through retinal imaging. However, due to uneven illumination, image blurring, and low contrast, retinal images with poor quality are not useful for diagnosis, especially in automated image analyzing systems. Here, we propose a new image enhancement method to improve color retinal image luminosity and contrast. A luminance gain matrix, which is obtained by gamma correction of the value channel in the HSV (hue, saturation, and value) color space, is used to enhance the R, G, and B (red, green and blue) channels, respectively. Contrast is then enhanced in the luminosity channel of L * a * b * color space by CLAHE (contrast-limited adaptive histogram equalization). Image enhancement by the proposed method is compared to other methods by evaluating quality scores of the enhanced images. The performance of the method is mainly validated on a dataset of 961 poor-quality retinal images. Quality assessment (range 0-1) of image enhancement of this poor dataset indicated that our method improved color retinal image quality from an average of 0.0404 (standard deviation 0.0291) up to an average of 0.4565 (standard deviation 0.1000). The proposed method is shown to achieve superior image enhancement compared to contrast enhancement in other color spaces or by other related methods, while simultaneously preserving image naturalness. This method of color retinal image enhancement may be employed to assist ophthalmologists in more efficient screening of retinal diseases and in development of improved automated image analysis for clinical diagnosis.

An Overview of High-Resolution, Non-Dispersive, Imaging Spectrometers for High-Energy Photons

NASA Technical Reports Server (NTRS)

Kilbourne, Caroline

2010-01-01

High-resolution x-ray spectroscopy has become a powerful tool for studying the evolving universe. The grating spectrometers on the XMM and Chandra satellites initiated a new era in x-ray astronomy. Despite their successes, there is still need for instrumentation that can provide higher spectral resolution with high throughput in the Fe-K band and for extended sources. What is needed is a non-dispersive imaging spectrometer - essentially a 14-bit x-ray color camera. And a requirement for a nondispersive spectrometer designed to provide eV-scale spectral resolution is a temperature below 0.1 K. The required spectral resolution and the constraints of thermodynamics and engineering dictate the temperature regime nearly independently of the details of the sensor or the read-out technology. Low-temperature spectrometers can be divided into two classes - - equilibrium and non-equilibrium. In the equilibrium devices, or calorimeters, the energy is deposited in an isolated thermal mass and the resulting increase in temperature is measured. In the non-equilibrium devices, the absorbed energy produces quantized excitations that are counted to determine the energy. The two approaches have different strong points, and within each class a variety of optimizations have been pursued. I will present the basic fundamentals of operation and the details of the most successful device designs to date. I will also discuss how the measurement priorities (resolution, energy band, count rate) influence the optimal choice of detector technology.

Quantitative characterization of color Doppler images: reproducibility, accuracy, and limitations.

PubMed

Delorme, S; Weisser, G; Zuna, I; Fein, M; Lorenz, A; van Kaick, G

1995-01-01

A computer-based quantitative analysis for color Doppler images of complex vascular formations is presented. The red-green-blue-signal from an Acuson XP10 is frame-grabbed and digitized. By matching each image pixel with the color bar, color pixels are identified and assigned to the corresponding flow velocity (color value). Data analysis consists of delineation of a region of interest and calculation of the relative number of color pixels in this region (color pixel density) as well as the mean color value. The mean color value was compared to flow velocities in a flow phantom. The thyroid and carotid artery in a volunteer were repeatedly examined by a single examiner to assess intra-observer variability. The thyroids in five healthy controls were examined by three experienced physicians to assess the extent of inter-observer variability and observer bias. The correlation between the mean color value and flow velocity ranged from 0.94 to 0.96 for a range of velocities determined by pulse repetition frequency. The average deviation of the mean color value from the flow velocity was 22% to 41%, depending on the selected pulse repetition frequency (range of deviations, -46% to +66%). Flow velocity was underestimated with inadequately low pulse repetition frequency, or inadequately high reject threshold. An overestimation occurred with inadequately high pulse repetition frequency. The highest intra-observer variability was 22% (relative standard deviation) for the color pixel density, and 9.1% for the mean color value. The inter-observer variation was approximately 30% for the color pixel density, and 20% for the mean color value. In conclusion, computer assisted image analysis permits an objective description of color Doppler images. However, the user must be aware that image acquisition under in vivo conditions as well as physical and instrumental factors may considerably influence the results.

Fusion of lens-free microscopy and mobile-phone microscopy images for high-color-accuracy and high-resolution pathology imaging

NASA Astrophysics Data System (ADS)

Zhang, Yibo; Wu, Yichen; Zhang, Yun; Ozcan, Aydogan

2017-03-01

Digital pathology and telepathology require imaging tools with high-throughput, high-resolution and accurate color reproduction. Lens-free on-chip microscopy based on digital in-line holography is a promising technique towards these needs, as it offers a wide field of view (FOV >20 mm2) and high resolution with a compact, low-cost and portable setup. Color imaging has been previously demonstrated by combining reconstructed images at three discrete wavelengths in the red, green and blue parts of the visible spectrum, i.e., the RGB combination method. However, this RGB combination method is subject to color distortions. To improve the color performance of lens-free microscopy for pathology imaging, here we present a wavelet-based color fusion imaging framework, termed "digital color fusion microscopy" (DCFM), which digitally fuses together a grayscale lens-free microscope image taken at a single wavelength and a low-resolution and low-magnification color-calibrated image taken by a lens-based microscope, which can simply be a mobile phone based cost-effective microscope. We show that the imaging results of an H&E stained breast cancer tissue slide with the DCFM technique come very close to a color-calibrated microscope using a 40x objective lens with 0.75 NA. Quantitative comparison showed 2-fold reduction in the mean color distance using the DCFM method compared to the RGB combination method, while also preserving the high-resolution features of the lens-free microscope. Due to the cost-effective and field-portable nature of both lens-free and mobile-phone microscopy techniques, their combination through the DCFM framework could be useful for digital pathology and telepathology applications, in low-resource and point-of-care settings.

Demosaiced pixel super-resolution in digital holography for multiplexed computational color imaging on-a-chip (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2017-03-01

Digital holographic on-chip microscopy achieves large space-bandwidth-products (e.g., >1 billion) by making use of pixel super-resolution techniques. To synthesize a digital holographic color image, one can take three sets of holograms representing the red (R), green (G) and blue (B) parts of the spectrum and digitally combine them to synthesize a color image. The data acquisition efficiency of this sequential illumination process can be improved by 3-fold using wavelength-multiplexed R, G and B illumination that simultaneously illuminates the sample, and using a Bayer color image sensor with known or calibrated transmission spectra to digitally demultiplex these three wavelength channels. This demultiplexing step is conventionally used with interpolation-based Bayer demosaicing methods. However, because the pixels of different color channels on a Bayer image sensor chip are not at the same physical location, conventional interpolation-based demosaicing process generates strong color artifacts, especially at rapidly oscillating hologram fringes, which become even more pronounced through digital wave propagation and phase retrieval processes. Here, we demonstrate that by merging the pixel super-resolution framework into the demultiplexing process, such color artifacts can be greatly suppressed. This novel technique, termed demosaiced pixel super-resolution (D-PSR) for digital holographic imaging, achieves very similar color imaging performance compared to conventional sequential R,G,B illumination, with 3-fold improvement in image acquisition time and data-efficiency. We successfully demonstrated the color imaging performance of this approach by imaging stained Pap smears. The D-PSR technique is broadly applicable to high-throughput, high-resolution digital holographic color microscopy techniques that can be used in resource-limited-settings and point-of-care offices.

Enhancement of low light level images using color-plus-mono dual camera.

PubMed

Jung, Yong Ju

2017-05-15

In digital photography, the improvement of imaging quality in low light shooting is one of the users' needs. Unfortunately, conventional smartphone cameras that use a single, small image sensor cannot provide satisfactory quality in low light level images. A color-plus-mono dual camera that consists of two horizontally separate image sensors, which simultaneously captures both a color and mono image pair of the same scene, could be useful for improving the quality of low light level images. However, an incorrect image fusion between the color and mono image pair could also have negative effects, such as the introduction of severe visual artifacts in the fused images. This paper proposes a selective image fusion technique that applies an adaptive guided filter-based denoising and selective detail transfer to only those pixels deemed reliable with respect to binocular image fusion. We employ a dissimilarity measure and binocular just-noticeable-difference (BJND) analysis to identify unreliable pixels that are likely to cause visual artifacts during image fusion via joint color image denoising and detail transfer from the mono image. By constructing an experimental system of color-plus-mono camera, we demonstrate that the BJND-aware denoising and selective detail transfer is helpful in improving the image quality during low light shooting.

Acceleration of color computer-generated hologram from three-dimensional scenes with texture and depth information

NASA Astrophysics Data System (ADS)

Shimobaba, Tomoyoshi; Kakue, Takashi; Ito, Tomoyoshi

2014-06-01

We propose acceleration of color computer-generated holograms (CGHs) from three-dimensional (3D) scenes that are expressed as texture (RGB) and depth (D) images. These images are obtained by 3D graphics libraries and RGB-D cameras: for example, OpenGL and Kinect, respectively. We can regard them as two-dimensional (2D) cross-sectional images along the depth direction. The generation of CGHs from the 2D cross-sectional images requires multiple diffraction calculations. If we use convolution-based diffraction such as the angular spectrum method, the diffraction calculation takes a long time and requires large memory usage because the convolution diffraction calculation requires the expansion of the 2D cross-sectional images to avoid the wraparound noise. In this paper, we first describe the acceleration of the diffraction calculation using "Band-limited double-step Fresnel diffraction," which does not require the expansion. Next, we describe color CGH acceleration using color space conversion. In general, color CGHs are generated on RGB color space; however, we need to repeat the same calculation for each color component, so that the computational burden of the color CGH generation increases three-fold, compared with monochrome CGH generation. We can reduce the computational burden by using YCbCr color space because the 2D cross-sectional images on YCbCr color space can be down-sampled without the impairing of the image quality.

Color normalization for robust evaluation of microscopy images

NASA Astrophysics Data System (ADS)

Švihlík, Jan; Kybic, Jan; Habart, David

2015-09-01

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either lαβ or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation.

Color constancy using bright-neutral pixels

NASA Astrophysics Data System (ADS)

Wang, Yanfang; Luo, Yupin

2014-03-01

An effective illuminant-estimation approach for color constancy is proposed. Bright and near-neutral pixels are selected to jointly represent the illuminant color and utilized for illuminant estimation. To assess the representing capability of pixels, bright-neutral strength (BNS) is proposed by combining pixel chroma and brightness. Accordingly, a certain percentage of pixels with the largest BNS is selected to be the representative set. For every input image, a proper percentage value is determined via an iterative strategy by seeking the optimal color-corrected image. To compare various color-corrected images of an input image, image color-cast degree (ICCD) is devised using means and standard deviations of RGB channels. Experimental evaluation on standard real-world datasets validates the effectiveness of the proposed approach.

Image Reconstruction for Hybrid True-Color Micro-CT

PubMed Central

Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

2013-01-01

X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid “true-color” micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose. PMID:22481806

Color transfer algorithm in medical images

NASA Astrophysics Data System (ADS)

Wang, Weihong; Xu, Yangfa

2007-12-01

In digital virtual human project, image data acquires from the freezing slice of human body specimen. The color and brightness between a group of images of a certain organ could be quite different. The quality of these images could bring great difficulty in edge extraction, segmentation, as well as 3D reconstruction process. Thus it is necessary to unify the color of the images. The color transfer algorithm is a good algorithm to deal with this kind of problem. This paper introduces the principle of this algorithm and uses it in the medical image processing.

A generalized Benford's law for JPEG coefficients and its applications in image forensics

NASA Astrophysics Data System (ADS)

Fu, Dongdong; Shi, Yun Q.; Su, Wei

2007-02-01

In this paper, a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients is presented. A parametric logarithmic law, i.e., the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics are discussed in this paper, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Qfactor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. The results of our extensive experiments demonstrate the effectiveness of the proposed statistical model.

Global Binary Continuity for Color Face Detection With Complex Background

NASA Astrophysics Data System (ADS)

Belavadi, Bhaskar; Mahendra Prashanth, K. V.; Joshi, Sujay S.; Suprathik, N.

2017-08-01

In this paper, we propose a method to detect human faces in color images, with complex background. The proposed algorithm makes use of basically two color space models, specifically HSV and YCgCr. The color segmented image is filled uniformly with a single color (binary) and then all unwanted discontinuous lines are removed to get the final image. Experimental results on Caltech database manifests that the purported model is able to accomplish far better segmentation for faces of varying orientations, skin color and background environment.

Superresolution with the focused plenoptic camera

NASA Astrophysics Data System (ADS)

Georgiev, Todor; Chunev, Georgi; Lumsdaine, Andrew

2011-03-01

Digital images from a CCD or CMOS sensor with a color filter array must undergo a demosaicing process to combine the separate color samples into a single color image. This interpolation process can interfere with the subsequent superresolution process. Plenoptic superresolution, which relies on precise sub-pixel sampling across captured microimages, is particularly sensitive to such resampling of the raw data. In this paper we present an approach for superresolving plenoptic images that takes place at the time of demosaicing the raw color image data. Our approach exploits the interleaving provided by typical color filter arrays (e.g., Bayer filter) to further refine plenoptic sub-pixel sampling. Our rendering algorithm treats the color channels in a plenoptic image separately, which improves final superresolution by a factor of two. With appropriate plenoptic capture we show the theoretical possibility for rendering final images at full sensor resolution.

Discriminative Projection Selection Based Face Image Hashing

NASA Astrophysics Data System (ADS)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Single underwater image enhancement based on color cast removal and visibility restoration

NASA Astrophysics Data System (ADS)

Li, Chongyi; Guo, Jichang; Wang, Bo; Cong, Runmin; Zhang, Yan; Wang, Jian

2016-05-01

Images taken under underwater condition usually have color cast and serious loss of contrast and visibility. Degraded underwater images are inconvenient for observation and analysis. In order to address these problems, an underwater image-enhancement method is proposed. A simple yet effective underwater image color cast removal algorithm is first presented based on the optimization theory. Then, based on the minimum information loss principle and inherent relationship of medium transmission maps of three color channels in an underwater image, an effective visibility restoration algorithm is proposed to recover visibility, contrast, and natural appearance of degraded underwater images. To evaluate the performance of the proposed method, qualitative comparison, quantitative comparison, and color accuracy test are conducted. Experimental results demonstrate that the proposed method can effectively remove color cast, improve contrast and visibility, and recover natural appearance of degraded underwater images. Additionally, the proposed method is comparable to and even better than several state-of-the-art methods.

Color correction optimization with hue regularization

NASA Astrophysics Data System (ADS)

Zhang, Heng; Liu, Huaping; Quan, Shuxue

2011-01-01

Previous work has suggested that observers are capable of judging the quality of an image without any knowledge of the original scene. When no reference is available, observers can extract the apparent objects in an image and compare them with the typical colors of similar objects recalled from their memories. Some generally agreed upon research results indicate that although perfect colorimetric rendering is not conspicuous and color errors can be well tolerated, the appropriate rendition of certain memory colors such as skin, grass, and sky is an important factor in the overall perceived image quality. These colors are appreciated in a fairly consistent manner and are memorized with slightly different hues and higher color saturation. The aim of color correction for a digital color pipeline is to transform the image data from a device dependent color space to a target color space, usually through a color correction matrix which in its most basic form is optimized through linear regressions between the two sets of data in two color spaces in the sense of minimized Euclidean color error. Unfortunately, this method could result in objectionable distortions if the color error biased certain colors undesirably. In this paper, we propose a color correction optimization method with preferred color reproduction in mind through hue regularization and present some experimental results.

Color calibration of swine gastrointestinal tract images acquired by radial imaging capsule endoscope

NASA Astrophysics Data System (ADS)

Ou-Yang, Mang; Jeng, Wei-De; Lai, Chien-Cheng; Wu, Hsien-Ming; Lin, Jyh-Hung

2016-01-01

The type of illumination systems and color filters used typically generate varying levels of color difference in capsule endoscopes, which influence medical diagnoses. In order to calibrate the color difference caused by the optical system, this study applied a radial imaging capsule endoscope (RICE) to photograph standard color charts, which were then employed to calculate the color gamut of RICE. Color gamut was also measured using a spectrometer in order to get a high-precision color information, and the results obtained using both methods were compared. Subsequently, color-correction methods, namely polynomial transform and conformal mapping, were used to improve the color difference. Before color calibration, the color difference value caused by the influences of optical systems in RICE was 21.45±1.09. Through the proposed polynomial transformation, the color difference could be reduced effectively to 1.53±0.07. Compared to another proposed conformal mapping, the color difference value was substantially reduced to 1.32±0.11, and the color difference is imperceptible for human eye because it is <1.5. Then, real-time color correction was achieved using this algorithm combined with a field-programmable gate array, and the results of the color correction can be viewed from real-time images.

