Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.

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Image quality assessment: from error visibility to structural similarity

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Introduction to a Transient World. Fourier Kingdom. Discrete Revolution. Time Meets Frequency. Frames. Wavelet Zoom. Wavelet Bases. Wavelet Packet and Local Cosine Bases. An Approximation Tour. Estimations are Approximations. Transform Coding. Appendix A: Mathematical Complements. Appendix B: Software Toolboxes.

http://ahvazdownload.persiangig.com/document/article/39.pdf

A wavelet tour of signal processing

A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

Mean shift: a robust approach toward feature space analysis

Publisher Summary This chapter focuses on the modern notion of short-term memory, called working memory. Working memory refers to the temporary maintenance of information that was just experienced or just retrieved from long-term memory but no longer exists in the external environment. These internal representations are short-lived, but can be maintained for longer periods of time through active rehearsal strategies, and can be subjected to various operations that manipulate the information in such a way that makes it useful for goal-directed behavior. Working memory is a system that is critically important in cognition and seems necessary in the course of performing many other cognitive functions, such as reasoning, language comprehension, planning, and spatial processing. This chapter demonstrates the functional importance of dopamine to working memory function in several ways. Elucidation of the cognitive and neural mechanisms underlying human working memory is an important focus of cognitive neuroscience and neurology for much of the past decade. One conclusion that arises from research is that working memory, a faculty that enables temporary storage and manipulation of information in the service of behavioral goals, can be viewed as neither a unitary, nor a dedicated system. Data from numerous neuropsychological and neurophysiological studies in animals and humans demonstrates that a network of brain regions, including the prefrontal cortex, is critical for the active maintenance of internal representations.

Chapter 11 Working memory

During binocular rivalry, two incompatible monocular images compete for perceptual dominance, with one pattern temporarily suppressed from conscious awareness We measured fMRI signals in early visual cortex while subjects viewed rival dichoptic images of two different contrasts; the contrast difference served as a 'tag' for the neuronal representations of the two monocular images Activity in primary visual cortex (V1) increased when subjects perceived the higher contrast pattern and decreased when subjects perceived the lower contrast pattern These fluctuations in V1 activity during rivalry were about 55% as large as those evoked by alternately presenting the two monocular images without rivalry The rivalry-related fluctuations in V1 activity were roughly equal to those observed in other visual areas (V2, V3, V3a and V4v) These results challenge the view that the neuronal mechanisms responsible for binocular rivalry occur primarily in later visual areas

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Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry.

In this paper, we present a perceptual distortion measure that predicts image integrity far better than mean-squared error. This perceptual distortion measure is based an a model of human visual processing that fits empirical measurements of the psychophysics of spatial pattern detection. The model of human visual processing proposed involves two major components: a steerable pyramid transform and contrast normalization. We also illustrate the usefulness of the model in predicting perceptual distortion in real images. >

Perceptual image distortion

Functional magnetic resonance imaging (fMRI) was used to measure activity in human parietal cortex during performance of a visual detection task in which the focus of attention systematically traversed the visual field. Critically, the stimuli were identical on all trials (except for slight contrast changes in a fully randomized selection of the target locations) whereas only the cued location varied. Traveling waves of activity were observed in posterior parietal cortex consistent with shifts in covert attention in the absence of eye movements. The temporal phase of the fMRI signal in each voxel indicated the corresponding visual field location. Visualization of the distribution of temporal phases on a flattened representation of parietal cortex revealed at least two distinct topographically organized cortical areas within the intraparietal sulcus (IPS), each representing the contralateral visual field. Two cortical areas were proposed based on this topographic organization, which we refer to as IPS1 and IPS2 to indicate their locations within the IPS. This nomenclature is neutral with respect to possible homologies with well-established cortical areas in the monkey brain. The two proposed cortical areas exhibited relatively little response to passive visual stimulation in comparison with early visual areas. These results provide evidence for multiple topographic maps in human parietal cortex.

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Topographic maps of visual spatial attention in human parietal cortex.

How is color represented by spatially distributed patterns of activity in visual cortex? Functional magnetic resonance imaging responses to several stimulus colors were analyzed with multivariate techniques: conventional pattern classification, a forward model of idealized color tuning, and principal component analysis (PCA). Stimulus color was accurately decoded from activity in V1, V2, V3, V4, and VO1 but not LO1, LO2, V3A/B, or MT+. The conventional classifier and forward model yielded similar accuracies, but the forward model (unlike the classifier) also reliably reconstructed novel stimulus colors not used to train (specify parameters of) the model. The mean responses, averaged across voxels in each visual area, were not reliably distinguishable for the different stimulus colors. Hence, each stimulus color was associated with a unique spatially distributed pattern of activity, presumably reflecting the color selectivity of cortical neurons. Using PCA, a color space was derived from the covariation, across voxels, in the responses to different colors. In V4 and VO1, the first two principal component scores (main source of variation) of the responses revealed a progression through perceptual color space, with perceptually similar colors evoking the most similar responses. This was not the case for any of the other visual cortical areas, including V1, although decoding was most accurate in V1. This dissociation implies a transformation from the color representation in V1 to reflect perceptual color space in V4 and VO1.

https://www.jneurosci.org/content/jneuro/29/44/13992.full.pdf

Decoding and Reconstructing Color from Responses in Human Visual Cortex

As an observer moves and explores the environment, the visual stimulation in his/her eye is constantly changing. Somehow he/she is able to perceive the spatial layout of the scene, and to discern his/her movement through space. Computational vision researchers have been trying to solve this problem for a number of years with only limited success. It is a difficult problem to solve because the optical flow field is nonlinearly related to the 3D motion and depth parameters. Here, we show that the nonlinear equation describing the optical flow field can be split by an exact algebraic manipulation to form three sets of equations. The first set relates the flow field to only the translational component of 3D motion. Thus, depth and rotation need not be known or estimated prior to solving for translation. Once the translation has been recovered, the second set of equations can be used to solve for rotation. Finally, depth can be estimated with the third set of equations, given the recovered translation and rotation. The algorithm applies to the general case of arbitrary motion with respect to an arbitrary scene. It is simple to compute, and it is plausible biologically. The results reported in this article demonstrate the potential of our new approach, and show that it performs favorably when compared with two other well-known algorithms.

David J. Heeger

Papers

Neuronal activity in human primary visual cortex correlates with perception during binocular rivalry.

Perceptual image distortion

Topographic maps of visual spatial attention in human parietal cortex.

Decoding and Reconstructing Color from Responses in Human Visual Cortex

Subspace methods for recovering rigid motion I: algorithm and implementation