towards a full reference quality assessment for color images using directional statistics this paper presents a novel computational model for quantifying the perceptual quality of color images consistently with subjective evaluations the proposed full reference color metric namely a directional statistics based color similarity index is designed to consistently perform well over commonly encountered chromatic and achromatic distortions in order to accurately predict the visual quality of color images we make use of local color descriptors extracted from three perceptual color channels 1 hue 2 chroma and 3 lightness in particular directional statistical tools are employed to properly process hue data by considering their periodicities moreover two weighting mechanisms are exploited to accurately combine locally measured comparison scores into a final score extensive experimentation performed on large scale databases indicates that the proposed metric is effective across a wide range of chromatic and achromatic distortions making it better suited for the evaluation and optimization of color image processing algorithms

long route to consensus two stage coarsening in a binary choice voting model formation of consensus in binary yes no type of voting is a well defined process however even in presence of clear incentives the dynamics involved can be incredibly complex specifically formations of large groups of similarly opinionated individuals could create a condition of support bubbles or spontaneous polarization that renders consensus virtually unattainable e g the question of the uk exiting the eu there have been earlier attempts in capturing the dynamics of consensus formation in societies through simple z 2 symmetric models hoping to capture the essential dynamics of average behavior of a large number of individuals in a statistical sense however in absence of external noise they tend to reach a frozen state with fragmented and polarized states i e two or more groups of similarly opinionated groups with frozen dynamics here we show in a kinetic exchange opinion model considered on l l square lattices that while such frozen states could be avoided an exponentially slow approach to consensus is manifested specifically the system could either reach consensus in a time that scales as l 2 or a long lived metastable state termed a domain wall state for which formation of consensus takes a time scaling as l 3 6 the latter behavior is comparable to some voterlike models with intermediate states studied previously the late time anomaly in the timescale is reflected in the persistence probability of the model finally the interval of zero crossing of the average opinion i e the time interval over which the average opinion does not change sign is shown to follow a scale free distribution which is compared with that seen in the opinion surveys regarding brexit and associated issues since the late 1970s the issue of minority spreading is also addressed by calculating the exit probability

image difference prediction from color to spectral we propose a new strategy to evaluate the quality of multi and hyperspectral images from the perspective of human perception we define the spectral image difference as the overall perceived difference between two spectral images under a set of specified viewing conditions illuminants first we analyze the stability of seven image difference features across illuminants by means of an information theoretic strategy we demonstrate in particular that in the case of common spectral distortions spectral gamut mapping spectral compression spectral reconstruction chromatic features vary much more than achromatic ones despite considering chromatic adaptation then we propose two computationally efficient spectral image difference metrics and compare them to the results of a subjective visual experiment a significant improvement is shown over existing metrics such as the widely used root mean square error

the spatial distribution of clusters and the formation of mixed languages in bilingual competition abstract we use cellular automata simulation methods to study the competition between two languages language a and b we assume each of the two languages consists of f independent features and define an individual as two f length identity level integer strings the value of each integer of the strings indicates whether the individual is willing or unwilling to express a certain feature and how his willingness or unwillingness is in our model individuals who speak either language a or b are randomly placed on a square lattice initially and programmed to evolve under the communication and interaction methods first we consider the situation that the competition occurs between two languages with only one feature we find the differences between short time coexistence processes and long time coexistence processes and discuss how the spatial distribution of languages evolves we observe that periodic line shaped boundaries take shape in some simulations and lead to long time coexistence between the two languages then we study the multi feature cases when f 10 and find the correlation among the evolution of different features decreases with time we also observe the extinction of two primitive languages and formation of mixed languages

wavelets and filter banks theory and design the wavelet transform is compared with the more classical short time fourier transform approach to signal analysis then the relations between wavelets filter banks and multiresolution signal processing are explored a brief review is given of perfect reconstruction filter banks which can be used both for computing the discrete wavelet transform and for deriving continuous wavelet bases provided that the filters meet a constraint known as regularity given a low pass filter necessary and sufficient conditions for the existence of a complementary high pass filter that will permit perfect reconstruction are derived the perfect reconstruction condition is posed as a bezout identity and it is shown how it is possible to find all higher degree complementary filters based on an analogy with the theory of diophantine equations an alternative approach based on the theory of continued fractions is also given these results are used to design highly regular filter banks which generate biorthogonal continuous wavelet bases with symmetries