Frequency division multiplexed multi-color fluorescence microscope system

NASA Astrophysics Data System (ADS)

Le, Vu Nam; Yang, Huai Dong; Zhang, Si Chun; Zhang, Xin Rong; Jin, Guo Fan

2017-10-01

Grayscale camera can only obtain gray scale image of object, while the multicolor imaging technology can obtain the color information to distinguish the sample structures which have the same shapes but in different colors. In fluorescence microscopy, the current method of multicolor imaging are flawed. Problem of these method is affecting the efficiency of fluorescence imaging, reducing the sampling rate of CCD etc. In this paper, we propose a novel multiple color fluorescence microscopy imaging method which based on the Frequency division multiplexing (FDM) technology, by modulating the excitation lights and demodulating the fluorescence signal in frequency domain. This method uses periodic functions with different frequency to modulate amplitude of each excitation lights, and then combine these beams for illumination in a fluorescence microscopy imaging system. The imaging system will detect a multicolor fluorescence image by a grayscale camera. During the data processing, the signal obtained by each pixel of the camera will be processed with discrete Fourier transform, decomposed by color in the frequency domain and then used inverse discrete Fourier transform. After using this process for signals from all of the pixels, monochrome images of each color on the image plane can be obtained and multicolor image is also acquired. Based on this method, this paper has constructed and set up a two-color fluorescence microscope system with two excitation wavelengths of 488 nm and 639 nm. By using this system to observe the linearly movement of two kinds of fluorescent microspheres, after the data processing, we obtain a two-color fluorescence dynamic video which is consistent with the original image. This experiment shows that the dynamic phenomenon of multicolor fluorescent biological samples can be generally observed by this method. Compared with the current methods, this method can obtain the image signals of each color at the same time, and the color video's frame rate is consistent with the frame rate of the camera. The optical system is simpler and does not need extra color separation element. In addition, this method has a good filtering effect on the ambient light or other light signals which are not affected by the modulation process.

CFA-aware features for steganalysis of color images

NASA Astrophysics Data System (ADS)

Goljan, Miroslav; Fridrich, Jessica

2015-03-01

Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

Citrus fruit recognition using color image analysis

NASA Astrophysics Data System (ADS)

Xu, Huirong; Ying, Yibin

2004-10-01

An algorithm for the automatic recognition of citrus fruit on the tree was developed. Citrus fruits have different color with leaves and branches portions. Fifty-three color images with natural citrus-grove scenes were digitized and analyzed for red, green, and blue (RGB) color content. The color characteristics of target surfaces (fruits, leaves, or branches) were extracted using the range of interest (ROI) tool. Several types of contrast color indices were designed and tested. In this study, the fruit image was enhanced using the (R-B) contrast color index because results show that the fruit have the highest color difference among the objects in the image. A dynamic threshold function was derived from this color model and used to distinguish citrus fruit from background. The results show that the algorithm worked well under frontlighting or backlighting condition. However, there are misclassifications when the fruit or the background is under a brighter sunlight.

An improved quantum watermarking scheme using small-scale quantum circuits and color scrambling

NASA Astrophysics Data System (ADS)

Li, Panchi; Zhao, Ya; Xiao, Hong; Cao, Maojun

2017-05-01

In order to solve the problem of embedding the watermark into the quantum color image, in this paper, an improved scheme of using small-scale quantum circuits and color scrambling is proposed. Both color carrier image and color watermark image are represented using novel enhanced quantum representation. The image sizes for carrier and watermark are assumed to be 2^{n+1}× 2^{n+2} and 2n× 2n, respectively. At first, the color of pixels in watermark image is scrambled using the controlled rotation gates, and then, the scrambled watermark with 2^n× 2^n image size and 24-qubit gray scale is expanded to an image with 2^{n+1}× 2^{n+2} image size and 3-qubit gray scale. Finally, the expanded watermark image is embedded into the carrier image by the controlled-NOT gates. The extraction of watermark is the reverse process of embedding it into carrier image, which is achieved by applying operations in the reverse order. Simulation-based experimental results show that the proposed scheme is superior to other similar algorithms in terms of three items, visual quality, scrambling effect of watermark image, and noise resistibility.

Astronomy with the Color Blind

ERIC Educational Resources Information Center

Smith, Donald A.; Melrose, Justyn

2014-01-01

The standard method to create dramatic color images in astrophotography is to record multiple black and white images, each with a different color filter in the optical path, and then tint each frame with a color appropriate to the corresponding filter. When combined, the resulting image conveys information about the sources of emission in the…

Applied learning-based color tone mapping for face recognition in video surveillance system

NASA Astrophysics Data System (ADS)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Color TV: total variation methods for restoration of vector-valued images.

PubMed

Blomgren, P; Chan, T F

1998-01-01

We propose a new definition of the total variation (TV) norm for vector-valued functions that can be applied to restore color and other vector-valued images. The new TV norm has the desirable properties of 1) not penalizing discontinuities (edges) in the image, 2) being rotationally invariant in the image space, and 3) reducing to the usual TV norm in the scalar case. Some numerical experiments on denoising simple color images in red-green-blue (RGB) color space are presented.

Digital color representation

DOEpatents

White, James M.; Faber, Vance; Saltzman, Jeffrey S.

1992-01-01

An image population having a large number of attributes is processed to form a display population with a predetermined smaller number of attributes which represent the larger number of attributes. In a particular application, the color values in an image are compressed for storage in a discrete lookup table (LUT) where an 8-bit data signal is enabled to form a display of 24-bit color values. The LUT is formed in a sampling and averaging process from the image color values with no requirement to define discrete Voronoi regions for color compression. Image color values are assigned 8-bit pointers to their closest LUT value whereby data processing requires only the 8-bit pointer value to provide 24-bit color values from the LUT.

Color preservation for tone reproduction and image enhancement

NASA Astrophysics Data System (ADS)

Hsin, Chengho; Lee, Zong Wei; Lee, Zheng Zhan; Shin, Shaw-Jyh

2014-01-01

Applications based on luminance processing often face the problem of recovering the original chrominance in the output color image. A common approach to reconstruct a color image from the luminance output is by preserving the original hue and saturation. However, this approach often produces a highly colorful image which is undesirable. We develop a color preservation method that not only retains the ratios of the input tri-chromatic values but also adjusts the output chroma in an appropriate way. Linearizing the output luminance is the key idea to realize this method. In addition, a lightness difference metric together with a colorfulness difference metric are proposed to evaluate the performance of the color preservation methods. It shows that the proposed method performs consistently better than the existing approaches.

Fusion of visible and near-infrared images based on luminance estimation by weighted luminance algorithm

NASA Astrophysics Data System (ADS)

Wang, Zhun; Cheng, Feiyan; Shi, Junsheng; Huang, Xiaoqiao

2018-01-01

In a low-light scene, capturing color images needs to be at a high-gain setting or a long-exposure setting to avoid a visible flash. However, such these setting will lead to color images with serious noise or motion blur. Several methods have been proposed to improve a noise-color image through an invisible near infrared flash image. A novel method is that the luminance component and the chroma component of the improved color image are estimated from different image sources [1]. The luminance component is estimated mainly from the NIR image via a spectral estimation, and the chroma component is estimated from the noise-color image by denoising. However, it is challenging to estimate the luminance component. This novel method to estimate the luminance component needs to generate the learning data pairs, and the processes and algorithm are complex. It is difficult to achieve practical application. In order to reduce the complexity of the luminance estimation, an improved luminance estimation algorithm is presented in this paper, which is to weight the NIR image and the denoised-color image and the weighted coefficients are based on the mean value and standard deviation of both images. Experimental results show that the same fusion effect at aspect of color fidelity and texture quality is achieved, compared the proposed method with the novel method, however, the algorithm is more simple and practical.

Color dithering methods for LEGO-like 3D printing

NASA Astrophysics Data System (ADS)

Sun, Pei-Li; Sie, Yuping

2015-01-01

Color dithering methods for LEGO-like 3D printing are proposed in this study. The first method is work for opaque color brick building. It is a modification of classic error diffusion. Many color primaries can be chosen. However, RGBYKW is recommended as its image quality is good and the number of color primary is limited. For translucent color bricks, multi-layer color building can enhance the image quality significantly. A LUT-based method is proposed to speed the dithering proceeding and make the color distribution even smoother. Simulation results show the proposed multi-layer dithering method can really improve the image quality of LEGO-like 3D printing.

Research of image retrieval technology based on color feature

NASA Astrophysics Data System (ADS)

Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

2009-10-01

Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram make rotating and translation does not change. The HSV color space is used to show color characteristic of image, which is suitable to the visual characteristic of human. Taking advance of human's feeling to color, it quantifies color sector with unequal interval, and get characteristic vector. Finally, it matches the similarity of image with the algorithm of the histogram intersection and the partition-overall histogram. Users can choose a demonstration image to show inquired vision require, and also can adjust several right value through the relevance-feedback method to obtain the best result of search.An image retrieval system based on these approaches is presented. The result of the experiments shows that the image retrieval based on partition-overall histogram can keep the space distribution information while abstracting color feature efficiently, and it is superior to the normal color histograms in precision rate while researching. The query precision rate is more than 95%. In addition, the efficient block expression will lower the complicate degree of the images to be searched, and thus the searching efficiency will be increased. The image retrieval algorithms based on the partition-overall histogram proposed in the paper is efficient and effective.

Guided color consistency optimization for image mosaicking

NASA Astrophysics Data System (ADS)

Xie, Renping; Xia, Menghan; Yao, Jian; Li, Li

2018-01-01

This paper studies the problem of color consistency correction for sequential images with diverse color characteristics. Existing algorithms try to adjust all images to minimize color differences among images under a unified energy framework, however, the results are prone to presenting a consistent but unnatural appearance when the color difference between images is large and diverse. In our approach, this problem is addressed effectively by providing a guided initial solution for the global consistency optimization, which avoids converging to a meaningless integrated solution. First of all, to obtain the reliable intensity correspondences in overlapping regions between image pairs, we creatively propose the histogram extreme point matching algorithm which is robust to image geometrical misalignment to some extents. In the absence of the extra reference information, the guided initial solution is learned from the major tone of the original images by searching some image subset as the reference, whose color characteristics will be transferred to the others via the paths of graph analysis. Thus, the final results via global adjustment will take on a consistent color similar to the appearance of the reference image subset. Several groups of convincing experiments on both the synthetic dataset and the challenging real ones sufficiently demonstrate that the proposed approach can achieve as good or even better results compared with the state-of-the-art approaches.

Reconstruction of color images via Haar wavelet based on digital micromirror device

NASA Astrophysics Data System (ADS)

Liu, Xingjiong; He, Weiji; Gu, Guohua

2015-10-01

A digital micro mirror device( DMD) is introduced to form Haar wavelet basis , projecting on the color target image by making use of structured illumination, including red, green and blue light. The light intensity signals reflected from the target image are received synchronously by the bucket detector which has no spatial resolution, converted into voltage signals and then transferred into PC[1] .To reach the aim of synchronization, several synchronization processes are added during data acquisition. In the data collection process, according to the wavelet tree structure, the locations of significant coefficients at the finer scale are predicted by comparing the coefficients sampled at the coarsest scale with the threshold. The monochrome grayscale images are obtained under red , green and blue structured illumination by using Haar wavelet inverse transform algorithm, respectively. The color fusion algorithm is carried on the three monochrome grayscale images to obtain the final color image. According to the imaging principle, the experimental demonstration device is assembled. The letter "K" and the X-rite Color Checker Passport are projected and reconstructed as target images, and the final reconstructed color images have good qualities. This article makes use of the method of Haar wavelet reconstruction, reducing the sampling rate considerably. It provides color information without compromising the resolution of the final image.

A 128×96 Pixel Stack-Type Color Image Sensor: Stack of Individual Blue-, Green-, and Red-Sensitive Organic Photoconductive Films Integrated with a ZnO Thin Film Transistor Readout Circuit

NASA Astrophysics Data System (ADS)

Seo, Hokuto; Aihara, Satoshi; Watabe, Toshihisa; Ohtake, Hiroshi; Sakai, Toshikatsu; Kubota, Misao; Egami, Norifumi; Hiramatsu, Takahiro; Matsuda, Tokiyoshi; Furuta, Mamoru; Hirao, Takashi

2011-02-01

A color image was produced by a vertically stacked image sensor with blue (B)-, green (G)-, and red (R)-sensitive organic photoconductive films, each having a thin-film transistor (TFT) array that uses a zinc oxide (ZnO) channel to read out the signal generated in each organic film. The number of the pixels of the fabricated image sensor is 128×96 for each color, and the pixel size is 100×100 µm2. The current on/off ratio of the ZnO TFT is over 106, and the B-, G-, and R-sensitive organic photoconductive films show excellent wavelength selectivity. The stacked image sensor can produce a color image at 10 frames per second with a resolution corresponding to the pixel number. This result clearly shows that color separation is achieved without using any conventional color separation optical system such as a color filter array or a prism.

Dehazed Image Quality Assessment by Haze-Line Theory

NASA Astrophysics Data System (ADS)

Song, Yingchao; Luo, Haibo; Lu, Rongrong; Ma, Junkai

2017-06-01

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

Scalable Inkjet-Based Structural Color Printing by Molding Transparent Gratings on Multilayer Nanostructured Surfaces.

PubMed

Jiang, Hao; Kaminska, Bozena

2018-04-24

To enable customized manufacturing of structural colors for commercial applications, up-scalable, low-cost, rapid, and versatile printing techniques are highly demanded. In this paper, we introduce a viable strategy for scaling up production of custom-input images by patterning individual structural colors on separate layers, which are then vertically stacked and recombined into full-color images. By applying this strategy on molded-ink-on-nanostructured-surface printing, we present an industry-applicable inkjet structural color printing technique termed multilayer molded-ink-on-nanostructured-surface (M-MIONS) printing, in which structural color pixels are molded on multiple layers of nanostructured surfaces. Transparent colorless titanium dioxide nanoparticles were inkjet-printed onto three separate transparent polymer substrates, and each substrate surface has one specific subwavelength grating pattern for molding the deposited nanoparticles into structural color pixels of red, green, or blue primary color. After index-matching lamination, the three layers were vertically stacked and bonded to display a color image. Each primary color can be printed into a range of different shades controlled through a half-tone process, and full colors were achieved by mixing primary colors from three layers. In our experiments, an image size as big as 10 cm by 10 cm was effortlessly achieved, and even larger images can potentially be printed on recombined grating surfaces. In one application example, the M-MIONS technique was used for printing customizable transparent color optical variable devices for protecting personalized security documents. In another example, a transparent diffractive color image printed with the M-MIONS technique was pasted onto a transparent panel for overlaying colorful information onto one's view of reality.

Structure-Preserving Color Normalization and Sparse Stain Separation for Histological Images.

PubMed

Vahadane, Abhishek; Peng, Tingying; Sethi, Amit; Albarqouni, Shadi; Wang, Lichao; Baust, Maximilian; Steiger, Katja; Schlitter, Anna Melissa; Esposito, Irene; Navab, Nassir

2016-08-01

Staining and scanning of tissue samples for microscopic examination is fraught with undesirable color variations arising from differences in raw materials and manufacturing techniques of stain vendors, staining protocols of labs, and color responses of digital scanners. When comparing tissue samples, color normalization and stain separation of the tissue images can be helpful for both pathologists and software. Techniques that are used for natural images fail to utilize structural properties of stained tissue samples and produce undesirable color distortions. The stain concentration cannot be negative. Tissue samples are stained with only a few stains and most tissue regions are characterized by at most one effective stain. We model these physical phenomena that define the tissue structure by first decomposing images in an unsupervised manner into stain density maps that are sparse and non-negative. For a given image, we combine its stain density maps with stain color basis of a pathologist-preferred target image, thus altering only its color while preserving its structure described by the maps. Stain density correlation with ground truth and preference by pathologists were higher for images normalized using our method when compared to other alternatives. We also propose a computationally faster extension of this technique for large whole-slide images that selects an appropriate patch sample instead of using the entire image to compute the stain color basis.

