Showing papers by "Alan C. Bovik published in 2006"
TL;DR: An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA.
Abstract: Measurement of visual quality is of fundamental importance to numerous image and video processing applications. The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images or videos in a perceptually consistent manner. Image QA algorithms generally interpret image quality as fidelity or similarity with a "reference" or "perfect" image in some perceptual space. Such "full-reference" QA methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychovisual features of the human visual system (HVS), or by signal fidelity measures. In this paper, we approach the image QA problem as an information fidelity problem. Specifically, we propose to quantify the loss of image information to the distortion process and explore the relationship between image information and visual quality. QA systems are invariably involved with judging the visual quality of "natural" images and videos that are meant for "human consumption." Researchers have developed sophisticated models to capture the statistics of such natural signals. Using these models, we previously presented an information fidelity criterion for image QA that related image quality with the amount of information shared between a reference and a distorted image. In this paper, we propose an image information measure that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image. Combining these two quantities, we propose a visual information fidelity measure for image QA. We validate the performance of our algorithm with an extensive subjective study involving 779 images and show that our method outperforms recent state-of-the-art image QA algorithms by a sizeable margin in our simulations. The code and the data from the subjective study are available at the LIVE website.
3,146 citations
TL;DR: This paper presents results of an extensive subjective quality assessment study in which a total of 779 distorted images were evaluated by about two dozen human subjects and is the largest subjective image quality study in the literature in terms of number of images, distortion types, and number of human judgments per image.
Abstract: Measurement of visual quality is of fundamental importance for numerous image and video processing applications, where the goal of quality assessment (QA) algorithms is to automatically assess the quality of images or videos in agreement with human quality judgments. Over the years, many researchers have taken different approaches to the problem and have contributed significant research in this area and claim to have made progress in their respective domains. It is important to evaluate the performance of these algorithms in a comparative setting and analyze the strengths and weaknesses of these methods. In this paper, we present results of an extensive subjective quality assessment study in which a total of 779 distorted images were evaluated by about two dozen human subjects. The "ground truth" image quality data obtained from about 25 000 individual human quality judgments is used to evaluate the performance of several prominent full-reference image quality assessment algorithms. To the best of our knowledge, apart from video quality studies conducted by the Video Quality Experts Group, the study presented in this paper is the largest subjective image quality study in the literature in terms of number of images, distortion types, and number of human judgments per image. Moreover, we have made the data from the study freely available to the research community . This would allow other researchers to easily report comparative results in the future
2,598 citations
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TL;DR: A practical quality-aware image encoding, decoding and quality analysis system, which employs a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.
Abstract: We propose the concept of quality-aware image , in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system, which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.
308 citations
TL;DR: It is demonstrated that even in very noisy displays, observers do not search randomly, but in many cases they deploy their fixations to regions in the stimulus that resemble some aspect of the target in their local image features.
Abstract: Visual search experiments have usually involved the detection of a salient target in the presence of distracters against a blank background. In such high signal-to-noise scenarios, observers have been shown to use visual cues such as color, size, and shape of the target to program their saccades during visual search. The degree to which these features affect search performance is usually measured using reaction times and detection accuracy. We asked whether human observers are able to use target features to succeed in visual search tasks in stimuli with very low signal-to-noise ratios. Using the classification image analysis technique, we investigated whether observers used structural cues to direct their fixations as they searched for simple geometric targets embedded at very low signal-to-noise ratios in noise stimuli that had the spectral characteristics of natural images. By analyzing properties of the noise stimulus at observers’ fixations, we were able to reveal idiosyncratic, target-dependent features used by observers in our visual search task. We demonstrate that even in very noisy displays, observers do not search randomly, but in many cases they deploy their fixations to regions in the stimulus that resemble some aspect of the target in their local image features.
82 citations
TL;DR: Physical properties of spiculated masses can be measured reliably on mammography and the interobserver and intraobserver variability for this task is comparable with that reported for other measurements made on medical images.
Abstract: The goal of this study was to assess the reliability of measurements of the physical characteristics of spiculated masses on mammography The images used in this study were obtained from the Digital Database for Screening Mammography Two experienced radiologists measured the properties of 21 images of spiculated masses The length and width of all spicules and the major axis of the mass were measured In addition, the observers counted the total number of spicules Interobserver and intraobserver variability were evaluated using a hypothesis test for equivalence, the intraclass correlation coefficient (ICC) and Bland-Altman statistics For an equivalence level of 30% of the mean of the senior radiologist's measurement, equivalence was achieved for the measurements of average spicule length (p,001), average spicule width (p5003), the length of the major axis (p,001) and for the count of the number of spicules (p,001) Similarly, with the ICC analysis technique ''excellent'' inter-rater agreement was observed for the measurements of average spicule length (ICC50770), the length of the major axis (ICC50801) and for the count of the number of spicules (ICC50780) ''Fair to good'' agreement was observed for the average spicule width (ICC50561) Equivalence was also demonstrated for intraobserver measurements Physical properties of spiculated masses can be measured reliably on mammography The interobserver and intraobserver variability for this task is comparable with that reported for other measurements made on medical images
72 citations
01 Dec 2006
TL;DR: This paper proposes to use the complex wavelet structural similarity index (CW-SSIM) method to measure the variability in identifying and localizing structures on images and demonstrates the effectiveness and robustness of the method.