effect of zealotry in high dimensional opinion dynamics models most of the work on opinion dynamics models focuses on the case of two or three opinion types we consider the case of an arbitrary number of opinions in the mean field case of the naming game model in which it is assumed the population is infinite and all individuals are neighbors a particular challenge of the naming game model is that the number of variables which corresponds to the number of possible sets of opinions grows exponentially with the number of possible opinions we present a method for generating mean field dynamical equations for the general case of k opinions we calculate the steady states in two important special cases in arbitrarily high dimension the case in which there exist zealots of only one type and the case in which there are an equal number of zealots for each opinion we show that in these special cases a phase transition occurs at critical values p c of the parameter p describing the fraction of zealots in the former case the critical value determines the threshold value beyond which it is not possible for the opinion with no zealots to be held by more nodes than the opinion with zealots and this point remains fixed regardless of dimension in the latter case the critical point p c is the threshold value beyond which a stalemate between all k opinions is guaranteed and we show that it decays precisely as a lognormal curve in k

robust rate control for wavelet based image coding via conditional probability models real time rate control for wavelet image coding requires characterization of the rate required to code quantized wavelet data an ideal robust solution can be used with any wavelet coder and any quantization scheme a large number of wavelet quantization schemes perceptual and otherwise are based on scalar dead zone quantization of wavelet coefficients a key to performing rate control is thus fast accurate characterization of the relationship between rate and quantization step size the r q curve a solution is presented using two invocations of the coder that estimates the slope of each r q curve via probability modeling the method is robust to choices of probability models quantization schemes and wavelet coders because of extreme robustness to probability modeling a fast approximation to spatially adaptive probability modeling can be used in the solution as well with respect to achieving a target rate the proposed approach and associated fast approximation yield average percentage errors around 0 5 and 1 0 on images in the test set by comparison 2 coding pass rho domain modeling yields errors around 2 0 and post compression rate distortion optimization yields average errors of around 1 0 at rates below 0 5 bits per pixel bpp that decrease down to about 0 5 at 1 0 bpp both methods exhibit more competitive performance on the larger images the proposed method and fast approximation approach are also similar in speed to the other state of the art methods in addition to possessing speed and accuracy the proposed method does not require any training and can maintain precise control over wavelet step sizes which adds flexibility to a wavelet based image coding system

regularized gap functions and error bounds for generalized mixed weak vector quasivariational inequality problems in fuzzy environments abstract in this paper we establish gap functions for a new class of generalized mixed weak vector quasivariational inequality problems in fuzzy environments in short mqvipf these functions are constructed through terms of regularized gap functions using the method of nonlinear scalarization functions moreover error bounds are provided for mqvipf via regularized gap functions under suitable assumptions the main results obtained in this paper improve and extend some corresponding known results some examples are given to illustrate our results

application of statistical physics to politics abstract the concept and technics of real space renormalization group are applied to study majority rule voting in hierarchical structures it is found that democratic voting can lead to totalitarianism by keeping in power a small minority conditions of this paradox are analyzed and singled out indeed majority rule produces critical thresholds to absolute power values of these thresholds can vary from 50 up to at least 77 the associated underlying mechanism could provide an explanation for both former apparent eternity of communist leaderships and their sudden collapse

infrequent social interaction can accelerate the spread of a persuasive idea we study the spread of a persuasive new idea through a population of continuous time random walkers in one dimension the idea spreads via social gatherings involving groups of nearby walkers who act according to a biased majority rule after each gathering the group takes on the new idea if more than a critical fraction 1 2 1 2 of them already hold it otherwise they all reject it the boundary of a domain where the new idea has taken hold expands as a traveling wave in the density of new idea holders our walkers move by levy motion and we compute the wave velocity analytically as a function of the frequency of social gatherings and the exponent of the jump distribution when this distribution is sufficiently heavy tailed then counter to intuition the idea can propagate faster if social gatherings are held less frequently when jumps are truncated a critical gathering frequency can emerge which maximizes propagation velocity we explore our model by simulation confirming our analytical results

structural similarity quality metrics in a coding context exploring the space of realistic distortions perceptual image quality metrics have explicitly accounted for human visual system hvs sensitivity to subband noise by estimating just noticeable distortion jnd thresholds a recently proposed class of quality metrics known as structural similarity metrics ssim models perception implicitly by taking into account the fact that the hvs is adapted for extracting structural information from images we evaluate ssim metrics and compare their performance to traditional approaches in the context of realistic distortions that arise from compression and error concealment in video compression transmission applications in order to better explore this space of distortions we propose models for simulating typical distortions encountered in such applications we compare specific ssim implementations both in the image space and the wavelet domain these include the complex wavelet ssim cwssim a translation insensitive ssim implementation we also propose a perceptually weighted multiscale variant of cwssim which introduces a viewing distance dependence and provides a natural way to unify the structural similarity approach with the traditional jnd based perceptual approaches