Scaling Law of High Harmonic Generation in the Framework of Photon Channels

NASA Astrophysics Data System (ADS)

Li, Liang; Lan, Pengfei; He, Lixin; Zhu, Xiaosong; Chen, Jing; Lu, Peixiang

2018-06-01

A photon channel perspective on high harmonic generation (HHG) is proposed by quantizing both the driving laser and high harmonics. It is shown that the HHG yield can be expressed as a sum of the contribution of all the photon channels. From this perspective, the contribution of a specific photon channel follows a simple scaling law and the competition between the channels is well interpreted. Our prediction is shown to be in good agreement with the simulations by solving the time-dependent Schrödinger equation. It also can explain well the experimental results of the HHG in the noncollinear two-color field and bicicular laser field.

Scaling Law of High Harmonic Generation in the Framework of Photon Channels.

PubMed

Li, Liang; Lan, Pengfei; He, Lixin; Zhu, Xiaosong; Chen, Jing; Lu, Peixiang

2018-06-01

A photon channel perspective on high harmonic generation (HHG) is proposed by quantizing both the driving laser and high harmonics. It is shown that the HHG yield can be expressed as a sum of the contribution of all the photon channels. From this perspective, the contribution of a specific photon channel follows a simple scaling law and the competition between the channels is well interpreted. Our prediction is shown to be in good agreement with the simulations by solving the time-dependent Schrödinger equation. It also can explain well the experimental results of the HHG in the noncollinear two-color field and bicicular laser field.

Securing Color Fidelity in 3D Architectural Heritage Scenarios.

PubMed

Gaiani, Marco; Apollonio, Fabrizio Ivan; Ballabeni, Andrea; Remondino, Fabio

2017-10-25

Ensuring color fidelity in image-based 3D modeling of heritage scenarios is nowadays still an open research matter. Image colors are important during the data processing as they affect algorithm outcomes, therefore their correct treatment, reduction and enhancement is fundamental. In this contribution, we present an automated solution developed to improve the radiometric quality of an image datasets and the performances of two main steps of the photogrammetric pipeline (camera orientation and dense image matching). The suggested solution aims to achieve a robust automatic color balance and exposure equalization, stability of the RGB-to-gray image conversion and faithful color appearance of a digitized artifact. The innovative aspects of the article are: complete automation, better color target detection, a MATLAB implementation of the ACR scripts created by Fraser and the use of a specific weighted polynomial regression. A series of tests are presented to demonstrate the efficiency of the developed methodology and to evaluate color accuracy ('color characterization').

Correlation based efficient face recognition and color change detection

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

2013-01-01

Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

New Windows based Color Morphological Operators for Biomedical Image Processing

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Securing Color Fidelity in 3D Architectural Heritage Scenarios

PubMed Central

Apollonio, Fabrizio Ivan; Ballabeni, Andrea; Remondino, Fabio

2017-01-01

Ensuring color fidelity in image-based 3D modeling of heritage scenarios is nowadays still an open research matter. Image colors are important during the data processing as they affect algorithm outcomes, therefore their correct treatment, reduction and enhancement is fundamental. In this contribution, we present an automated solution developed to improve the radiometric quality of an image datasets and the performances of two main steps of the photogrammetric pipeline (camera orientation and dense image matching). The suggested solution aims to achieve a robust automatic color balance and exposure equalization, stability of the RGB-to-gray image conversion and faithful color appearance of a digitized artifact. The innovative aspects of the article are: complete automation, better color target detection, a MATLAB implementation of the ACR scripts created by Fraser and the use of a specific weighted polynomial regression. A series of tests are presented to demonstrate the efficiency of the developed methodology and to evaluate color accuracy (‘color characterization’). PMID:29068359

Evaluating color performance of whole-slide imaging devices by multispectral-imaging of biological tissues

NASA Astrophysics Data System (ADS)

Saleheen, Firdous; Badano, Aldo; Cheng, Wei-Chung

2017-03-01

The color reproducibility of two whole-slide imaging (WSI) devices was evaluated with biological tissue slides. Three tissue slides (human colon, skin, and kidney) were used to test a modern and a legacy WSI devices. The color truth of the tissue slides was obtained using a multispectral imaging system. The output WSI images were compared with the color truth to calculate the color difference for each pixel. A psychophysical experiment was also conducted to measure the perceptual color reproducibility (PCR) of the same slides with four subjects. The experiment results show that the mean color differences of the modern, legacy, and monochrome WSI devices are 10.94+/-4.19, 22.35+/-8.99, and 42.74+/-2.96 ▵E00, while their mean PCRs are 70.35+/-7.64%, 23.06+/-14.68%, and 0.91+/-1.01%, respectively.

Physics and psychophysics of color reproduction

NASA Astrophysics Data System (ADS)

Giorgianni, Edward J.

1991-08-01

The successful design of a color-imaging system requires knowledge of the factors used to produce and control color. This knowledge can be derived, in part, from measurements of the physical properties of the imaging system. Color itself, however, is a perceptual response and cannot be directly measured. Though the visual process begins with physics, as radiant energy reaching the eyes, it is in the mind of the observer that the stimuli produced from this radiant energy are interpreted and organized to form meaningful perceptions, including the perception of color. A comprehensive understanding of color reproduction, therefore, requires not only a knowledge of the physical properties of color-imaging systems but also an understanding of the physics, psychophysics, and psychology of the human observer. The human visual process is quite complex; in many ways the physical properties of color-imaging systems are easier to understand.

BRST quantization of cosmological perturbations

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

Armendariz-Picon, Cristian; Şengör, Gizem

2016-11-08

BRST quantization is an elegant and powerful method to quantize theories with local symmetries. In this article we study the Hamiltonian BRST quantization of cosmological perturbations in a universe dominated by a scalar field, along with the closely related quantization method of Dirac. We describe how both formalisms apply to perturbations in a time-dependent background, and how expectation values of gauge-invariant operators can be calculated in the in-in formalism. Our analysis focuses mostly on the free theory. By appropriate canonical transformations we simplify and diagonalize the free Hamiltonian. BRST quantization in derivative gauges allows us to dramatically simplify the structuremore » of the propagators, whereas Dirac quantization, which amounts to quantization in synchronous gauge, dispenses with the need to introduce ghosts and preserves the locality of the gauge-fixed action.« less

A method and results of color calibration for the Chang'e-3 terrain camera and panoramic camera

NASA Astrophysics Data System (ADS)

Ren, Xin; Li, Chun-Lai; Liu, Jian-Jun; Wang, Fen-Fei; Yang, Jian-Feng; Liu, En-Hai; Xue, Bin; Zhao, Ru-Jin

2014-12-01

The terrain camera (TCAM) and panoramic camera (PCAM) are two of the major scientific payloads installed on the lander and rover of the Chang'e 3 mission respectively. They both use a Bayer color filter array covering CMOS sensor to capture color images of the Moon's surface. RGB values of the original images are related to these two kinds of cameras. There is an obvious color difference compared with human visual perception. This paper follows standards published by the International Commission on Illumination to establish a color correction model, designs the ground calibration experiment and obtains the color correction coefficient. The image quality has been significantly improved and there is no obvious color difference in the corrected images. Ground experimental results show that: (1) Compared with uncorrected images, the average color difference of TCAM is 4.30, which has been reduced by 62.1%. (2) The average color differences of the left and right cameras in PCAM are 4.14 and 4.16, which have been reduced by 68.3% and 67.6% respectively.

Image color reduction method for color-defective observers using a color palette composed of 20 particular colors

NASA Astrophysics Data System (ADS)

Sakamoto, Takashi

2015-01-01

This study describes a color enhancement method that uses a color palette especially designed for protan and deutan defects, commonly known as red-green color blindness. The proposed color reduction method is based on a simple color mapping. Complicated computation and image processing are not required by using the proposed method, and the method can replace protan and deutan confusion (p/d-confusion) colors with protan and deutan safe (p/d-safe) colors. Color palettes for protan and deutan defects proposed by previous studies are composed of few p/d-safe colors. Thus, the colors contained in these palettes are insufficient for replacing colors in photographs. Recently, Ito et al. proposed a p/dsafe color palette composed of 20 particular colors. The author demonstrated that their p/d-safe color palette could be applied to image color reduction in photographs as a means to replace p/d-confusion colors. This study describes the results of the proposed color reduction in photographs that include typical p/d-confusion colors, which can be replaced. After the reduction process is completed, color-defective observers can distinguish these confusion colors.

Deformation of second and third quantization

NASA Astrophysics Data System (ADS)

Faizal, Mir

2015-03-01

In this paper, we will deform the second and third quantized theories by deforming the canonical commutation relations in such a way that they become consistent with the generalized uncertainty principle. Thus, we will first deform the second quantized commutator and obtain a deformed version of the Wheeler-DeWitt equation. Then we will further deform the third quantized theory by deforming the third quantized canonical commutation relation. This way we will obtain a deformed version of the third quantized theory for the multiverse.

Melas Chasma - False Color

NASA Image and Video Library

2017-07-13

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of Melas Chasma. Orbit Number: 59750 Latitude: -10.5452 Longitude: 290.307 Instrument: VIS Captured: 2015-06-03 12:33 https://photojournal.jpl.nasa.gov/catalog/PIA21705

Melas Chasma - False Color

NASA Image and Video Library

2015-08-21

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of Melas Chasma. Orbit Number: 10289 Latitude: -9.9472 Longitude: 285.933 Instrument: VIS Captured: 2004-04-09 12:43 http://photojournal.jpl.nasa.gov/catalog/PIA19756

Color quality improvement of reconstructed images in color digital holography using speckle method and spectral estimation

NASA Astrophysics Data System (ADS)

Funamizu, Hideki; Onodera, Yusei; Aizu, Yoshihisa

2018-05-01

In this study, we report color quality improvement of reconstructed images in color digital holography using the speckle method and the spectral estimation. In this technique, an object is illuminated by a speckle field and then an object wave is produced, while a plane wave is used as a reference wave. For three wavelengths, the interference patterns of two coherent waves are recorded as digital holograms on an image sensor. Speckle fields are changed by moving a ground glass plate in an in-plane direction, and a number of holograms are acquired to average the reconstructed images. After the averaging process of images reconstructed from multiple holograms, we use the Wiener estimation method for obtaining spectral transmittance curves in reconstructed images. The color reproducibility in this method is demonstrated and evaluated using a Macbeth color chart film and staining cells of onion.

Output MSE and PSNR prediction in DCT-based lossy compression of remote sensing images

NASA Astrophysics Data System (ADS)

Kozhemiakin, Ruslan A.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

2017-10-01

Amount and size of remote sensing (RS) images acquired by modern systems are so large that data have to be compressed in order to transfer, save and disseminate them. Lossy compression becomes more popular for aforementioned situations. But lossy compression has to be applied carefully with providing acceptable level of introduced distortions not to lose valuable information contained in data. Then introduced losses have to be controlled and predicted and this is problematic for many coders. In this paper, we analyze possibilities of predicting mean square error or, equivalently, PSNR for coders based on discrete cosine transform (DCT) applied either for compressing singlechannel RS images or multichannel data in component-wise manner. The proposed approach is based on direct dependence between distortions introduced due to DCT coefficient quantization and losses in compressed data. One more innovation deals with possibility to employ a limited number (percentage) of blocks for which DCT-coefficients have to be calculated. This accelerates prediction and makes it considerably faster than compression itself. There are two other advantages of the proposed approach. First, it is applicable for both uniform and non-uniform quantization of DCT coefficients. Second, the approach is quite general since it works for several analyzed DCT-based coders. The simulation results are obtained for standard test images and then verified for real-life RS data.

The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine

PubMed Central

Tu, Li-ping; Chen, Jing-bo; Hu, Xiao-juan; Zhang, Zhi-feng

2016-01-01

Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods. Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L * a * b * of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results. The L * a * b * values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions. At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible. PMID:28050555

The Classification of Tongue Colors with Standardized Acquisition and ICC Profile Correction in Traditional Chinese Medicine.

PubMed

Qi, Zhen; Tu, Li-Ping; Chen, Jing-Bo; Hu, Xiao-Juan; Xu, Jia-Tuo; Zhang, Zhi-Feng

2016-01-01

Background and Goal . The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods . Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L * a * b * of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results . The L * a * b * values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions . At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible.

Color-coded fluid-attenuated inversion recovery images improve inter-rater reliability of fluid-attenuated inversion recovery signal changes within acute diffusion-weighted image lesions.

PubMed

Kim, Bum Joon; Kim, Yong-Hwan; Kim, Yeon-Jung; Ahn, Sung Ho; Lee, Deok Hee; Kwon, Sun U; Kim, Sang Joon; Kim, Jong S; Kang, Dong-Wha

2014-09-01

Diffusion-weighted image fluid-attenuated inversion recovery (FLAIR) mismatch has been considered to represent ischemic lesion age. However, the inter-rater agreement of diffusion-weighted image FLAIR mismatch is low. We hypothesized that color-coded images would increase its inter-rater agreement. Patients with ischemic stroke <24 hours of a clear onset were retrospectively studied. FLAIR signal change was rated as negative, subtle, or obvious on conventional and color-coded FLAIR images based on visual inspection. Inter-rater agreement was evaluated using κ and percent agreement. The predictive value of diffusion-weighted image FLAIR mismatch for identification of patients <4.5 hours of symptom onset was evaluated. One hundred and thirteen patients were enrolled. The inter-rater agreement of FLAIR signal change improved from 69.9% (k=0.538) with conventional images to 85.8% (k=0.754) with color-coded images (P=0.004). Discrepantly rated patients on conventional, but not on color-coded images, had a higher prevalence of cardioembolic stroke (P=0.02) and cortical infarction (P=0.04). The positive predictive value for patients <4.5 hours of onset was 85.3% and 71.9% with conventional and 95.7% and 82.1% with color-coded images, by each rater. Color-coded FLAIR images increased the inter-rater agreement of diffusion-weighted image FLAIR recovery mismatch and may ultimately help identify unknown-onset stroke patients appropriate for thrombolysis. © 2014 American Heart Association, Inc.

An Underwater Color Image Quality Evaluation Metric.

PubMed

Yang, Miao; Sowmya, Arcot

2015-12-01

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

A new Watermarking System based on Discrete Cosine Transform (DCT) in color biometric images.

PubMed

Dogan, Sengul; Tuncer, Turker; Avci, Engin; Gulten, Arif

2012-08-01

This paper recommend a biometric color images hiding approach An Watermarking System based on Discrete Cosine Transform (DCT), which is used to protect the security and integrity of transmitted biometric color images. Watermarking is a very important hiding information (audio, video, color image, gray image) technique. It is commonly used on digital objects together with the developing technology in the last few years. One of the common methods used for hiding information on image files is DCT method which used in the frequency domain. In this study, DCT methods in order to embed watermark data into face images, without corrupting their features.

[True color accuracy in digital forensic photography].

PubMed

Ramsthaler, Frank; Birngruber, Christoph G; Kröll, Ann-Katrin; Kettner, Mattias; Verhoff, Marcel A

2016-01-01

Forensic photographs not only need to be unaltered and authentic and capture context-relevant images, along with certain minimum requirements for image sharpness and information density, but color accuracy also plays an important role, for instance, in the assessment of injuries or taphonomic stages, or in the identification and evaluation of traces from photos. The perception of color not only varies subjectively from person to person, but as a discrete property of an image, color in digital photos is also to a considerable extent influenced by technical factors such as lighting, acquisition settings, camera, and output medium (print, monitor). For these reasons, consistent color accuracy has so far been limited in digital photography. Because images usually contain a wealth of color information, especially for complex or composite colors or shades of color, and the wavelength-dependent sensitivity to factors such as light and shadow may vary between cameras, the usefulness of issuing general recommendations for camera capture settings is limited. Our results indicate that true image colors can best and most realistically be captured with the SpyderCheckr technical calibration tool for digital cameras tested in this study. Apart from aspects such as the simplicity and quickness of the calibration procedure, a further advantage of the tool is that the results are independent of the camera used and can also be used for the color management of output devices such as monitors and printers. The SpyderCheckr color-code patches allow true colors to be captured more realistically than with a manual white balance tool or an automatic flash. We therefore recommend that the use of a color management tool should be considered for the acquisition of all images that demand high true color accuracy (in particular in the setting of injury documentation).

Quantization selection in the high-throughput H.264/AVC encoder based on the RD

NASA Astrophysics Data System (ADS)

Pastuszak, Grzegorz

2013-10-01

In the hardware video encoder, the quantization is responsible for quality losses. On the other hand, it allows the reduction of bit rates to the target one. If the mode selection is based on the rate-distortion criterion, the quantization can also be adjusted to obtain better compression efficiency. Particularly, the use of Lagrangian function with a given multiplier enables the encoder to select the most suitable quantization step determined by the quantization parameter QP. Moreover, the quantization offset added before discarding the fraction value after quantization can be adjusted. In order to select the best quantization parameter and offset in real time, the HD/SD encoder should be implemented in the hardware. In particular, the hardware architecture should embed the transformation and quantization modules able to process the same residuals many times. In this work, such an architecture is used. Experimental results show what improvements in terms of compression efficiency are achievable for Intra coding.