Abstract: Inter- and intra-observer variability exists in any measurements made on medical images There are two sources of variability The first occurs when the observers identify and localize the object of interest, and the second happens when the observers make appropriate measurement on the object of interest A number of statistical methods are available to quantify the degree of agreement between measurements made by different observers However, little has been done to develop metrics for quantifying the variability in identifying and localizing the objects of interest prior to measurement In this paper, we propose to use the complex wavelet structural similarity index (CW-SSIM) method to measure the variability in identifying and localizing structures on images Performance comparisons using simulated images as well as real mammography images demonstrate the effectiveness and robustness of the CW-SSIM method
46 citations
TL;DR: A statistical model for estimating the distortion introduced in progressive JPEG compressed images due to both quantization and channel bit errors, which shows that the distortion in terms of peak signal to noise ratio can be predicted within a 2 dB maximum error.
Abstract: 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.
41 citations
01 Dec 2006
TL;DR: A perceptual distortion metric-the structural similarity (SSIM) index is used to derive a new linear estimator for estimating zero-mean Gaussian sources distorted by additive white Gaussian noise (AWGN), which clearly outperforms the LLSE estimator in terms of the visual quality of the denoised images.
Abstract: We use a perceptual distortion metric -the structural similarity (SSIM) index, to derive a new linear estimator for estimating zero-mean Gaussian sources distorted by additive white Gaussian noise (AWGN). We use this estimator in an image denoising application and compare its performance with the traditional linear least squared error (LLSE) estimator. Although images denoised using the SSIM-optimized estimator have a lower peak signal-to-noise ratio (PSNR) compared to their LLSE couterparts, the SSIM-optimized estimator clearly outperforms the LLSE estimator in terms of the visual quality of the denoised images.
34 citations
01 Dec 2006
TL;DR: A novel unsupervised classification method based on fuzzy logic classification and a prior adjusted reclassification method for m-fish classification that combines both spectral and edge information is presented.
Abstract: Multicolor fluorescence in-situ hybridization (m-fish) technique provides color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole human chromosomes. Currently available m-fish systems exhibit misclassifications of multiple pixel regions that are often larger than the actual chromosomal rearrangement. This paper presents a novel unsupervised classification method based on fuzzy logic classification and a prior adjusted reclassification method. Utilizing the chromosome boundaries, the initial classification results improved significantly after the prior adjusted reclassification while keeping the translocations intact. This paper also presents a new segmentation method that combines both spectral and edge information. Ten m-fish images from a publicly available database were used to test our methods. The segmentation accuracy was more than 98% on average.
29 citations
01 Jan 2006
TL;DR: A novel decomposition method for overlapping and touching chromosomes in M-FISH images is presented and it is shown that about 90% of accuracy was obtained for two or three chromosome clusters, which consist about 95% of all clusters with two or more chromosomes.
Abstract: Since the birth of chromosome analysis by the aid of computers, building a fully automated chromosome analysis system has been the ultimate goal. Along with many other challenges, automating chromosome classification and segmentation has been one of the major challenges especially due to overlapping and touching chromosomes. In this paper we present a novel decomposition method for overlapping and touching chromosomes in M-FISH images. To overcome the limited success of previous decomposition methods that use partial information about a chromosome cluster, we have incorporated more knowledge about the clusters into a maximum-likelihood frame work. The proposed method evaluates multiple hypotheses based on geometric information, pixel classification results, and chromosome sizes, and a hypothesis that has a maximum-likelihood is chosen as the best decomposition of a given cluster. About 90% of accuracy was obtained for two or three chromosome clusters, which consist about 95% of all clusters with two or more chromosomes.
24 citations
06 Apr 2006
TL;DR: This work introduces a novel method of extending the depth-of-field by fusing several optical sections in the wavelet domain using multiscale point-wise product (MPP) criteria and indicates both qualitatively and quantitatively that it outperforms existing schemes in the literature.