local interaction scale controls the existence of a nontrivial optimal critical mass in opinion spreading we study a model of opinion formation where the collective decision of a group is said to happen if the fraction of agents having the most common opinion exceeds a threshold value a critical mass we find that there exists a unique nontrivial critical mass giving the most efficient convergence to consensus in addition we observe that for small critical masses the characteristic time scale for the relaxation to consensus splits into two the shorter time scale corresponds to a direct relaxation and the longer one can be explained by the existence of intermediate metastable states similar to those found in p chen and s redner phys rev e 71 036101 2005 this longer time scale is dependent on the precise condition for consensus with a modification of the condition it can go away

dct qm a dct based quality degradation metric for image quality optimization problems recent development of computational image quality assessment methods has shown to give very promising results in measuring perceptual visual quality for distorted images however most of them are difficult to be applied for optimization problems due to the lack of desirable mathematical properties such as differentiability convexity and valid distance metricability this paper proposes a novel discrete cosine transform dct based quality degradation metric called dct qm which is based on the probability summation theory with a psychometric function for neural responses in the receptive fields of visual cortex in psychophysics consequently the dct qm is formulated as a weighted mean text l 2 norm in the dct domain which is very easy to implement and inherits the three desirable mathematical properties that is differentiability convexity and valid distance metricability for image quality optimization problems the extensive experimental results show that the proposed dct qm has promising results for many practical distortion types in image processing problems by showing high consistency with perceived visual quality

biorthogonal bases of compactly supported wavelets orthonormal bases of compactly supported wavelet bases correspond to subband coding schemes with exact reconstruction in which the analysis and synthesis filters coincide we show here that under fairly general conditions exact reconstruction schemes with synthesis filters different from the analysis filters give rise to two dual riesz bases of compactly supported wavelets we give necessary and sufficient conditions for biorthogonality of the corresponding scaling functions and we present a sufficient condition for the decay of their fourier transforms we study the regularity of these biorthogonal bases we provide several families of examples all symmetric corresponding to linear phase filters in particular we can construct symmetric biorthogonal wavelet bases with arbitrarily high preassigned regularity we also show how to construct symmetric biorthogonal wavelet bases close to a nonsymmetric orthonormal basis

upper and lower possibility distributions of fuzzy decision variables in upper level decision problems in this paper a kind of decision problem in upper level decision making systems is formalized by a set of fuzzy satisfaction levels offered by decision makers these fuzzy satisfaction levels leave some feasible region for decision variables the exponential possibility distributions of decision variables are studied to obtain an approximate region for decision variables upper and lower possibility distributions are obtained to represent solutions with different fuzzy degrees in decision making procedure

contrast sensitivity of the wavelet dual tree complex wavelet curvelet and steerable pyramid transforms accurate estimation of the contrast sensitivity of the human visual system is crucial for perceptually based image processing in applications such as compression fusion and denoising conventional contrast sensitivity functions csfs have been obtained using fixed sized gabor functions however the basis functions of multiresolution decompositions such as wavelets often resemble gabor functions but are of variable size and shape therefore to use the conventional csfs in such cases is not appropriate we have therefore conducted a set of psychophysical tests in order to obtain the csf for a range of multiresolution transforms the discrete wavelet transform the steerable pyramid the dual tree complex wavelet transform and the curvelet transform these measures were obtained using contrast variation of each transforms basis functions in a 2afc experiment combined with an adapted version of the quest psychometric function method the results enable future image processing applications that exploit these transforms such as signal fusion superresolution processing denoising and motion estimation to be perceptually optimized in a principled fashion the results are compared with an existing vision model hdr vdp2 and are used to show quantitative improvements within a denoising application compared with using conventional csf values

dynamic contrast based quantization for lossy wavelet image compression this paper presents a contrast based quantization strategy for use in lossy wavelet image compression that attempts to preserve visual quality at any bit rate based on the results of recent psychophysical experiments using near threshold and suprathreshold wavelet subband quantization distortions presented against natural image backgrounds subbands are quantized such that the distortions in the reconstructed image exhibit root mean squared contrasts selected based on image subband and display characteristics and on a measure of total visual distortion so as to preserve the visual system s ability to integrate edge structure across scale space within a single unified framework the proposed contrast based strategy yields images which are competitive in visual quality with results from current visually lossless approaches at high bit rates and which demonstrate improved visual quality over current visually lossy approaches at low bit rates this strategy operates in the context of both nonembedded and embedded quantization the latter of which yields a highly scalable codestream which attempts to maintain visual quality at all bit rates a specific application of the proposed algorithm to jpeg 2000 is presented