Three Fresh Exposures, Enhanced Color

NASA Technical Reports Server (NTRS)

2004-01-01

This enhanced-color panoramic camera image from the Mars Exploration Rover Opportunity features three holes created by the rock abrasion tool between sols 143 and 148 (June 18 and June 23, 2004) inside 'Endurance Crater.' The enhanced image makes the red colors a little redder and blue colors a little bluer, allowing viewers to see differences too subtle to be seen without the exaggeration. When compared with an approximately true color image, the tailings from the rock abrasion tool and the interior of the abraded holes are more prominent in this view. Being able to discriminate color variations helps scientists determine rocks' compositional differences and texture variations. This image was created using the 753-, 535- and 432-nanometer filters.

Security of Color Image Data Designed by Public-Key Cryptosystem Associated with 2D-DWT

NASA Astrophysics Data System (ADS)

Mishra, D. C.; Sharma, R. K.; Kumar, Manish; Kumar, Kuldeep

2014-08-01

In present times the security of image data is a major issue. So, we have proposed a novel technique for security of color image data by public-key cryptosystem or asymmetric cryptosystem. In this technique, we have developed security of color image data using RSA (Rivest-Shamir-Adleman) cryptosystem with two-dimensional discrete wavelet transform (2D-DWT). Earlier proposed schemes for security of color images designed on the basis of keys, but this approach provides security of color images with the help of keys and correct arrangement of RSA parameters. If the attacker knows about exact keys, but has no information of exact arrangement of RSA parameters, then the original information cannot be recovered from the encrypted data. Computer simulation based on standard example is critically examining the behavior of the proposed technique. Security analysis and a detailed comparison between earlier developed schemes for security of color images and proposed technique are also mentioned for the robustness of the cryptosystem.

Single-exposure quantitative phase imaging in color-coded LED microscopy.

PubMed

Lee, Wonchan; Jung, Daeseong; Ryu, Suho; Joo, Chulmin

2017-04-03

We demonstrate single-shot quantitative phase imaging (QPI) in a platform of color-coded LED microscopy (cLEDscope). The light source in a conventional microscope is replaced by a circular LED pattern that is trisected into subregions with equal area, assigned to red, green, and blue colors. Image acquisition with a color image sensor and subsequent computation based on weak object transfer functions allow for the QPI of a transparent specimen. We also provide a correction method for color-leakage, which may be encountered in implementing our method with consumer-grade LEDs and image sensors. Most commercially available LEDs and image sensors do not provide spectrally isolated emissions and pixel responses, generating significant error in phase estimation in our method. We describe the correction scheme for this color-leakage issue, and demonstrate improved phase measurement accuracy. The computational model and single-exposure QPI capability of our method are presented by showing images of calibrated phase samples and cellular specimens.

Image enhancement and color constancy for a vehicle-mounted change detection system

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Monnin, David

2016-10-01

Vehicle-mounted change detection systems allow to improve situational awareness on outdoor itineraries of inter- est. Since the visibility of acquired images is often affected by illumination effects (e.g., shadows) it is important to enhance local contrast. For the analysis and comparison of color images depicting the same scene at different time points it is required to compensate color and lightness inconsistencies caused by the different illumination conditions. We have developed an approach for image enhancement and color constancy based on the center/surround Retinex model and the Gray World hypothesis. The combination of the two methods using a color processing function improves color rendition, compared to both methods. The use of stacked integral images (SII) allows to efficiently perform local image processing. Our combined Retinex/Gray World approach has been successfully applied to image sequences acquired on outdoor itineraries at different time points and a comparison with previous Retinex-based approaches has been carried out.

Video and thermal imaging system for monitoring interiors of high temperature reaction vessels

DOEpatents

Saveliev, Alexei V [Chicago, IL; Zelepouga, Serguei A [Hoffman Estates, IL; Rue, David M [Chicago, IL

2012-01-10

A system and method for real-time monitoring of the interior of a combustor or gasifier wherein light emitted by the interior surface of a refractory wall of the combustor or gasifier is collected using an imaging fiber optic bundle having a light receiving end and a light output end. Color information in the light is captured with primary color (RGB) filters or complimentary color (GMCY) filters placed over individual pixels of color sensors disposed within a digital color camera in a BAYER mosaic layout, producing RGB signal outputs or GMCY signal outputs. The signal outputs are processed using intensity ratios of the primary color filters or the complimentary color filters, producing video images and/or thermal images of the interior of the combustor or gasifier.

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

NASA Astrophysics Data System (ADS)

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

2003-09-01

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

Computerized simulation of color appearance for anomalous trichromats using the multispectral image.

PubMed

Yaguchi, Hirohisa; Luo, Junyan; Kato, Miharu; Mizokami, Yoko

2018-04-01

Most color simulators for color deficiencies are based on the tristimulus values and are intended to simulate the appearance of an image for dichromats. Statistics show that there are more anomalous trichromats than dichromats. Furthermore, the spectral sensitivities of anomalous cones are different from those of normal cones. Clinically, the types of color defects are characterized through Rayleigh color matching, where the observer matches a spectral yellow to a mixture of spectral red and green. The midpoints of the red/green ratios deviate from a normal trichromat. This means that any simulation based on the tristimulus values defined by a normal trichromat cannot predict the color appearance of anomalous Rayleigh matches. We propose a computerized simulation of the color appearance for anomalous trichromats using multispectral images. First, we assume that anomalous trichromats possess a protanomalous (green shifted) or deuteranomalous (red shifted) pigment instead of a normal (L or M) one. Second, we assume that the luminance will be given by L+M, and red/green and yellow/blue opponent color stimulus values are defined through L-M and (L+M)-S, respectively. Third, equal-energy white will look white for all observers. The spectral sensitivities of the luminance and the two opponent color channels are multiplied by the spectral radiance of each pixel of a multispectral image to give the luminance and opponent color stimulus values of the entire image. In the next stage of color reproduction for normal observers, the luminance and two opponent color channels are transformed into XYZ tristimulus values and then transformed into sRGB to reproduce a final image for anomalous trichromats. The proposed simulation can be used to predict the Rayleigh color matches for anomalous trichromats. We also conducted experiments to evaluate the appearance of simulated images by color deficient observers and verified the reliability of the simulation.

Imaging agents for monitoring changes of dopamine receptors and methods of using thereof

DOEpatents

Mukherjee, Jogeshwar; Chandy, George; Milne, Norah; Wang, Ping H.; Easwaramoorthy, Balu; Mantil, Joseph; Garcia, Adriana

2017-05-30

The present invention is related generally to a method for screening subjects to determine those subjects more likely to develop diabetes by quantization of insulin producing cells. The present invention is also related to the diagnosis of diabetes and related to monitor disease progression or treatment efficacy of candidate drugs.

Detection system for concentration quantization of colloidal-gold test strips based on embedded and image technology

USDA-ARS?s Scientific Manuscript database

Facing the increasing food safety issues, Chinese government has been carrying out compulsory tests on food to meet the requirements of domestic and foreign markets. Colloidal-gold test strips using the colorimetric principle are widely used for rapid qualitative detection of harmful residues in fo...

The Rich Color Variations of Pluto

NASA Image and Video Library

2015-09-24

NASA's New Horizons spacecraft captured this high-resolution enhanced color view of Pluto on July 14, 2015. The image combines blue, red and infrared images taken by the Ralph/Multispectral Visual Imaging Camera (MVIC). Pluto's surface sports a remarkable range of subtle colors, enhanced in this view to a rainbow of pale blues, yellows, oranges, and deep reds. Many landforms have their own distinct colors, telling a complex geological and climatological story that scientists have only just begun to decode. The image resolves details and colors on scales as small as 0.8 miles (1.3 kilometers). http://photojournal.jpl.nasa.gov/catalog/PIA19952

NPS assessment of color medical image displays using a monochromatic CCD camera

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

2012-10-01

This paper presents an approach to Noise Power Spectrum (NPS) assessment of color medical displays without using an expensive imaging colorimeter. The R, G and B color uniform patterns were shown on the display under study and the images were taken using a high resolution monochromatic camera. A colorimeter was used to calibrate the camera images. Synthetic intensity images were formed by the weighted sum of the R, G, B and the dark screen images. Finally the NPS analysis was conducted on the synthetic images. The proposed method replaces an expensive imaging colorimeter for NPS evaluation, which also suggests a potential solution for routine color medical display QA/QC in the clinical area, especially when imaging of display devices is desired

Terra Cimmeria - False Color

NASA Image and Video Library

2016-10-11

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows dust devil tracks (dark blue linear feature) in Terra Cimmeria. Orbit Number: 43463 Latitude: -53.1551 Longitude: 125.069 Instrument: VIS Captured: 2011-10-01 23:55 http://photojournal.jpl.nasa.gov/catalog/PIA21009

Russell Crater - False Color

NASA Image and Video Library

2017-06-01

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of Russell Crater in Noachis Terra. Orbit Number: 59591 Latitude: -54.471 Longitude: 13.1288 Instrument: VIS Captured: 2015-05-21 10:57 https://photojournal.jpl.nasa.gov/catalog/PIA21674

Optimal monochromatic color combinations for fusion imaging of FDG-PET and diffusion-weighted MR images.

PubMed

Kamei, Ryotaro; Watanabe, Yuji; Sagiyama, Koji; Isoda, Takuro; Togao, Osamu; Honda, Hiroshi

2018-05-23

To investigate the optimal monochromatic color combination for fusion imaging of FDG-PET and diffusion-weighted MR images (DW) regarding lesion conspicuity of each image. Six linear monochromatic color-maps of red, blue, green, cyan, magenta, and yellow were assigned to each of the FDG-PET and DW images. Total perceptual color differences of the lesions were calculated based on the lightness and chromaticity measured with the photometer. Visual lesion conspicuity was also compared among the PET-only, DW-only and PET-DW-double positive portions with mean conspicuity scores. Statistical analysis was performed with a one-way analysis of variance and Spearman's rank correlation coefficient. Among all the 12 possible monochromatic color-map combinations, the 3 combinations of red/cyan, magenta/green, and red/green produced the highest conspicuity scores. Total color differences between PET-positive and double-positive portions correlated with conspicuity scores (ρ = 0.2933, p < 0.005). Lightness differences showed a significant negative correlation with conspicuity scores between the PET-only and DWI-only positive portions. Chromaticity differences showed a marginally significant correlation with conspicuity scores between DWI-positive and double-positive portions. Monochromatic color combinations can facilitate the visual evaluation of FDG-uptake and diffusivity as well as registration accuracy on the FDG-PET/DW fusion images, when red- and green-colored elements are assigned to FDG-PET and DW images, respectively.

Full Spectrum Conversion Using Traveling Pulse Wave Quantization

DTIC Science & Technology

2017-03-01

Full Spectrum Conversion Using Traveling Pulse Wave Quantization Michael S. Kappes Mikko E. Waltari IQ-Analog Corporation San Diego, California...temporal-domain quantization technique called Traveling Pulse Wave Quantization (TPWQ). Full spectrum conversion is defined as the complete...pulse width measurements that are continuously generated hence the name “traveling” pulse wave quantization. Our TPWQ-based ADC is composed of a

Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

NASA Astrophysics Data System (ADS)

Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

2018-02-01

In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

Modeling a color-rendering operator for high dynamic range images using a cone-response function

NASA Astrophysics Data System (ADS)

Choi, Ho-Hyoung; Kim, Gi-Seok; Yun, Byoung-Ju

2015-09-01

Tone-mapping operators are the typical algorithms designed to produce visibility and the overall impression of brightness, contrast, and color of high dynamic range (HDR) images on low dynamic range (LDR) display devices. Although several new tone-mapping operators have been proposed in recent years, the results of these operators have not matched those of the psychophysical experiments based on the human visual system. A color-rendering model that is a combination of tone-mapping and cone-response functions using an XYZ tristimulus color space is presented. In the proposed method, the tone-mapping operator produces visibility and the overall impression of brightness, contrast, and color in HDR images when mapped onto relatively LDR devices. The tone-mapping resultant image is obtained using chromatic and achromatic colors to avoid well-known color distortions shown in the conventional methods. The resulting image is then processed with a cone-response function wherein emphasis is placed on human visual perception (HVP). The proposed method covers the mismatch between the actual scene and the rendered image based on HVP. The experimental results show that the proposed method yields an improved color-rendering performance compared to conventional methods.

Image Retrieval by Color Semantics with Incomplete Knowledge.

ERIC Educational Resources Information Center

Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico

1998-01-01

Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)

Color Facsimile.

DTIC Science & Technology

1995-02-01

modification of existing JPEG compression and decompression software available from Independent JPEG Users Group to process CIELAB color images and to use...externally specificed Huffman tables. In addition a conversion program was written to convert CIELAB color space images to red, green, blue color space

Quantifying nonhomogeneous colors in agricultural materials. Part II: comparison of machine vision and sensory panel evaluations.

PubMed

Balaban, M O; Aparicio, J; Zotarelli, M; Sims, C

2008-11-01

The average colors of mangos and apples were measured using machine vision. A method to quantify the perception of nonhomogeneous colors by sensory panelists was developed. Three colors out of several reference colors and their perceived percentage of the total sample area were selected by untrained panelists. Differences between the average colors perceived by panelists and those from the machine vision were reported as DeltaE values (color difference error). Effects of nonhomogeneity of color, and using real samples or their images in the sensory panels on DeltaE were evaluated. In general, samples with more nonuniform colors had higher DeltaE values, suggesting that panelists had more difficulty in evaluating more nonhomogeneous colors. There was no significant difference in DeltaE values between the real fruits and their screen image, therefore images can be used to evaluate color instead of the real samples.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

A user's guide for the signal processing software for image and speech compression developed in the Communications and Signal Processing Laboratory (CSPL), version 1

NASA Technical Reports Server (NTRS)

Kumar, P.; Lin, F. Y.; Vaishampayan, V.; Farvardin, N.

1986-01-01

A complete documentation of the software developed in the Communication and Signal Processing Laboratory (CSPL) during the period of July 1985 to March 1986 is provided. Utility programs and subroutines that were developed for a user-friendly image and speech processing environment are described. Additional programs for data compression of image and speech type signals are included. Also, programs for the zero-memory and block transform quantization in the presence of channel noise are described. Finally, several routines for simulating the perfromance of image compression algorithms are included.

Multi-rate, real time image compression for images dominated by point sources

NASA Technical Reports Server (NTRS)

Huber, A. Kris; Budge, Scott E.; Harris, Richard W.

1993-01-01

An image compression system recently developed for compression of digital images dominated by point sources is presented. Encoding consists of minimum-mean removal, vector quantization, adaptive threshold truncation, and modified Huffman encoding. Simulations are presented showing that the peaks corresponding to point sources can be transmitted losslessly for low signal-to-noise ratios (SNR) and high point source densities while maintaining a reduced output bit rate. Encoding and decoding hardware has been built and tested which processes 552,960 12-bit pixels per second at compression rates of 10:1 and 4:1. Simulation results are presented for the 10:1 case only.

Population attribute compression

DOEpatents

White, James M.; Faber, Vance; Saltzman, Jeffrey S.

1995-01-01

An image population having a large number of attributes is processed to form a display population with a predetermined smaller number of attributes that represent the larger number of attributes. In a particular application, the color values in an image are compressed for storage in a discrete look-up table (LUT). Color space containing the LUT color values is successively subdivided into smaller volumes until a plurality of volumes are formed, each having no more than a preselected maximum number of color values. Image pixel color values can then be rapidly placed in a volume with only a relatively few LUT values from which a nearest neighbor is selected. Image color values are assigned 8 bit pointers to their closest LUT value whereby data processing requires only the 8 bit pointer value to provide 24 bit color values from the LUT.

The effect of different standard illumination conditions on color balance failure in offset printed images on glossy coated paper expressed by color difference

NASA Astrophysics Data System (ADS)

Spiridonov, I.; Shopova, M.; Boeva, R.; Nikolov, M.

2012-05-01

One of the biggest problems in color reproduction processes is color shifts occurring when images are viewed under different illuminants. Process ink colors and their combinations that match under one light source will often appear different under another light source. This problem is referred to as color balance failure or color inconstancy. The main goals of the present study are to investigate and determine the color balance failure (color inconstancy) of offset printed images expressed by color difference and color gamut changes depending on three of the most commonly used in practice illuminants, CIE D50, CIE F2 and CIE A. The results obtained are important from a scientific and a practical point of view. For the first time, a methodology is suggested and implemented for the examination and estimation of color shifts by studying a large number of color and gamut changes in various ink combinations for different illuminants.