Abstract: Imaging specimens thicker than the depth-of-field of a microscope produces poor quality images as only a portion of the specimen is in focus. Therefore, even in the best focused image, there are always objects that are out of focus and thus blurred. It is difficult to accurately measure the size, shape, and boundary of a blurred object. As a result, several optical sections are often required to estimate accurately the entire intensity distribution of the specimen. To overcome this problem, we introduce a novel method of extending the depth-of-field by fusing several optical sections in the wavelet domain using multiscale point-wise product (MPP) criteria. Most existing fusion methods rely on criteria that are merely based on edges and do not distinguish signals from noise. However, our MPP criteria ensures that the signal content, rather than the noise, is collected. Instead of directly fusing optical sections, we preprocess the images by performing adjacent plane deblurring that removes blurred content and preserves the in-focus objects. The overall scheme provides superior quality images with extended depth-of-field and yet the fused images are insensitive to noise. The experimental results indicate both qualitatively and quantitatively that our approach outperforms existing schemes in the literature.
15 Jan 2006
TL;DR: A new approach to finding corners in images that combines foveated edge detection and curvature calculation with saccadic placement of foveal fixations is developed and results show that the algorithm is a good locator of corners.
Abstract: We develop a new approach to finding corners in images that combines foveated edge detection and curvature calculation with saccadic placement of foveal fixations. Each saccade moves the fovea to a location of high curvature combined with high edge gradient. Edges are located using a foveated Canny edge detector with spatial constant that increases with eccentricity. Next, we calculate a measure of local corner strength , based on a product of curvature and gradient. An inhibition factor based on previous visits to a region of the image prevents the system from repeatedly returning to the same locale. A long saccade is move thes fovea to previously unexplored areas of the image. Subsequent short saccades improve the accuracy of the location of the corner approximated by the long saccade. The system is tested on two natural scenes and the results compared against subjects observing the same test images through an eyetracker. Results show that the algorithm is a good locator of corners.
14 May 2006
TL;DR: It is shown that unmodulated versions of these filters can be used to detect the central mass region of spiculated masses in mammography using toroidal Gaussian filters.
Abstract: We have invented a new class of linear filters for the detection of spiculated masses and architectural distortions in mammography. We call these Spiculation Filters. These filters are narrow band filters and form a new class of wavelet-type filter banks. In this paper, we show that unmodulated versions of these filters can be used to detect the central mass region of spiculated masses. We refer to these as toroidal gaussian filters. We also show that the physical properties of spiculated masses can be extracted from the responses of the toroidal gaussian filters without segmentation.
14 May 2006
TL;DR: This model takes into account important aspects of video compression such as transform coding, motion compensation, and variable length coding and estimates distortion within 1 dB of actual simulation values in terms of peak-signal-to-noise-ratio.
Abstract: Joint source-channel coding is becoming more important for wireless multimedia transmission due to high bandwidth requirements of these multimedia sources. Design of all joint source-channel coding schemes require an estimate of distortion at different source coding rates and under different channel conditions. In this paper, we present one such distortion model for estimating distortion due to quantization and channel errors in a joint manner for MPEG-4 compressed video streams. This model takes into account important aspects of video compression such as transform coding, motion compensation, and variable length coding. Results show that our model estimates distortion within 1 dB of actual simulation values in terms of peak-signal-to-noise-ratio.
01 Oct 2006
TL;DR: A novel foveated analysis framework is presented, in which features were analyzed at the spatial resolution at which they were perceived, and a new algorithm is presented that selects image regions as likely candidates for fixation.
Abstract: The ability to automatically detect visually interesting regions in images has practical applications in the design of active machine vision systems. Analysis of the statistics of image features at observers gaze can provide insights into the mechanisms of fixation selection in humans. Using a novel foveated analysis framework, in which features were analyzed at the spatial resolution at which they were perceived, we studied the statistics of four low-level local image features: luminance, contrast, center-surround outputs of luminance and contrast, and discovered that the image patches around human fixations had, on average, higher values of each of these features than the image patches selected at random. Center-surround contrast showed the greatest difference between human and random fixations, followed by contrast, center-surround luminance, and luminance. Using these measurements, we present a new algorithm that selects image regions as likely candidates for fixation. These regions are shown to correlate well with fixations recorded from observers.
01 Jan 2006
TL;DR: Compounds satisfying four specific requirements, namely: a log P value in the range of from 2.5 to 6, a molecular structure with at least one carboxyl group, and absence of halo substitution promote absorption of pharmacologically-active substance through the rectum into the bloodstream and are effective to raise the concentration of such active substance in the bloodstream.
Abstract: Compounds satisfying four specific requirements, namely: (1) a log P value in the range of from 2.5 to 6, (2) a molecular structure with at least one carboxyl group, (3) a pKa value for the carboxyl group of not less than 2.5 and (4) absence of halo substitution, and nontoxic salts thereof promote absorption of pharmacologically-active substance through the rectum into the bloodstream and are effective to raise the concentration of such active substance in the bloodstream even when the active substance is usually unabsorbable or absorbable through the rectum only with considerable difficulty. The compounds are combined with pharmacologically-active ingredients, with pharmaceutical bases suitable for rectal administration of drugs and with appropriate combinations of both.