vsnr a wavelet based visual signal to noise ratio for natural images this paper presents an efficient metric for quantifying the visual fidelity of natural images based on near threshold and suprathreshold properties of human vision the proposed metric the visual signal to noise ratio vsnr operates via a two stage approach in the first stage contrast thresholds for detection of distortions in the presence of natural images are computed via wavelet based models of visual masking and visual summation in order to determine whether the distortions in the distorted image are visible if the distortions are below the threshold of detection the distorted image is deemed to be of perfect visual fidelity vsnr infin and no further analysis is required if the distortions are suprathreshold a second stage is applied which operates based on the low level visual property of perceived contrast and the mid level visual property of global precedence these two properties are modeled as euclidean distances in distortion contrast space of a multiscale wavelet decomposition and vsnr is computed based on a simple linear sum of these distances the proposed vsnr metric is generally competitive with current metrics of visual fidelity it is efficient both in terms of its low computational complexity and in terms of its low memory requirements and it operates based on physical luminances and visual angle rather than on digital pixel values and pixel based dimensions to accommodate different viewing conditions

histogram based segmentation in a perceptually uniform color space in this work we present a segmentation algorithm for color images that uses the watershed algorithm to segment either the two dimensional 2 d or the three dimensional 3 d color histogram of an image for compliance with the way humans perceive color this segmentation has to take place in a perceptually uniform color space like the luv space to avoid oversegmentation the watershed algorithm has to be applied to a smoothed histogram

image coding using wavelet transform a scheme for image compression that takes into account psychovisual features both in the space and frequency domains is proposed this method involves two steps first a wavelet transform used in order to obtain a set of biorthogonal subclasses of images the original image is decomposed at different scales using a pyramidal algorithm architecture the decomposition is along the vertical and horizontal directions and maintains constant the number of pixels required to describe the image second according to shannon s rate distortion theory the wavelet coefficients are vector quantized using a multiresolution codebook to encode the wavelet coefficients a noise shaping bit allocation procedure which assumes that details at high resolution are less visible to the human eye is proposed in order to allow the receiver to recognize a picture as quickly as possible at minimum cost a progressive transmission scheme is presented it is shown that the wavelet transform is particularly well adapted to progressive transmission

spread spectrum image watermarking based on perceptual quality metric efficient image watermarking calls for full exploitation of the perceptual distortion constraint second order statistics of visual stimuli are regarded as critical features for perception this paper proposes a second order statistics sos based image quality metric which considers the texture masking effect and the contrast sensitivity in karhunen loeve transform domain compared with the state of the art metrics the quality prediction by sos better correlates with several subjectively rated image databases in which the images are impaired by the typical coding and watermarking artifacts with the explicit metric definition spread spectrum watermarking is posed as an optimization problem we search for a watermark to minimize the distortion of the watermarked image and to maximize the correlation between the watermark pattern and the spread spectrum carrier the simple metric guarantees the optimal watermark a closed form solution and a fast implementation the experiments show that the proposed watermarking scheme can take full advantage of the distortion constraint and improve the robustness in return

wavelet tree quantization for copyright protection watermarking this paper proposes a wavelet tree based blind watermarking scheme for copyright protection the wavelet coefficients of the host image are grouped into so called super trees the watermark is embedded by quantizing super trees the trees are so quantized that they exhibit a large enough statistical difference which will later be used for watermark extraction each watermark bit is embedded in perceptually important frequency bands which renders the mark more resistant to frequency based attacks also the watermark is spread throughout large spatial regions this yields more robustness against time domain geometric attacks examples of various attacks will be given to demonstrate the robustness of the proposed technique

color image quality assessment from prediction to optimization while image difference metrics show good prediction performance on visual data they often yield artifact contaminated results if used as objective functions for optimizing complex image processing tasks we investigate in this regard the recently proposed color image difference cid metric particularly developed for predicting gamut mapping distortions we present an algorithm for optimizing gamut mapping employing the cid metric as the objective function resulting images contain various visual artifacts which are addressed by multiple modifications yielding the improved color image difference icid metric the icid based optimizations are free from artifacts and retain contrast structure and color of the original image to a great extent furthermore the prediction performance on visual data is improved by the modifications