Russell Crater Dunes - False Color

NASA Image and Video Library

2017-07-07

The THEMIS VIS camera contains 5 filters. The data from different filters can be combined in multiple ways to create a false color image. These false color images may reveal subtle variations of the surface not easily identified in a single band image. Today's false color image shows part of the large dune form on the floor of Russell Crater. Orbit Number: 59672 Latitude: -54.337 Longitude: 13.1087 Instrument: VIS Captured: 2015-05-28 02:39 https://photojournal.jpl.nasa.gov/catalog/PIA21701

Availability of color calibration for consistent color display in medical images and optimization of reference brightness for clinical use

NASA Astrophysics Data System (ADS)

Iwai, Daiki; Suganami, Haruka; Hosoba, Minoru; Ohno, Kazuko; Emoto, Yutaka; Tabata, Yoshito; Matsui, Norihisa

2013-03-01

Color image consistency has not been accomplished yet except the Digital Imaging and Communication in Medicine (DICOM) Supplement 100 for implementing a color reproduction pipeline and device independent color spaces. Thus, most healthcare enterprises could not check monitor degradation routinely. To ensure color consistency in medical color imaging, monitor color calibration should be introduced. Using simple color calibration device . chromaticity of colors including typical color (Red, Green, Blue, Green and White) are measured as device independent profile connection space value called u'v' before and after calibration. In addition, clinical color images are displayed and visual differences are observed. In color calibration, monitor brightness level has to be set to quite lower value 80 cd/m2 according to sRGB standard. As Maximum brightness of most color monitors available currently for medical use have much higher brightness than 80 cd/m2, it is not seemed to be appropriate to use 80 cd/m2 level for calibration. Therefore, we propose that new brightness standard should be introduced while maintaining the color representation in clinical use. To evaluate effects of brightness to chromaticity experimentally, brightness level is changed in two monitors from 80 to 270cd/m2 and chromaticity value are compared with each brightness levels. As a result, there are no significant differences in chromaticity diagram when brightness levels are changed. In conclusion, chromaticity is close to theoretical value after color calibration. Moreover, chromaticity isn't moved when brightness is changed. The results indicate optimized reference brightness level for clinical use could be set at high brightness in current monitors .

Dual-color 3D superresolution microscopy by combined spectral-demixing and biplane imaging.

PubMed

Winterflood, Christian M; Platonova, Evgenia; Albrecht, David; Ewers, Helge

2015-07-07

Multicolor three-dimensional (3D) superresolution techniques allow important insight into the relative organization of cellular structures. While a number of innovative solutions have emerged, multicolor 3D techniques still face significant technical challenges. In this Letter we provide a straightforward approach to single-molecule localization microscopy imaging in three dimensions and two colors. We combine biplane imaging and spectral-demixing, which eliminates a number of problems, including color cross-talk, chromatic aberration effects, and problems with color registration. We present 3D dual-color images of nanoscopic structures in hippocampal neurons with a 3D compound resolution routinely achieved only in a single color. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Spectral edge: gradient-preserving spectral mapping for image fusion.

PubMed

Connah, David; Drew, Mark S; Finlayson, Graham D

2015-12-01

This paper describes a novel approach to image fusion for color display. Our goal is to generate an output image whose gradient matches that of the input as closely as possible. We achieve this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mapped exactly to that of a low-dimensional gradient field which is then reintegrated to form an output. Constraints on output colors are provided by an initial RGB rendering. Initially, we motivate our solution with a simple "ansatz" (educated guess) for projecting higher-D contrast onto color gradients, which we expand to a more rigorous theorem to incorporate color constraints. The solution to these constrained optimizations is closed-form, allowing for simple and hence fast and efficient algorithms. The approach can map any N-D image data to any M-D output and can be used in a variety of applications using the same basic algorithm. In this paper, we focus on the problem of mapping N-D inputs to 3D color outputs. We present results in five applications: hyperspectral remote sensing, fusion of color and near-infrared or clear-filter images, multilighting imaging, dark flash, and color visualization of magnetic resonance imaging diffusion-tensor imaging.

NPS assessment of color medical displays using a monochromatic CCD camera

NASA Astrophysics Data System (ADS)

Roehrig, Hans; Gu, Xiliang; Fan, Jiahua

2012-02-01

This paper presents an approach to Noise Power Spectrum (NPS) assessment of color medical displays without using an expensive imaging colorimeter. The R, G and B color uniform patterns were shown on the display under study and the images were taken using a high resolution monochromatic camera. A colorimeter was used to calibrate the camera images. Synthetic intensity images were formed by the weighted sum of the R, G, B and the dark screen images. Finally the NPS analysis was conducted on the synthetic images. The proposed method replaces an expensive imaging colorimeter for NPS evaluation, which also suggests a potential solution for routine color medical display QA/QC in the clinical area, especially when imaging of display devices is desired.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents.

PubMed

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-13

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions.

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

PubMed Central

Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

2017-01-01

The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

Quantizing and sampling considerations in digital phased-locked loops

NASA Technical Reports Server (NTRS)

Hurst, G. T.; Gupta, S. C.

1974-01-01

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

GREAT: a gradient-based color-sampling scheme for Retinex.

PubMed

Lecca, Michela; Rizzi, Alessandro; Serapioni, Raul Paolo

2017-04-01

Modeling the local color spatial distribution is a crucial step for the algorithms of the Milano Retinex family. Here we present GREAT, a novel, noise-free Milano Retinex implementation based on an image-aware spatial color sampling. For each channel of a color input image, GREAT computes a 2D set of edges whose magnitude exceeds a pre-defined threshold. Then GREAT re-scales the channel intensity of each image pixel, called target, by the average of the intensities of the selected edges weighted by a function of their positions, gradient magnitudes, and intensities relative to the target. In this way, GREAT enhances the input image, adjusting its brightness, contrast and dynamic range. The use of the edges as pixels relevant to color filtering is justified by the importance that edges play in human color sensation. The name GREAT comes from the expression "Gradient RElevAnce for ReTinex," which refers to the threshold-based definition of a gradient relevance map for edge selection and thus for image color filtering.

Single Lens Dual-Aperture 3D Imaging System: Color Modeling

NASA Technical Reports Server (NTRS)

Bae, Sam Y.; Korniski, Ronald; Ream, Allen; Fritz, Eric; Shearn, Michael

2012-01-01

In an effort to miniaturize a 3D imaging system, we created two viewpoints in a single objective lens camera. This was accomplished by placing a pair of Complementary Multi-band Bandpass Filters (CMBFs) in the aperture area. Two key characteristics about the CMBFs are that the passbands are staggered so only one viewpoint is opened at a time when a light band matched to that passband is illuminated, and the passbands are positioned throughout the visible spectrum, so each viewpoint can render color by taking RGB spectral images. Each viewpoint takes a different spectral image from the other viewpoint hence yielding a different color image relative to the other. This color mismatch in the two viewpoints could lead to color rivalry, where the human vision system fails to resolve two different colors. The difference will be closer if the number of passbands in a CMBF increases. (However, the number of passbands is constrained by cost and fabrication technique.) In this paper, simulation predicting the color mismatch is reported.

A blind dual color images watermarking based on IWT and state coding

NASA Astrophysics Data System (ADS)

Su, Qingtang; Niu, Yugang; Liu, Xianxi; Zhu, Yu

2012-04-01

In this paper, a state-coding based blind watermarking algorithm is proposed to embed color image watermark to color host image. The technique of state coding, which makes the state code of data set be equal to the hiding watermark information, is introduced in this paper. When embedding watermark, using Integer Wavelet Transform (IWT) and the rules of state coding, these components, R, G and B, of color image watermark are embedded to these components, Y, Cr and Cb, of color host image. Moreover, the rules of state coding are also used to extract watermark from the watermarked image without resorting to the original watermark or original host image. Experimental results show that the proposed watermarking algorithm cannot only meet the demand on invisibility and robustness of the watermark, but also have well performance compared with other proposed methods considered in this work.

Distinction of Green Sweet Peppers by Using Various Color Space Models and Computation of 3 Dimensional Location Coordinates of Recognized Green Sweet Peppers Based on Parallel Stereovision System

NASA Astrophysics Data System (ADS)

Bachche, Shivaji; Oka, Koichi

2013-06-01

This paper presents the comparative study of various color space models to determine the suitable color space model for detection of green sweet peppers. The images were captured by using CCD cameras and infrared cameras and processed by using Halcon image processing software. The LED ring around the camera neck was used as an artificial lighting to enhance the feature parameters. For color images, CieLab, YIQ, YUV, HSI and HSV whereas for infrared images, grayscale color space models were selected for image processing. In case of color images, HSV color space model was found more significant with high percentage of green sweet pepper detection followed by HSI color space model as both provides information in terms of hue/lightness/chroma or hue/lightness/saturation which are often more relevant to discriminate the fruit from image at specific threshold value. The overlapped fruits or fruits covered by leaves can be detected in better way by using HSV color space model as the reflection feature from fruits had higher histogram than reflection feature from leaves. The IR 80 optical filter failed to distinguish fruits from images as filter blocks useful information on features. Computation of 3D coordinates of recognized green sweet peppers was also conducted in which Halcon image processing software provides location and orientation of the fruits accurately. The depth accuracy of Z axis was examined in which 500 to 600 mm distance between cameras and fruits was found significant to compute the depth distance precisely when distance between two cameras maintained to 100 mm.

a New Color Correction Method for Underwater Imaging

NASA Astrophysics Data System (ADS)

Bianco, G.; Muzzupappa, M.; Bruno, F.; Garcia, R.; Neumann, L.

2015-04-01

Recovering correct or at least realistic colors of underwater scenes is a very challenging issue for imaging techniques, since illumination conditions in a refractive and turbid medium as the sea are seriously altered. The need to correct colors of underwater images or videos is an important task required in all image-based applications like 3D imaging, navigation, documentation, etc. Many imaging enhancement methods have been proposed in literature for these purposes. The advantage of these methods is that they do not require the knowledge of the medium physical parameters while some image adjustments can be performed manually (as histogram stretching) or automatically by algorithms based on some criteria as suggested from computational color constancy methods. One of the most popular criterion is based on gray-world hypothesis, which assumes that the average of the captured image should be gray. An interesting application of this assumption is performed in the Ruderman opponent color space lαβ, used in a previous work for hue correction of images captured under colored light sources, which allows to separate the luminance component of the scene from its chromatic components. In this work, we present the first proposal for color correction of underwater images by using lαβ color space. In particular, the chromatic components are changed moving their distributions around the white point (white balancing) and histogram cutoff and stretching of the luminance component is performed to improve image contrast. The experimental results demonstrate the effectiveness of this method under gray-world assumption and supposing uniform illumination of the scene. Moreover, due to its low computational cost it is suitable for real-time implementation.

Modeling and analysis of energy quantization effects on single electron inverter performance

NASA Astrophysics Data System (ADS)

Dan, Surya Shankar; Mahapatra, Santanu

2009-08-01

In this paper, for the first time, the effects of energy quantization on single electron transistor (SET) inverter performance are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantization mainly changes the Coulomb blockade region and drain current of SET devices and thus affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new analytical model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. A compact expression is developed for a novel parameter quantization threshold which is introduced for the first time in this paper. Quantization threshold explicitly defines the maximum energy quantization that an SET inverter logic circuit can withstand before its noise margin falls below a specified tolerance level. It is found that SET inverter designed with CT:CG=1/3 (where CT and CG are tunnel junction and gate capacitances, respectively) offers maximum robustness against energy quantization.

An instructional guide for leaf color analysis using digital imaging software

Treesearch

Paula F. Murakami; Michelle R. Turner; Abby K. van den Berg; Paul G. Schaberg

2005-01-01

Digital color analysis has become an increasingly popular and cost-effective method utilized by resource managers and scientists for evaluating foliar nutrition and health in response to environmental stresses. We developed and tested a new method of digital image analysis that uses Scion Image or NIH image public domain software to quantify leaf color. This...

Fuzzy Logic-Based Filter for Removing Additive and Impulsive Noise from Color Images

NASA Astrophysics Data System (ADS)

Zhu, Yuhong; Li, Hongyang; Jiang, Huageng

2017-12-01

This paper presents an efficient filter method based on fuzzy logics for adaptively removing additive and impulsive noise from color images. The proposed filter comprises two parts including noise detection and noise removal filtering. In the detection part, the fuzzy peer group concept is applied to determine what type of noise is added to each pixel of the corrupted image. In the filter part, the impulse noise is deducted by the vector median filter in the CIELAB color space and an optimal fuzzy filter is introduced to reduce the Gaussian noise, while they can work together to remove the mixed Gaussian-impulse noise from color images. Experimental results on several color images proves the efficacy of the proposed fuzzy filter.

Compression of color-mapped images

NASA Technical Reports Server (NTRS)

Hadenfeldt, A. C.; Sayood, Khalid

1992-01-01

In a standard image coding scenario, pixel-to-pixel correlation nearly always exists in the data, especially if the image is a natural scene. This correlation is what allows predictive coding schemes (e.g., DPCM) to perform efficient compression. In a color-mapped image, the values stored in the pixel array are no longer directly related to the pixel intensity. Two color indices which are numerically adjacent (close) may point to two very different colors. The correlation still exists, but only via the colormap. This fact can be exploited by sorting the color map to reintroduce the structure. The sorting of colormaps is studied and it is shown how the resulting structure can be used in both lossless and lossy compression of images.

Snow Storm Blankets Southeastern U.S.

NASA Technical Reports Server (NTRS)

2002-01-01

A new year's storm brought heavy snow to portions of the southeastern United States, with some regions receiving more than a foot in less than two days. By Friday, January 4, 2002, the skies had cleared, and MODIS captured this false-color image showing the extent of the snowfall. Snow cover is red, and extends all the way from Alabama (lower left), up through Georgia, South Carolina, North Carolina, Virginia, and Maryland, including the southern reaches of the Delmarva Peninsula (upper right). Beneath some clouds in West Virginia (top center), snow is also visible on the Allegheny Mountains and the Appalachian Plateau, although it did come from the same storm. Though red isn't the color we associate with snow, scientists often find 'false-color' images more useful than 'true-color' images in certain situations. True-color images are images in which the satellite data are made to look like what our eyes would see, using a combination of red, green, and blue. In a true-color image of this scene, cloud and snow would appear almost identical-both would be very bright white-and would be hard to distinguish from each other. However, at near-infrared wavelengths of light, snow cover absorbs sunlight and therefore appears much darker than clouds. So a false-color image in which one visible wavelength of the data is colored red, and different near-infrared wavelengths are colored green and blue helps show the snow cover most clearly.

Color analysis of the human airway wall

NASA Astrophysics Data System (ADS)

Gopalakrishnan, Deepa; McLennan, Geoffrey; Donnelley, Martin; Delsing, Angela; Suter, Melissa; Flaherty, Dawn; Zabner, Joseph; Hoffman, Eric A.; Reinhardt, Joseph M.

2002-04-01

A bronchoscope can be used to examine the mucosal surface of the airways for abnormalities associated with a variety of lung diseases. The diagnosis of these abnormalities through the process of bronchoscopy is based, in part, on changes in airway wall color. Therefore it is important to characterize the normal color inside the airways. We propose a standardized method to calibrate the bronchoscopic imaging system and to tabulate the normal colors of the airway. Our imaging system consists of a Pentium PC and video frame grabber, coupled with a true color bronchoscope. The calibration procedure uses 24 standard color patches. Images of these color patches at three different distances (1, 1.5, and 2 cm) were acquired using the bronchoscope in a darkened room, to assess repeatability and sensitivity to illumination. The images from the bronchoscope are in a device-dependent Red-Green-Blue (RGB) color space, which was converted to a tri-stimulus image and then into a device-independent color space sRGB image by a fixed polynomial transformation. Images were acquired from five normal human volunteer subjects, two cystic fibrosis (CF) patients and one normal heavy smoker subject. The hue and saturation values of regions within the normal airway were tabulated and these values were compared with the values obtained from regions within the airways of the CF patients and the normal heavy smoker. Repeated measurements of the same region in the airways showed no measurable change in hue or saturation.

Effect of instrument settings on liquid-containing lesion images characterized by radiofrequency ultrasound local estimators.

PubMed

Wang, Jian; Kang, Chunsong; Feng, Tinghua; Xue, Jiping; Shi, Kailing; Li, Tingting; Liu, Xiaofang; Wang, Yu

2013-05-01

The purpose of this study was to investigate the effects of ultrasonic instrument gain, transducer frequency, and depth on the color variety and color filling of radiofrequency ultrasonic local estimators (RULES) images which indicated specific physical representation of liquid-containing lesions in order to find the optimal settings for the clinical application of RULES in liquid-containing lesions. Changing the ultrasonic instrument gain, transducer frequency, and depth affected the color filling and color variety of 21 pathologically-confirmed liquid-containing lesion images analyzed by RULES. Blue colored fill dominated the RULES images to represent the liquid-containing lesions. A frequency of 12.5MHz led to red and green colors along the inner edges of the liquid-containing lesions. Changing the gain resulted in significantly different blue colored filling that was highest when the gain was 90 to 100. Changing the frequency also significantly changed the blue color filling, with the highest filling occurring at 12.5MHz. Changing the depth did not affect the blue color filling. The liquid components of the lesions may be identified by their characteristic manifestations in RULES, where color variety is affected by transducer frequency and blue color filling which represent liquid-containing lesions in RULES images is affected by frequency and gain. Copyright © 2012. Published by Elsevier GmbH.

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

NASA Astrophysics Data System (ADS)

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

2009-05-01

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

Berezin-Toeplitz quantization and naturally defined star products for Kähler manifolds

NASA Astrophysics Data System (ADS)

Schlichenmaier, Martin

2018-04-01

For compact quantizable Kähler manifolds the Berezin-Toeplitz quantization schemes, both operator and deformation quantization (star product) are reviewed. The treatment includes Berezin's covariant symbols and the Berezin transform. The general compact quantizable case was done by Bordemann-Meinrenken-Schlichenmaier, Schlichenmaier, and Karabegov-Schlichenmaier. For star products on Kähler manifolds, separation of variables, or equivalently star product of (anti-) Wick type, is a crucial property. As canonically defined star products the Berezin-Toeplitz, Berezin, and the geometric quantization are treated. It turns out that all three are equivalent, but different.

Mobile image based color correction using deblurring

NASA Astrophysics Data System (ADS)

Wang, Yu; Xu, Chang; Boushey, Carol; Zhu, Fengqing; Delp, Edward J.

2015-03-01

Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. The goals of the Technology Assisted Dietary Assessment (TADA) System, developed at Purdue University, is to automatically identify and quantify foods and beverages consumed by utilizing food images acquired with a mobile device. Color correction serves as a critical step to ensure accurate food identification and volume estimation. We make use of a specifically designed color checkerboard (i.e. a fiducial marker) to calibrate the imaging system so that the variations of food appearance under different lighting conditions can be determined. In this paper, we propose an image quality enhancement technique by combining image de-blurring and color correction. The contribution consists of introducing an automatic camera shake removal method using a saliency map and improving the polynomial color correction model using the LMS color space.

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

PubMed Central

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

2013-01-01

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

Clinical skin imaging using color spatial frequency domain imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yang, Bin; Lesicko, John; Moy, Austin J.; Reichenberg, Jason; Tunnell, James W.

2016-02-01

Skin diseases are typically associated with underlying biochemical and structural changes compared with normal tissues, which alter the optical properties of the skin lesions, such as tissue absorption and scattering. Although widely used in dermatology clinics, conventional dermatoscopes don't have the ability to selectively image tissue absorption and scattering, which may limit its diagnostic power. Here we report a novel clinical skin imaging technique called color spatial frequency domain imaging (cSFDI) which enhances contrast by rendering color spatial frequency domain (SFD) image at high spatial frequency. Moreover, by tuning spatial frequency, we can obtain both absorption weighted and scattering weighted images. We developed a handheld imaging system specifically for clinical skin imaging. The flexible configuration of the system allows for better access to skin lesions in hard-to-reach regions. A total of 48 lesions from 31 patients were imaged under 470nm, 530nm and 655nm illumination at a spatial frequency of 0.6mm^(-1). The SFD reflectance images at 470nm, 530nm and 655nm were assigned to blue (B), green (G) and red (R) channels to render a color SFD image. Our results indicated that color SFD images at f=0.6mm-1 revealed properties that were not seen in standard color images. Structural features were enhanced and absorption features were reduced, which helped to identify the sources of the contrast. This imaging technique provides additional insights into skin lesions and may better assist clinical diagnosis.

Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search

PubMed Central

Muhammad, Khan; Baik, Sung Wook

2017-01-01

In recent years, image databases are growing at exponential rates, making their management, indexing, and retrieval, very challenging. Typical image retrieval systems rely on sample images as queries. However, in the absence of sample query images, hand-drawn sketches are also used. The recent adoption of touch screen input devices makes it very convenient to quickly draw shaded sketches of objects to be used for querying image databases. This paper presents a mechanism to provide access to visual information based on users’ hand-drawn partially colored sketches using touch screen devices. A key challenge for sketch-based image retrieval systems is to cope with the inherent ambiguity in sketches due to the lack of colors, textures, shading, and drawing imperfections. To cope with these issues, we propose to fine-tune a deep convolutional neural network (CNN) using augmented dataset to extract features from partially colored hand-drawn sketches for query specification in a sketch-based image retrieval framework. The large augmented dataset contains natural images, edge maps, hand-drawn sketches, de-colorized, and de-texturized images which allow CNN to effectively model visual contents presented to it in a variety of forms. The deep features extracted from CNN allow retrieval of images using both sketches and full color images as queries. We also evaluated the role of partial coloring or shading in sketches to improve the retrieval performance. The proposed method is tested on two large datasets for sketch recognition and sketch-based image retrieval and achieved better classification and retrieval performance than many existing methods. PMID:28859140

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels.

PubMed

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Adaptive pseudo-color enhancement method of weld radiographic images based on HSI color space and self-transformation of pixels

NASA Astrophysics Data System (ADS)

Jiang, Hongquan; Zhao, Yalin; Gao, Jianmin; Gao, Zhiyong

2017-06-01

The radiographic testing (RT) image of a steam turbine manufacturing enterprise has the characteristics of low gray level, low contrast, and blurriness, which lead to a substandard image quality. Moreover, it is not conducive for human eyes to detect and evaluate defects. This study proposes an adaptive pseudo-color enhancement method for weld radiographic images based on the hue, saturation, and intensity (HSI) color space and the self-transformation of pixels to solve these problems. First, the pixel's self-transformation is performed to the pixel value of the original RT image. The function value after the pixel's self-transformation is assigned to the HSI components in the HSI color space. Thereafter, the average intensity of the enhanced image is adaptively adjusted to 0.5 according to the intensity of the original image. Moreover, the hue range and interval can be adjusted according to personal habits. Finally, the HSI components after the adaptive adjustment can be transformed to display in the red, green, and blue color space. Numerous weld radiographic images from a steam turbine manufacturing enterprise are used to validate the proposed method. The experimental results show that the proposed pseudo-color enhancement method can improve image definition and make the target and background areas distinct in weld radiographic images. The enhanced images will be more conducive for defect recognition. Moreover, the image enhanced using the proposed method conforms to the human eye visual properties, and the effectiveness of defect recognition and evaluation can be ensured.

Design of a motion JPEG (M/JPEG) adapter card

NASA Astrophysics Data System (ADS)

Lee, D. H.; Sudharsanan, Subramania I.

1994-05-01

In this paper we describe a design of a high performance JPEG (Joint Photographic Experts Group) Micro Channel adapter card. The card, tested on a range of PS/2 platforms (models 50 to 95), can complete JPEG operations on a 640 by 240 pixel image within 1/60 of a second, thus enabling real-time capture and display of high quality digital video. The card accepts digital pixels for either a YUV 4:2:2 or an RGB 4:4:4 pixel bus and has been shown to handle up to 2.05 MBytes/second of compressed data. The compressed data is transmitted to a host memory area by Direct Memory Access operations. The card uses a single C-Cube's CL550 JPEG processor that complies with the baseline JPEG. We give broad descriptions of the hardware that controls the video interface, CL550, and the system interface. Some critical design points that enhance the overall performance of the M/JPEG systems are pointed out. The control of the adapter card is achieved by an interrupt driven software that runs under DOS. The software performs a variety of tasks that include change of color space (RGB or YUV), change of quantization and Huffman tables, odd and even field control and some diagnostic operations.

UltraColor: a new gamut-mapping strategy

NASA Astrophysics Data System (ADS)

Spaulding, Kevin E.; Ellson, Richard N.; Sullivan, James R.

1995-04-01

Many color calibration and enhancement strategies exist for digital systems. Typically, these approaches are optimized to work well with one class of images, but may produce unsatisfactory results for other types of images. For example, a colorimetric strategy may work well when printing photographic scenes, but may give inferior results for business graphic images because of device color gamut limitations. On the other hand, a color enhancement strategy that works well for business graphics images may distort the color reproduction of skintones and other important photographic colors. This paper describes a method for specifying different color mapping strategies in various regions of color space, while providing a mechanism for smooth transitions between the different regions. The method involves a two step process: (1) constraints are applied so some subset of the points in the input color space explicitly specifying the color mapping function; (2) the color mapping for the remainder of the color values is then determined using an interpolation algorithm that preserves continuity and smoothness. The interpolation algorithm that was developed is based on a computer graphics morphing technique. This method was used to develop the UltraColor gamut mapping strategy, which combines a colorimetric mapping for colors with low saturation levels, with a color enhancement technique for colors with high saturation levels. The result is a single color transformation that produces superior quality for all classes of imagery. UltraColor has been incorporated in several models of Kodak printers including the Kodak ColorEase PS and the Kodak XLS 8600 PS thermal dye sublimation printers.

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

PubMed

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

Color Based Bags-of-Emotions

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.

A Binary Planet in Color

NASA Image and Video Library

2015-07-23

This image from NASA New Horizons highlights the contrasting appearance of the two worlds: Charon is mostly gray, with a dark reddish polar cap, while Pluto shows a wide variety of subtle color variations. Pluto and Charon are shown in enhanced color in this image, which is the highest-resolution color image of the pair so far returned to Earth by New Horizons. It was taken at 06:49 UT on July 14, 2015, five hours before Pluto closest approach, from a range of 150,000 miles (250,000 kilometers), with the spacecraft's Ralph instrument. The image highlights the contrasting appearance of the two worlds: Charon is mostly gray, with a dark reddish polar cap, while Pluto shows a wide variety of subtle color variations, including yellowish patches on the north polar cap and subtly contrasting colors for the two halves of Pluto's "heart," informally named Tombaugh Regio, seen in the upper right quadrant of the image. In order to fit Pluto and Charon in the same frame in their correct relative positions, the image has been rotated so the north pole on both Pluto and Charon is pointing towards the upper left. The image was made with the blue, red, and near-infrared color filters of Ralph's Multispectral Visible Imaging Camera, and shows colors that are similar, but not identical, to what would be seen with the human eye, which is sensitive to a narrower range of wavelengths. http://photojournal.jpl.nasa.gov/catalog/PIA19856

Interpretation of the rainbow color scale for quantitative medical imaging: perceptually linear color calibration (CSDF) versus DICOM GSDF

NASA Astrophysics Data System (ADS)

Chesterman, Frédérique; Manssens, Hannah; Morel, Céline; Serrell, Guillaume; Piepers, Bastian; Kimpe, Tom

2017-03-01

Medical displays for primary diagnosis are calibrated to the DICOM GSDF1 but there is no accepted standard today that describes how display systems for medical modalities involving color should be calibrated. Recently the Color Standard Display Function3,4 (CSDF), a calibration using the CIEDE2000 color difference metric to make a display as perceptually linear as possible has been proposed. In this work we present the results of a first observer study set up to investigate the interpretation accuracy of a rainbow color scale when a medical display is calibrated to CSDF versus DICOM GSDF and a second observer study set up to investigate the detectability of color differences when a medical display is calibrated to CSDF, DICOM GSDF and sRGB. The results of the first study indicate that the error when interpreting a rainbow color scale is lower for CSDF than for DICOM GSDF with statistically significant difference (Mann-Whitney U test) for eight out of twelve observers. The results correspond to what is expected based on CIEDE2000 color differences between consecutive colors along the rainbow color scale for both calibrations. The results of the second study indicate a statistical significant improvement in detecting color differences when a display is calibrated to CSDF compared to DICOM GSDF and a (non-significant) trend indicating improved detection for CSDF compared to sRGB. To our knowledge this is the first work that shows the added value of a perceptual color calibration method (CSDF) in interpreting medical color images using the rainbow color scale. Improved interpretation of the rainbow color scale may be beneficial in the area of quantitative medical imaging (e.g. PET SUV, quantitative MRI and CT and doppler US), where a medical specialist needs to interpret quantitative medical data based on a color scale and/or detect subtle color differences and where improved interpretation accuracy and improved detection of color differences may contribute to a better diagnosis. Our results indicate that for diagnostic applications involving both grayscale and color images, CSDF should be chosen over DICOM GSDF and sRGB as it assures excellent detection for color images and at the same time maintains DICOM GSDF for grayscale images.

Halftoning and Image Processing Algorithms

DTIC Science & Technology

1999-02-01

screening techniques with the quality advantages of error diffusion in the half toning of color maps, and on color image enhancement for halftone ...image quality. Our goals in this research were to advance the understanding in image science for our new halftone algorithm and to contribute to...image retrieval and noise theory for such imagery. In the field of color halftone printing, research was conducted on deriving a theoretical model of our

Color Image Restoration Using Nonlocal Mumford-Shah Regularizers

NASA Astrophysics Data System (ADS)

Jung, Miyoun; Bresson, Xavier; Chan, Tony F.; Vese, Luminita A.

We introduce several color image restoration algorithms based on the Mumford-Shah model and nonlocal image information. The standard Ambrosio-Tortorelli and Shah models are defined to work in a small local neighborhood, which are sufficient to denoise smooth regions with sharp boundaries. However, textures are not local in nature and require semi-local/non-local information to be denoised efficiently. Inspired from recent work (NL-means of Buades, Coll, Morel and NL-TV of Gilboa, Osher), we extend the standard models of Ambrosio-Tortorelli and Shah approximations to Mumford-Shah functionals to work with nonlocal information, for better restoration of fine structures and textures. We present several applications of the proposed nonlocal MS regularizers in image processing such as color image denoising, color image deblurring in the presence of Gaussian or impulse noise, color image inpainting, and color image super-resolution. In the formulation of nonlocal variational models for the image deblurring with impulse noise, we propose an efficient preprocessing step for the computation of the weight function w. In all the applications, the proposed nonlocal regularizers produce superior results over the local ones, especially in image inpainting with large missing regions. Experimental results and comparisons between the proposed nonlocal methods and the local ones are shown.

Effects of the Earth’s atmosphere and human neural processing of light on the apparent colors of stars

NASA Astrophysics Data System (ADS)

Savino, Michael; Comins, Neil Francis

2015-01-01

The aim of this study is to develop a mathematical algorithm for quantifying the perceived colors of stars as viewed from the surface of the Earth across a wide range of possible atmospheric conditions. These results are then used to generate color-corrected stellar images. As a first step, optics corrections are calculated to adjust for the CCD bias and the transmission curves of any filters used during image collection. Next, corrections for atmospheric scattering and absorption are determined for the atmospheric conditions during imaging by utilizing the Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS). These two sets of corrections are then applied to a series of reference spectra, which are then weighted against the CIE 1931 XYZ color matching functions before being mapped onto the sRGB color space, in order to determine a series of reference colors against which the original image will be compared. Each pixel of the image is then re-colored based upon its closest corresponding reference spectrum so that the final image output closely matches, in color, what would be seen by the human eye above the Earth's atmosphere. By comparing against the reference spectrum, the stellar classification for each star in the image can also be determined. An observational experiment is underway to test the accuracy of these calculations.

Uranus Rings in False Color

NASA Technical Reports Server (NTRS)

1986-01-01

This false-color view of the rings of Uranus was made from images taken by Voyager 2 on Jan. 21, 1986, from a distance of 4.17 million kilometers (2.59 million miles). All nine known rings are visible here; the somewhat fainter, pastel lines seen between them are contributed by the computer enhancement. Six 15-second narrow-angle images were used to extract color information from the extremely dark and faint rings. Two images each in the green, clear and violet filters were added together and averaged to find the proper color differences between the rings. The final image was made from these three color averages and represents an enhanced, false-color view. The image shows that the brightest, or epsilon, ring at top is neutral in color, with the fainter eight other rings showing color differences between them. Moving down, toward Uranus, we see the delta, gamma and eta rings in shades of blue and green; the beta and alpha rings in somewhat lighter tones; and then a final set of three, known simply as the 4, 5 and 6 rings, in faint off-white tones. Scientists will use this color information to try to understand the nature and origin of the ring material. The resolution of this image is approximately 40 km (25 mi). The Voyager project is managed for NASA by the Jet Propulsion Laboratory.