portfolio selection based on upper and lower exponential possibility distributions in this paper two kinds of possibility distributions namely upper and lower possibility distributions are identified to reflect experts knowledge in portfolio selection problems portfolio selection models based on these two kinds of distributions are formulated by quadratic programming problems it can be said that a portfolio return based on the lower possibility distribution has smaller possibility spread than the one on the upper possibility distribution in addition a possibility risk can be defined as an interval given by the spreads of the portfolio returns from the upper and the lower possibility distributions to reflect the uncertainty in real investment problems a numerical example of a portfolio selection problem is given to illustrate our proposed approaches

influence of normalization and color space to color texture classification abstract color texture classification has recently attracted significant attention due to its multiple applications the color texture images depend on the texture surface and its albedo the illumination the camera and its viewing position a key problem to get an acceptable performance is the ambient illumination which can vary the perceived structures in the surface given a color texture classification problem it would be desirable to know which is the best approach to solve the problem making the minimal assumptions about the illumination conditions the present work does an exhaustive evaluation of the state of the art color texture classification methods considering 5 different color spaces 12 normalization methods to achieve illumination invariances 19 texture feature vectors and 23 pure color feature vectors our experiments allow to conclude that parallel approaches are better than integrative approaches for color texture classification achieving the first positions in the friedman ranking multiresolution local binary patterns mlbp are the best intensity texture features followed by wavelet and gabor filters combined with luminance chrominance color spaces lab and lab2000hl and for pure color classification the best are first order statistics fos calculated in rgb color space for intensity texture features the learning methods work better on the four smallest datasets although they could not be tested in other four bigger datasets due to its huge computational cost nor with color texture classification normalization and color spaces slightly increase the average accuracy of color texture classification although the differences achieved using normalization are not statistically significant in a paired t test lab2000hl and rgb are the best color spaces but the former is the slowest one regarding elapsed time the best vector features mlbp for intensity texture daub4 daubechies filters using mean and variance statistics for color texture and fos for pure color are nearly the fastest or are in the middle interval of all the tested methods

image dependent gamut mapping as optimization problem we explore the potential of image dependent gamut mapping as a constrained optimization problem the performance of our new approach is compared to standard reference gamut mapping algorithms in psycho visual tests

a distortion measure for blocking artifacts in images based on human visual sensitivity a visual model that gives a distortion measure for blocking artifacts in images is presented given the original and reproduced image as inputs the model output is a numerical value that quantifies the visibility of blocking error in the reproduced image the model is derived based on the human visual sensitivity to horizontal and vertical edge artifacts that result from blocking psychovisual experiments have been carried out to measure the visual sensitivity to these artifacts in the experiments typical edge artifacts are shown to subjects and the sensitivity to them is measured with the variation of background luminance background activity edge length and edge amplitude synthetic test patterns are used as background images in the experiments the sensitivity measures thus obtained are used to estimate the model parameters the final model is tested on real images and the results show that the error visibility predicted by the model correlates well with the subjective ranking

toward a no reference image quality assessment using statistics of perceptual color descriptors analysis of the statistical properties of natural images has played a vital role in the design of no reference nr image quality assessment iqa techniques in this paper we propose parametric models describing the general characteristics of chromatic data in natural images they provide informative cues for quantifying visual discomfort caused by the presence of chromatic image distortions the established models capture the correlation of chromatic data between spatially adjacent pixels by means of color invariance descriptors the use of color invariance descriptors is inspired by their relevance to visual perception since they provide less sensitive descriptions of image scenes against viewing geometry and illumination variations than luminances in order to approximate the visual quality perception of chromatic distortions we devise four parametric models derived from invariance descriptors representing independent aspects of color perception 1 hue 2 saturation 3 opponent angle and 4 spherical angle the practical utility of the proposed models is examined by deploying them in our new general purpose nr iqa metric the metric initially estimates the parameters of the proposed chromatic models from an input image to constitute a collection of quality aware features qaf thereafter a machine learning technique is applied to predict visual quality given a set of extracted qafs experimentation performed on large scale image databases demonstrates that the proposed metric correlates well with the provided subjective ratings of image quality over commonly encountered achromatic and chromatic distortions indicating that it can be deployed on a wide variety of color image processing problems as a generalized iqa solution

subband coding of images subband coding has become quite popular for the source encoding of speech this paper presents a simple yet efficient extension of this concept to the source coding of images we specify the constraints for a set of two dimensional quadrature mirror filters qmf s for a particular frequency domain partition and show that these constraints are satisfied by a separable combination of one dimensional qmf s bits are then optimally allocated among the subbands to minimize the mean squared error for dpcm coding of the subbands also an adaptive technique is developed to allocate the bits within each subband by means of a local variance mask optimum quantization is employed with quantizers matched to the laplacian distribution subband coded images are presented along with their signal to noise ratios snr s the snr performance of the subband coder is compared to that of the adaptive discrete cosine transform dct vector quantization and differential vector quantization for bit rates of 0 67 1 0 and 2 0 bits per pixel for 256 256 monochrome images the adaptive subband coder has the best snr performance

embedded foveation image coding the human visual system hvs is highly space variant in sampling coding processing and understanding the spatial resolution of the hvs is highest around the point of fixation foveation point and decreases rapidly with increasing eccentricity by taking advantage of this fact it is possible to remove considerable high frequency information redundancy from the peripheral regions and still reconstruct a perceptually good quality image great success has been obtained previously by a class of embedded wavelet image coding algorithms such as the embedded zerotree wavelet ezw and the set partitioning in hierarchical trees spiht algorithms embedded wavelet coding not only provides very good compression performance but also has the property that the bitstream can be truncated at any point and still be decoded to recreate a reasonably good quality image in this paper we propose an embedded foveation image coding efic algorithm which orders the encoded bitstream to optimize foveated visual quality at arbitrary bit rates a foveation based image quality metric namely foveated wavelet image quality index fwqi plays an important role in the efic system we also developed a modified spiht algorithm to improve the coding efficiency experiments show that efic integrates foveation filtering with foveated image coding and demonstrates very good coding performance and scalability in terms of foveated image quality measurement

effect of initial concentration and spatial heterogeneity of active agent distribution on opinion dynamics abstract we analyze the effect of spatial heterogeneity in the initial spin distribution on spin dynamics in a three state square lattice divided into spatial cells districts in the spirit of the statistical mechanics of social impact we introduce a dominant influence rule dir according to which in a single update step a chosen node adopts the state determined by the influence of its discussion group formed by the node itself and its neighbors within one or more coordination spheres in contrast to models based on some form of majority rule mr a system governed by the dir is easily trapped in a stable non consensus state if all nodes of the discussion group have the same weight of influence to ensure that a consensus in the dir system is necessarily reached we need to put a stochastic process in the update rule further the stochastic dir model is used as a starting point for understanding the effect of spatial heterogeneity of active agent non zero spin distribution on the exit probabilities initially the positive and negative spins active agents are assigned to some nodes with non uniform spatial distributions while the rest of the nodes remain in the state with spin zero uncommitted voters by varying the relative means and skewness of the initial spin distributions we observe critical behaviors of exit probabilities in finite size systems the critical exponents are obtained by monte carlo simulations the results of numerical simulations are discussed in the context of social dynamics

gamut extension for cinema emerging display technologies are able to produce images with a much wider color gamut than those of conventional distribution gamuts for cinema and tv creating an opportunity for the development of gamut extension algorithms geas that exploit the full color potential of these new systems in this paper we present a novel gea implemented as a pde based optimization procedure related to visual perception models that performs gamut extension ge by taking into account the analysis of distortions in hue chroma and saturation user studies performed using a digital cinema projector under cinematic low ambient light large screen conditions show that the proposed algorithm outperforms the state of the art producing gamut extended images that are perceptually more faithful to the wide gamut ground truth as well as free of color artifacts and hue shifts we also show how currently available image quality metrics when applied to the ge problem provide results that do not correlate with users choices

visibility of wavelet quantization noise the discrete wavelet transform dwt decomposes an image into bands that vary in spatial frequency and orientation it is widely used for image compression measures of the visibility of dwt quantization errors are required to achieve optimal compression uniform quantization of a single band of coefficients results in an artifact that we call dwt uniform quantization noise it is the sum of a lattice of random amplitude basis functions of the corresponding dwt synthesis filter we measured visual detection thresholds for samples of dwt uniform quantization noise in y cb and cr color channels the spatial frequency of a wavelet is r2 sup spl lambda where r is the display visual resolution in pixels degree and spl lambda is the wavelet level thresholds increase rapidly with wavelet spatial frequency thresholds also increase from y to cr to cb and with orientation from lowpass to horizontal vertical to diagonal we construct a mathematical model for dwt noise detection thresholds that is a function of level orientation and display visual resolution this allows calculation of a perceptually lossless quantization matrix for which all errors are in theory below the visual threshold the model may also be used as the basis for adaptive quantization schemes