How daylight influences high-order chromatic descriptors in natural images.

PubMed

Ojeda, Juan; Nieves, Juan Luis; Romero, Javier

2017-07-01

Despite the global and local daylight changes naturally occurring in natural scenes, the human visual system usually adapts quite well to those changes, developing a stable color perception. Nevertheless, the influence of daylight in modeling natural image statistics is not fully understood and has received little attention. The aim of this work was to analyze the influence of daylight changes in different high-order chromatic descriptors (i.e., color volume, color gamut, and number of discernible colors) derived from 350 color images, which were rendered under 108 natural illuminants with Correlated Color Temperatures (CCT) from 2735 to 25,889 K. Results suggest that chromatic and luminance information is almost constant and does not depend on the CCT of the illuminant for values above 14,000 K. Nevertheless, differences between the red-green and blue-yellow image components were found below that CCT, with most of the statistical descriptors analyzed showing local extremes in the range 2950 K-6300 K. Uniform regions and areas of the images attracting observers' attention were also considered in this analysis and were characterized by their patchiness index and their saliency maps. Meanwhile, the results of the patchiness index do not show a clear dependence on CCT, and it is remarkable that a significant reduction in the number of discernible colors (58% on average) was found when the images were masked with their corresponding saliency maps. Our results suggest that chromatic diversity, as defined in terms of the discernible colors, can be strongly reduced when an observer scans a natural scene. These findings support the idea that a reduction in the number of discernible colors will guide visual saliency and attention. Whatever the modeling is mediating the neural representation of natural images, natural image statistics, it is clear that natural image statistics should take into account those local maxima and minima depending on the daylight illumination and the reduction of the number of discernible colors when salient regions are considered.

Europa Stunning Surface

NASA Image and Video Library

2014-11-21

The puzzling, fascinating surface of Jupiter icy moon Europa looms large in this newly-reprocessed [sic] color view, made from images taken by NASA Galileo spacecraft in the late 1990s. This is the color view of Europa from Galileo that shows the largest portion of the moon's surface at the highest resolution. The view was previously released as a mosaic with lower resolution and strongly enhanced color (see PIA02590). To create this new version, the images were assembled into a realistic color view of the surface that approximates how Europa would appear to the human eye. The scene shows the stunning diversity of Europa's surface geology. Long, linear cracks and ridges crisscross the surface, interrupted by regions of disrupted terrain where the surface ice crust has been broken up and re-frozen into new patterns. Color variations across the surface are associated with differences in geologic feature type and location. For example, areas that appear blue or white contain relatively pure water ice, while reddish and brownish areas include non-ice components in higher concentrations. The polar regions, visible at the left and right of this view, are noticeably bluer than the more equatorial latitudes, which look more white. This color variation is thought to be due to differences in ice grain size in the two locations. Images taken through near-infrared, green and violet filters have been combined to produce this view. The images have been corrected for light scattered outside of the image, to provide a color correction that is calibrated by wavelength. Gaps in the images have been filled with simulated color based on the color of nearby surface areas with similar terrain types. This global color view consists of images acquired by the Galileo Solid-State Imaging (SSI) experiment on the spacecraft's first and fourteenth orbits through the Jupiter system, in 1995 and 1998, respectively. Image scale is 1 mile (1.6 kilometers) per pixel. North on Europa is at right. http://photojournal.jpl.nasa.gov/catalog/PIA19048

Asymmetric color image encryption based on singular value decomposition

NASA Astrophysics Data System (ADS)

Yao, Lili; Yuan, Caojin; Qiang, Junjie; Feng, Shaotong; Nie, Shouping

2017-02-01

A novel asymmetric color image encryption approach by using singular value decomposition (SVD) is proposed. The original color image is encrypted into a ciphertext shown as an indexed image by using the proposed method. The red, green and blue components of the color image are subsequently encoded into a complex function which is then separated into U, S and V parts by SVD. The data matrix of the ciphertext is obtained by multiplying orthogonal matrices U and V while implementing phase-truncation. Diagonal entries of the three diagonal matrices of the SVD results are abstracted and scrambling combined to construct the colormap of the ciphertext. Thus, the encrypted indexed image covers less space than the original image. For decryption, the original color image cannot be recovered without private keys which are obtained from phase-truncation and the orthogonality of V. Computer simulations are presented to evaluate the performance of the proposed algorithm. We also analyze the security of the proposed system.

Contrast enhancement of bite mark images using the grayscale mixer in ACR in Photoshop®.

PubMed

Evans, Sam; Noorbhai, Suzanne; Lawson, Zoe; Stacey-Jones, Seren; Carabott, Romina

2013-05-01

Enhanced images may improve bite mark edge definition, assisting forensic analysis. Current contrast enhancement involves color extraction, viewing layered images by channel. A novel technique, producing a single enhanced image using the grayscale mix panel within Adobe Camera Raw®, has been developed and assessed here, allowing adjustments of multiple color channels simultaneously. Stage 1 measured RGB values in 72 versions of a color chart image; eight sliders in Photoshop® were adjusted at 25% intervals, all corresponding colors affected. Stage 2 used a bite mark image, and found only red, orange, and yellow sliders had discernable effects. Stage 3 assessed modality preference between color, grayscale, and enhanced images; on average, the 22 survey participants chose the enhanced image as better defined for nine out of 10 bite marks. The study has shown potential benefits for this new technique. However, further research is needed before use in the analysis of bite marks. © 2013 American Academy of Forensic Sciences.

Significance of perceptually relevant image decolorization for scene classification

NASA Astrophysics Data System (ADS)

Viswanathan, Sowmya; Divakaran, Govind; Soman, Kutti Padanyl

2017-11-01

Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

Image Guided Biodistribution and Pharmacokinetic Studies of Theranostics

PubMed Central

Ding, Hong; Wu, Fang

2012-01-01

Image guided technique is playing an increasingly important role in the investigation of the biodistribution and pharmacokinetics of drugs or drug delivery systems in various diseases, especially cancers. Besides anatomical imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), molecular imaging strategy including optical imaging, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) will facilitate the localization and quantization of radioisotope or optical probe labeled nanoparticle delivery systems in the category of theranostics. The quantitative measurement of the bio-distribution and pharmacokinetics of theranostics in the fields of new drug/probe development, diagnosis and treatment process monitoring as well as tracking the brain-blood-barrier (BBB) breaking through by high sensitive imaging method, and the applications of the representative imaging modalities are summarized in this review. PMID:23227121

Clinical applications of computerized thermography

NASA Technical Reports Server (NTRS)

Anbar, Michael

1988-01-01

Computerized or digital, thermography is a rapidly growing diagnostic imaging modality. It has superseded contact thermography and analog imaging thermography which do not allow effective quantization. Medical applications of digital thermography can be classified in two groups: static and dynamic imaging. They can also be classified into macro thermography (resolution greater than 1 mm) and micro thermography (resolution less than 100 microns). Both modalities allow a thermal resolution of 0.1 C. The diagnostic power of images produced by any of these modalities can be augmented by the use of digital image enhancement and image recognition procedures. Computerized thermography has been applied in neurology, cardiovascular and plastic surgery, rehabilitation and sports medicine, psychiatry, dermatology and ophthalmology. Examples of these applications are shown and their scope and limitations are discussed.

Color separation in forensic image processing using interactive differential evolution.

PubMed

Mushtaq, Harris; Rahnamayan, Shahryar; Siddiqi, Areeb

2015-01-01

Color separation is an image processing technique that has often been used in forensic applications to differentiate among variant colors and to remove unwanted image interference. This process can reveal important information such as covered text or fingerprints in forensic investigation procedures. However, several limitations prevent users from selecting the appropriate parameters pertaining to the desired and undesired colors. This study proposes the hybridization of an interactive differential evolution (IDE) and a color separation technique that no longer requires users to guess required control parameters. The IDE algorithm optimizes these parameters in an interactive manner by utilizing human visual judgment to uncover desired objects. A comprehensive experimental verification has been conducted on various sample test images, including heavily obscured texts, texts with subtle color variations, and fingerprint smudges. The advantage of IDE is apparent as it effectively optimizes the color separation parameters at a level indiscernible to the naked eyes. © 2014 American Academy of Forensic Sciences.

Unsupervised color image segmentation using a lattice algebra clustering technique

NASA Astrophysics Data System (ADS)

Urcid, Gonzalo; Ritter, Gerhard X.

2011-08-01

In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

Pluto and Charon in False Color Show Compositional Diversity

NASA Image and Video Library

2015-07-14

This July 13, 2015, image of Pluto and Charon is presented in false colors to make differences in surface material and features easy to see. It was obtained by the Ralph instrument on NASA's New Horizons spacecraft, using three filters to obtain color information, which is exaggerated in the image. These are not the actual colors of Pluto and Charon, and the apparent distance between the two bodies has been reduced for this side-by-side view. The image reveals that the bright heart-shaped region of Pluto includes areas that differ in color characteristics. The western lobe, shaped like an ice-cream cone, appears peach color in this image. A mottled area on the right (east) appears bluish. Even within Pluto's northern polar cap, in the upper part of the image, various shades of yellow-orange indicate subtle compositional differences. The surface of Charon is viewed using the same exaggerated color. The red on the dark northern polar cap of Charon is attributed to hydrocarbon materials including a class of chemical compounds called tholins. The mottled colors at lower latitudes point to the diversity of terrains on Charon. This image was taken at 3:38 a.m. EDT on July 13, one day before New Horizons' closest approach to Pluto. http://photojournal.jpl.nasa.gov/catalog/PIA19707

Semi-automatic mapping for identifying complex geobodies in seismic images

NASA Astrophysics Data System (ADS)

Domínguez-C, Raymundo; Romero-Salcedo, Manuel; Velasquillo-Martínez, Luis G.; Shemeretov, Leonid

2017-03-01

Seismic images are composed of positive and negative seismic wave traces with different amplitudes (Robein 2010 Seismic Imaging: A Review of the Techniques, their Principles, Merits and Limitations (Houten: EAGE)). The association of these amplitudes together with a color palette forms complex visual patterns. The color intensity of such patterns is directly related to impedance contrasts: the higher the contrast, the higher the color intensity. Generally speaking, low impedance contrasts are depicted with low tone colors, creating zones with different patterns whose features are not evident for a 3D automated mapping option available on commercial software. In this work, a workflow for a semi-automatic mapping of seismic images focused on those areas with low-intensity colored zones that may be associated with geobodies of petroleum interest is proposed. The CIE L*A*B* color space was used to perform the seismic image processing, which helped find small but significant differences between pixel tones. This process generated binary masks that bound color regions to low-intensity colors. The three-dimensional-mask projection allowed the construction of 3D structures for such zones (geobodies). The proposed method was applied to a set of digital images from a seismic cube and tested on four representative study cases. The obtained results are encouraging because interesting geobodies are obtained with a minimum of information.

Align and conquer: moving toward plug-and-play color imaging

NASA Astrophysics Data System (ADS)

Lee, Ho J.

1996-03-01

The rapid evolution of the low-cost color printing and image capture markets has precipitated a huge increase in the use of color imagery by casual end users on desktop systems, as opposed to traditional professional color users working with specialized equipment. While the cost of color equipment and software has decreased dramatically, the underlying system-level problems associated with color reproduction have remained the same, and in many cases are more difficult to address in a casual environment than in a professional setting. The proliferation of color imaging technologies so far has resulted in a wide availability of component solutions which work together poorly. A similar situation in the desktop computing market has led to the various `Plug-and-Play' standards, which provide a degree of interoperability between a range of products on disparate computing platforms. This presentation will discuss some of the underlying issues and emerging trends in the desktop and consumer digital color imaging markets.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Low illumination color image enhancement based on improved Retinex

NASA Astrophysics Data System (ADS)

Liao, Shujing; Piao, Yan; Li, Bing

2017-11-01

Low illumination color image usually has the characteristics of low brightness, low contrast, detail blur and high salt and pepper noise, which greatly affected the later image recognition and information extraction. Therefore, in view of the degradation of night images, the improved algorithm of traditional Retinex. The specific approach is: First, the original RGB low illumination map is converted to the YUV color space (Y represents brightness, UV represents color), and the Y component is estimated by using the sampling acceleration guidance filter to estimate the background light; Then, the reflection component is calculated by the classical Retinex formula and the brightness enhancement ratio between original and enhanced is calculated. Finally, the color space conversion from YUV to RGB and the feedback enhancement of the UV color component are carried out.

Visualization of dyed NAPL concentration in transparent porous media using color space components.

PubMed

Kashuk, Sina; Mercurio, Sophia R; Iskander, Magued

2014-07-01

Finding a correlation between image pixel information and non-aqueous phase liquid (NAPL) saturation is an important issue in bench-scale geo-environmental model studies that employ optical imaging techniques. Another concern is determining the best dye color and its optimum concentration as a tracer for use in mapping NAPL zones. Most bench scale flow studies employ monochromatic gray-scale imaging to analyze the concentration of mostly red dyed NAPL tracers in porous media. However, the use of grayscale utilizes a third of the available information in color images, which typically contain three color-space components. In this study, eight color spaces consisting of 24 color-space components were calibrated against dye concentration for three color-dyes. Additionally, multiple color space components were combined to increase the correlation between color-space data and dyed NAPL concentration. This work is performed to support imaging of NAPL migration in transparent synthetic soils representing the macroscopic behavior of natural soils. The transparent soil used in this study consists of fused quartz and a matched refractive index mineral-oil solution that represents the natural aquifer. The objective is to determine the best color dye concentration and ideal color space components for rendering dyed sucrose-saturated fused quartz that represents contamination of the natural aquifer by a dense NAPL (DNAPL). Calibration was achieved for six NAPL zone lengths using 3456 images (24 color space components×3 dyes×48 NAPL combinations) of contaminants within a defined criteria expressed as peak signal to noise ratio. The effect of data filtering was also considered and a convolution average filter is recommended for image conditioning. The technology presented in this paper is fast, accurate, non-intrusive and inexpensive method for quantifying contamination zones using transparent soil models. Copyright © 2014 Elsevier B.V. All rights reserved.

Exploring the use of memory colors for image enhancement

NASA Astrophysics Data System (ADS)

Xue, Su; Tan, Minghui; McNamara, Ann; Dorsey, Julie; Rushmeier, Holly

2014-02-01

Memory colors refer to those colors recalled in association with familiar objects. While some previous work introduces this concept to assist digital image enhancement, their basis, i.e., on-screen memory colors, are not appropriately investigated. In addition, the resulting adjustment methods developed are not evaluated from a perceptual view of point. In this paper, we first perform a context-free perceptual experiment to establish the overall distributions of screen memory colors for three pervasive objects. Then, we use a context-based experiment to locate the most representative memory colors; at the same time, we investigate the interactions of memory colors between different objects. Finally, we show a simple yet effective application using representative memory colors to enhance digital images. A user study is performed to evaluate the performance of our technique.

Physics-based approach to color image enhancement in poor visibility conditions.

PubMed

Tan, K K; Oakley, J P

2001-10-01

Degradation of images by the atmosphere is a familiar problem. For example, when terrain is imaged from a forward-looking airborne camera, the atmosphere degradation causes a loss in both contrast and color information. Enhancement of such images is a difficult task because of the complexity in restoring both the luminance and the chrominance while maintaining good color fidelity. One particular problem is the fact that the level of contrast loss depends strongly on wavelength. A novel method is presented for the enhancement of color images. This method is based on the underlying physics of the degradation process, and the parameters required for enhancement are estimated from the image itself.

A new efficient method for color image compression based on visual attention mechanism

NASA Astrophysics Data System (ADS)

Shao, Xiaoguang; Gao, Kun; Lv, Lily; Ni, Guoqiang

2010-11-01

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

Color image fusion for concealed weapon detection

NASA Astrophysics Data System (ADS)

Toet, Alexander

2003-09-01

Recent advances in passive and active imaging sensor technology offer the potential to detect weapons that are concealed underneath a person's clothing or carried along in bags. Although the concealed weapons can sometimes easily be detected, it can be difficult to perceive their context, due to the non-literal nature of these images. Especially for dynamic crowd surveillance purposes it may be impossible to rapidly asses with certainty which individual in the crowd is the one carrying the observed weapon. Sensor fusion is an enabling technology that may be used to solve this problem. Through fusion the signal of the sensor that depicts the weapon can be displayed in the context provided by a sensor of a different modality. We propose an image fusion scheme in which non-literal imagery can be fused with standard color images such that the result clearly displays the observed weapons in the context of the original color image. The procedure is such that the relevant contrast details from the non-literal image are transferred to the color image without altering the original color distribution of this image. The result is a natural looking color image that fluently combines all details from both input sources. When an observer who performs a dynamic crowd surveillance task, detects a weapon in the scene, he will also be able to quickly determine which person in the crowd is actually carrying the observed weapon (e.g. "the man with the red T-shirt and blue jeans"). The method is illustrated by the fusion of thermal 8-12 μm imagery with standard RGB color images.