consensus formation in multi state majority and plurality models we study consensus formation in interacting systems that evolve by multi state majority rule and by plurality rule in an update event a group of g agents with g odd each endowed with an s state spin variable is specified for majority rule all group members adopt the local majority state for plurality rule the group adopts the local plurality state this update is repeated until a final consensus state is generally reached in the mean field limit the consensus time for an n spin system increases as ln n for both majority and plurality rules with an amplitude that depends on s and g for finite spatial dimensions domains undergo diffusive coarsening in majority rule when s or g is small for larger s and g opinions spread ballistically from the few groups with an initial local majority for plurality rule there is always diffusive domain coarsening towards consensus

space dependent color gamut mapping a variational approach gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium a typical use for this tool is the reproduction of a color image prior to its printing such that it exploits best the given printer medium color gamut namely the colors the printer can produce on the given medium most of the classical gamut mapping methods involve a pixel by pixel mapping and ignore the spatial color configuration recently proposed spatial dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost in this paper we present a new variational approach for space dependent gamut mapping our treatment starts with the presentation of a new measure for the problem closely related to a recent measure proposed for retinex we also link our method to recent measures that attempt to couple spectral and spatial perceptual measures it is shown that the gamut mapping problem leads to a quadratic programming formulation guaranteed to have a unique solution if the gamut of the target device is convex an efficient numerical solution is proposed with promising results

a visual model weighted cosine transform for image compression and quality assessment utilizing a cosine transform in image compression has several recognized performance benefits resulting in the ability to attain large compression ratios with small quality loss also incorporation of a model of the human visual system into an image compression or quality assessment technique intuitively should and has often proven to improve performance clearly then it should prove highly beneficial to combine the image cosine transform with a visual model in the past combining these two has been hindered by a fundamental problem resulting from the scene alteration that is necessary for proper cosine transform utilization a new analytical solution to this problem taking the form of a straightforward multiplicative weighting function is developed in this paper this solution is readily applicable to image compression and quality assessment in conjunction with a visual model and the image cosine transform in the development relevant aspects of a human visual system model are discussed and a refined version of the mean square error quality assessment measure is given which should increase this measure s utility

perceptual image fusion using wavelets a perceptual image fusion method is proposed that employs explicit luminance and contrast masking models these models are combined to give the perceptual importance of each coefficient produced by the dual tree complex wavelet transform of each input image this combined model of perceptual importance is used to select which coefficients are retained and furthermore to determine how to present the retained information in the most effective way this paper is the first to give a principled approach to image fusion from a perceptual perspective furthermore the proposed method is shown to give improved quantitative and qualitative results compared with previously developed methods

majority rule dynamics in finite dimensions we investigate the long time behavior of a majority rule opinion dynamics model in finite spatial dimensions each site of the system is endowed with a two state spin variable that evolves by majority rule in a single update event a group of spins with a fixed odd size is specified and all members of the group adopt the local majority state repeated application of this update step leads to a coarsening mosaic of spin domains and ultimate consensus in a finite system the approach to consensus is governed by two disparate time scales with the longer time scale arising from realizations in which spins organize into coherent single opinion bands the consequences of this geometrical organization on the long time kinetics are explored

orthonormal bases of compactly supported wavelets we construct orthonormal bases of compactly supported wavelets with arbitrarily high regularity the order of regularity increases linearly with the support width we start by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction the construction then follows from a synthesis of these different approaches

noise estimation from digital step model signal this paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model it is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image the proposed approach uses polarized directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution e g gaussian poisson speckle etc the moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models the 1d performances are detailed and as this paper is mostly dedicated to image processing a 2d extension is proposed the 2d performances for several noise distributions and noise models are presented and are compared with selected other methods

decision analysis based on fused double exponential possibility distributions abstract in this paper the possibility grades given by an expert are approximated by double possibility distributions called upper and lower possibility distributions to characterize uncertainty knowledge from this expert the upper and lower possibility distributions have some similarities to upper and lower approximations in rough set theory multi source knowledge from multiple experts is represented by a set of exponential possibility distributions based on the consistency index defined by the possibility measure of each pair of possibility distributions a fusion model is proposed to integrate multiple possibility distributions into a new one representing a refined knowledge as an application a portfolio selection problem with multiple experts is considered