Color constancy in dermatoscopy with smartphone

NASA Astrophysics Data System (ADS)

Cugmas, Blaž; Pernuš, Franjo; Likar, Boštjan

2017-12-01

The recent spread of cheap dermatoscopes for smartphones can empower patients to acquire images of skin lesions on their own and send them to dermatologists. Since images are acquired by different smartphone cameras under unique illumination conditions, the variability in colors is expected. Therefore, the mobile dermatoscopic systems should be calibrated in order to ensure the color constancy in skin images. In this study, we have tested a dermatoscope DermLite DL1 basic, attached to Samsung Galaxy S4 smartphone. Under the controlled conditions, jpeg images of standard color patches were acquired and a model between an unknown device-dependent RGB and a deviceindependent Lab color space has been built. Results showed that median and the best color error was 7.77 and 3.94, respectively. Results are in the range of a human eye detection capability (color error ≈ 4) and video and printing industry standards (color error is expected to be between 5 and 6). It can be concluded that a calibrated smartphone dermatoscope can provide sufficient color constancy and can serve as an interesting opportunity to bring dermatologists closer to the patients.

CMEIAS color segmentation: an improved computing technology to process color images for quantitative microbial ecology studies at single-cell resolution.

PubMed

Gross, Colin A; Reddy, Chandan K; Dazzo, Frank B

2010-02-01

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system's uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at http://cme.msu.edu/cmeias/ . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most, thereby strengthening quantitative microscopy-based approaches to advance microbial ecology in situ at individual single-cell resolution.

77 FR 25082 - Picture Permit Imprint Indicia

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-27

... customers to include business-related color images, such as corporate logos, company brand or trademarks, in... including a business-related color image within the permit imprint indicia. When tested, indicia placed in the upper right corner of the mailpiece that contained color images did not impede the Postal Service...

A novel weighted-direction color interpolation

NASA Astrophysics Data System (ADS)

Tao, Jin-you; Yang, Jianfeng; Xue, Bin; Liang, Xiaofen; Qi, Yong-hong; Wang, Feng

2013-08-01

A digital camera capture images by covering the sensor surface with a color filter array (CFA), only get a color sample at pixel location. Demosaicking is a process by estimating the missing color components of each pixel to get a full resolution image. In this paper, a new algorithm based on edge adaptive and different weighting factors is proposed. Our method can effectively suppress undesirable artifacts. Experimental results based on Kodak images show that the proposed algorithm obtain higher quality images compared to other methods in numerical and visual aspects.

Color image processing and vision system for an automated laser paint-stripping system

NASA Astrophysics Data System (ADS)

Hickey, John M., III; Hise, Lawson

1994-10-01

Color image processing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system which could discriminate between substrates of various colors and textures and paints ranging from semi-gloss grays to high gloss red, white and blue (Air Force Thunderbirds). The changing lighting levels produced by the pulsed CO2 laser mandated a vision system that did not require a constant color temperature lighting for reliable image analysis.

Surface-Plasmon Holography with White-Light Illumination

NASA Astrophysics Data System (ADS)

Ozaki, Miyu; Kato, Jun-ichi; Kawata, Satoshi

2011-04-01

The recently emerging three-dimensional (3D) displays in the electronic shops imitate depth illusion by overlapping two parallax 2D images through either polarized glasses that viewers are required to wear or lenticular lenses fixed directly on the display. Holography, on the other hand, provides real 3D imaging, although usually limiting colors to monochrome. The so-called rainbow holograms—mounted, for example, on credit cards—are also produced from parallax images that change color with viewing angle. We report on a holographic technique based on surface plasmons that can reconstruct true 3D color images, where the colors are reconstructed by satisfying resonance conditions of surface plasmon polaritons for individual wavelengths. Such real 3D color images can be viewed from any angle, just like the original object.

Edge enhancement of color images using a digital micromirror device.

PubMed

Di Martino, J Matías; Flores, Jorge L; Ayubi, Gastón A; Alonso, Julia R; Fernández, Ariel; Ferrari, José A

2012-06-01

A method for orientation-selective enhancement of edges in color images is proposed. The method utilizes the capacity of digital micromirror devices to generate a positive and a negative color replica of the image used as input. When both images are slightly displaced and imagined together, one obtains an image with enhanced edges. The proposed technique does not require a coherent light source or precise alignment. The proposed method could be potentially useful for processing large image sequences in real time. Validation experiments are presented.

The quantitative control and matching of an optical false color composite imaging system

NASA Astrophysics Data System (ADS)

Zhou, Chengxian; Dai, Zixin; Pan, Xizhe; Li, Yinxi

1993-10-01

Design of an imaging system for optical false color composite (OFCC) capable of high-precision density-exposure time control and color balance is presented. The system provides high quality FCC image data that can be analyzed using a quantitative calculation method. The quality requirement to each part of the image generation system is defined, and the distribution of satellite remote sensing image information is analyzed. The proposed technology makes it possible to present the remote sensing image data more effectively and accurately.

Video data compression using artificial neural network differential vector quantization

NASA Technical Reports Server (NTRS)

Krishnamurthy, Ashok K.; Bibyk, Steven B.; Ahalt, Stanley C.

1991-01-01

An artificial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Differential Vector Quantization is used to preserve edge features, and a new adaptive algorithm, known as Frequency-Sensitive Competitive Learning, is used to develop the vector quantizer codebook. To develop real time performance, a custom Very Large Scale Integration Application Specific Integrated Circuit (VLSI ASIC) is being developed to realize the associative memory functions needed in the vector quantization algorithm. By using vector quantization, the need for Huffman coding can be eliminated, resulting in superior performance against channel bit errors than methods that use variable length codes.

Quantization and fractional quantization of currents in periodically driven stochastic systems. I. Average currents

NASA Astrophysics Data System (ADS)

Chernyak, Vladimir Y.; Klein, John R.; Sinitsyn, Nikolai A.

2012-04-01

This article studies Markovian stochastic motion of a particle on a graph with finite number of nodes and periodically time-dependent transition rates that satisfy the detailed balance condition at any time. We show that under general conditions, the currents in the system on average become quantized or fractionally quantized for adiabatic driving at sufficiently low temperature. We develop the quantitative theory of this quantization and interpret it in terms of topological invariants. By implementing the celebrated Kirchhoff theorem we derive a general and explicit formula for the average generated current that plays a role of an efficient tool for treating the current quantization effects.

Self-Organizing-Map Program for Analyzing Multivariate Data

NASA Technical Reports Server (NTRS)

Li, P. Peggy; Jacob, Joseph C.; Block, Gary L.; Braverman, Amy J.

2005-01-01

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras.

PubMed

Zheng, Lei; Lukac, Rastislav; Wu, Xiaolin; Zhang, David

2009-04-01

Single-sensor digital color cameras use a process called color demosiacking to produce full color images from the data captured by a color filter array (CAF). The quality of demosiacked images is degraded due to the sensor noise introduced during the image acquisition process. The conventional solution to combating CFA sensor noise is demosiacking first, followed by a separate denoising processing. This strategy will generate many noise-caused color artifacts in the demosiacking process, which are hard to remove in the denoising process. Few denoising schemes that work directly on the CFA images have been presented because of the difficulties arisen from the red, green and blue interlaced mosaic pattern, yet a well-designed "denoising first and demosiacking later" scheme can have advantages such as less noise-caused color artifacts and cost-effective implementation. This paper presents a principle component analysis (PCA)-based spatially-adaptive denoising algorithm, which works directly on the CFA data using a supporting window to analyze the local image statistics. By exploiting the spatial and spectral correlations existing in the CFA image, the proposed method can effectively suppress noise while preserving color edges and details. Experiments using both simulated and real CFA images indicate that the proposed scheme outperforms many existing approaches, including those sophisticated demosiacking and denoising schemes, in terms of both objective measurement and visual evaluation.

Spatio-spectral color filter array design for optimal image recovery.

PubMed

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Recognition of simulated cyanosis by color-vision-normal and color-vision-deficient subjects.

PubMed

Dain, Stephen J

2014-04-01

There are anecdotal reports that the recognition of cyanosis is difficult for some color-deficient observers. The chromaticity changes of blood with oxygenation in vitro lie close to the dichromatic confusion lines. The chromaticity changes of lips and nail beds measured in vivo are also generally aligned in the same way. Experiments involving visual assessment of cyanosis in vivo are fraught with technical and ethical difficulties A single lower face image of a healthy individual was digitally altered to produce levels of simulated cyanosis. The color change is essentially one of saturation. Some images with other color changes were also included to ensure that there was no propensity to identify those as cyanosed. The images were assessed for reality by a panel of four instructors from the NSW Ambulance Service training section. The images were displayed singly and the observer was required to identify if the person was cyanosed or not. Color normal subjects comprised 32 experienced ambulance officers and 27 new recruits. Twenty-seven color deficient subjects (non-NSW Ambulance Service) were examined. The recruits were less accurate and slower at identifying the cyanosed images and the color vision deficient were less accurate and slower still. The identification of cyanosis is a skill that improves with training and is adversely affected in color deficient observers.

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.

Use of fluorescent proteins and color-coded imaging to visualize cancer cells with different genetic properties.

PubMed

Hoffman, Robert M

2016-03-01

Fluorescent proteins are very bright and available in spectrally-distinct colors, enable the imaging of color-coded cancer cells growing in vivo and therefore the distinction of cancer cells with different genetic properties. Non-invasive and intravital imaging of cancer cells with fluorescent proteins allows the visualization of distinct genetic variants of cancer cells down to the cellular level in vivo. Cancer cells with increased or decreased ability to metastasize can be distinguished in vivo. Gene exchange in vivo which enables low metastatic cancer cells to convert to high metastatic can be color-coded imaged in vivo. Cancer stem-like and non-stem cells can be distinguished in vivo by color-coded imaging. These properties also demonstrate the vast superiority of imaging cancer cells in vivo with fluorescent proteins over photon counting of luciferase-labeled cancer cells.

Seed viability detection using computerized false-color radiographic image enhancement

NASA Technical Reports Server (NTRS)

Vozzo, J. A.; Marko, Michael

1994-01-01

Seed radiographs are divided into density zones which are related to seed germination. The seeds which germinate have densities relating to false-color red. In turn, a seed sorter may be designed which rejects those seeds not having sufficient red to activate a gate along a moving belt containing the seed source. This results in separating only seeds with the preselected densities representing biological viability lending to germination. These selected seeds demand a higher market value. Actual false-coloring isn't required for a computer to distinguish the significant gray-zone range. This range can be predetermined and screened without the necessity of red imaging. Applying false-color enhancement is a means of emphasizing differences in densities of gray within any subject from photographic, radiographic, or video imaging. Within the 0-255 range of gray levels, colors can be assigned to any single level or group of gray levels. Densitometric values then become easily recognized colors which relate to the image density. Choosing a color to identify any given density allows separation by morphology or composition (form or function). Additionally, relative areas of each color are readily available for determining distribution of that density by comparison with other densities within the image.

Image quality analysis of a color LCD as well as a monochrome LCD using a Foveon color CMOS camera

NASA Astrophysics Data System (ADS)

Dallas, William J.; Roehrig, Hans; Krupinski, Elizabeth A.

2007-09-01

We have combined a CMOS color camera with special software to compose a multi-functional image-quality analysis instrument. It functions as a colorimeter as well as measuring modulation transfer functions (MTF) and noise power spectra (NPS). It is presently being expanded to examine fixed-pattern noise and temporal noise. The CMOS camera has 9 μm square pixels and a pixel matrix of 2268 x 1512 x 3. The camera uses a sensor that has co-located pixels for all three primary colors. We have imaged sections of both a color and a monochrome LCD monitor onto the camera sensor with LCD-pixel-size to camera-pixel-size ratios of both 12:1 and 17.6:1. When used as an imaging colorimeter, each camera pixel is calibrated to provide CIE color coordinates and tristimulus values. This capability permits the camera to simultaneously determine chromaticity in different locations on the LCD display. After the color calibration with a CS-200 colorimeter the color coordinates of the display's primaries determined from the camera's luminance response are very close to those found from the CS-200. Only the color coordinates of the display's white point were in error. For calculating the MTF a vertical or horizontal line is displayed on the monitor. The captured image is color-matrix preprocessed, Fourier transformed then post-processed. For NPS, a uniform image is displayed on the monitor. Again, the image is pre-processed, transformed and processed. Our measurements show that the horizontal MTF's of both displays have a larger negative slope than that of the vertical MTF's. This behavior indicates that the horizontal MTF's are poorer than the vertical MTF's. However the modulations at the Nyquist frequency seem lower for the color LCD than for the monochrome LCD. The spatial noise of the color display in both directions is larger than that of the monochrome display. Attempts were also made to analyze the total noise in terms of spatial and temporal noise by applying subtractions of images taken at exactly the same exposure. Temporal noise seems to be significantly lower than spatial noise.

Local adaptive contrast enhancement for color images

NASA Astrophysics Data System (ADS)

Dijk, Judith; den Hollander, Richard J. M.; Schavemaker, John G. M.; Schutte, Klamer

2007-04-01

A camera or display usually has a smaller dynamic range than the human eye. For this reason, objects that can be detected by the naked eye may not be visible in recorded images. Lighting is here an important factor; improper local lighting impairs visibility of details or even entire objects. When a human is observing a scene with different kinds of lighting, such as shadows, he will need to see details in both the dark and light parts of the scene. For grey value images such as IR imagery, algorithms have been developed in which the local contrast of the image is enhanced using local adaptive techniques. In this paper, we present how such algorithms can be adapted so that details in color images are enhanced while color information is retained. We propose to apply the contrast enhancement on color images by applying a grey value contrast enhancement algorithm to the luminance channel of the color signal. The color coordinates of the signal will remain the same. Care is taken that the saturation change is not too high. Gamut mapping is performed so that the output can be displayed on a monitor. The proposed technique can for instance be used by operators monitoring movements of people in order to detect suspicious behavior. To do this effectively, specific individuals should both be easy to recognize and track. This requires optimal local contrast, and is sometimes much helped by color when tracking a person with colored clothes. In such applications, enhanced local contrast in color images leads to more effective monitoring.

Improving color constancy by discounting the variation of camera spectral sensitivity

NASA Astrophysics Data System (ADS)

Gao, Shao-Bing; Zhang, Ming; Li, Chao-Yi; Li, Yong-Jie

2017-08-01

It is an ill-posed problem to recover the true scene colors from a color biased image by discounting the effects of scene illuminant and camera spectral sensitivity (CSS) at the same time. Most color constancy (CC) models have been designed to first estimate the illuminant color, which is then removed from the color biased image to obtain an image taken under white light, without the explicit consideration of CSS effect on CC. This paper first studies the CSS effect on illuminant estimation arising in the inter-dataset-based CC (inter-CC), i.e., training a CC model on one dataset and then testing on another dataset captured by a distinct CSS. We show the clear degradation of existing CC models for inter-CC application. Then a simple way is proposed to overcome such degradation by first learning quickly a transform matrix between the two distinct CSSs (CSS-1 and CSS-2). The learned matrix is then used to convert the data (including the illuminant ground truth and the color biased images) rendered under CSS-1 into CSS-2, and then train and apply the CC model on the color biased images under CSS-2, without the need of burdensome acquiring of training set under CSS-2. Extensive experiments on synthetic and real images show that our method can clearly improve the inter-CC performance for traditional CC algorithms. We suggest that by taking the CSS effect into account, it is more likely to obtain the truly color constant images invariant to the changes of both illuminant and camera sensors.

Purple Mountain Majesty

NASA Image and Video Library

2015-07-15

NASA Mars Reconnaissance Orbite observed this image of an isolated mountain in the Southern highlands reveals a large exposure of purplish bedrock. Since HiRISE color is shifted to longer wavelengths than visible color and given relative stretches, this really means that the bedrock is roughly dark in the broad red bandpass image compared to the blue-green and near-infrared bandpass images. In the RGB (red-green-blue) color image, which excludes the near-infrared bandpass image, the bedrock appears bluish in color. This small mountain is located near the northeastern rim of the giant Hellas impact basin, and could be impact ejecta. http://photojournal.jpl.nasa.gov/catalog/PIA19854