wavelet filter evaluation for image compression choice of filter bank in wavelet compression is a critical issue that affects image quality as well as system design although regularity is sometimes used in filter evaluation its success at predicting compression performance is only partial a more reliable evaluation can be obtained by considering an l level synthesis analysis system as a single input single output linear shift variant system with a response that varies according to the input location module 2 sup l 2 sup l by characterizing a filter bank according to its impulse response and step response in addition to regularity we obtain reliable and relevant for image coding filter evaluation metrics using this approach we have evaluated all possible reasonably short less than 36 taps in the synthesis analysis pair minimum order biorthogonal wavelet filter banks of this group of over 4300 candidate filter banks we have selected and present here the filters best suited to image compression while some of these filters have been published previously others are new and have properties that make them attractive in system design

image quality assessment based on a degradation model we model a degraded image as an original image that has been subject to linear frequency distortion and additive noise injection since the psychovisual effects of frequency distortion and noise injection are independent we decouple these two sources of degradation and measure their effect on the human visual system we develop a distortion measure dm of the effect of frequency distortion and a noise quality measure nqm of the effect of additive noise the nqm which is based on peli s 1990 contrast pyramid takes into account the following 1 variation in contrast sensitivity with distance image dimensions and spatial frequency 2 variation in the local luminance mean 3 contrast interaction between spatial frequencies 4 contrast masking effects for additive noise we demonstrate that the nonlinear nqm is a better measure of visual quality than peak signal to noise ratio psnr and linear quality measures we compute the dm in three steps first we find the frequency distortion in the degraded image second we compute the deviation of this frequency distortion from an allpass response of unity gain no distortion finally we weight the deviation by a model of the frequency response of the human visual system and integrate over the visible frequencies we demonstrate how to decouple distortion and additive noise degradation in a practical image restoration system

dynamics of majority rule in two state interacting spin systems we introduce a two state opinion dynamics model where agents evolve by majority rule in each update a group of agents is specified whose members then all adopt the local majority state in the mean field limit where a group consists of randomly selected agents consensus is reached in a time that scales ln n where n is the number of agents on finite dimensional lattices where a group is a contiguous cluster the consensus time fluctuates strongly between realizations and grows as a dimension dependent power of n the upper critical dimension appears to be larger than 4 the final opinion always equals that of the initial majority except in one dimension

dynamics of opinion formation in a small world network the dynamical process of opinion formation within a model using a local majority opinion updating rule is studied numerically in networks with the small world geometrical property the network is one in which shortcuts are added to randomly chosen pairs of nodes in an underlying regular lattice the presence of a small number of shortcuts is found to shorten the time to reach a consensus significantly the effects of having shortcuts in a lattice of fixed spatial dimension are shown to be analogous to that of increasing the spatial dimension in regular lattices the shortening of the consensus time is shown to be related to the shortening of the mean shortest path as shortcuts are added results can also be translated into that of the dynamics of a spin system in a small world network

entropy based distortion measure and bit allocation for wavelet image compression quality criteria for image coding are often based on mean square error however this is not always a relevant measure of visual quality at low bit rates here we investigate the properties of a distortion measure based on the conditional differential entropy of the input signal given its quantized value the proposed measure appears to be a correct representation of the amount of information lost by quantization an adaptive bit allocation algorithm is proposed in order to take advantage of this criterion experimental results illustrate the behavior of the proposed distortion measure and exhibit interesting visual properties for low bit rate subband image coding

toward a unified color space for perception based image processing image processing methods that utilize characteristics of the human visual system require color spaces with certain properties to operate effectively after analyzing different types of perception based image processing problems we present a list of properties that a unified color space should have due to contradictory perceptual phenomena and geometric issues a color space cannot incorporate all these properties we therefore identify the most important properties and focus on creating opponent color spaces without cross contamination between color attributes i e lightness chroma and hue and with maximum perceptual uniformity induced by color difference formulas color lookup tables define simple transformations from an initial color space to the new spaces we calculate such tables using multigrid optimization considering the hung and berns data of constant perceived hue and the cmc cie94 and ciede2000 color difference formulas the resulting color spaces exhibit low cross contamination between color attributes and are only slightly less perceptually uniform than spaces optimized exclusively for perceptual uniformity we compare the ciede2000 based space with commonly used color spaces in two examples of perception based image processing in both cases standard methods show improved results if the new space is used all color space transformations and examples are provided as matlab codes on our website