Conventional mean squared error based methods for objective image quality assessment are not well correlated with human evaluation. The design of better objective measures of quality has attracted a lot of attention and several image quality metrics based explicitly on the properties of the Human Visual System (HVS) have been proposed in recent years. However, only in a few cases has the performance of such metrics been demonstrated on real images. In accounting for visual masking, all these metrics assume that the multiple channels mediating visual perception are independent of each other. Recent neuroscience findings and psychophysical experiments have established that there is interaction across the channels and that such interactions are important for visual masking. In this work, we propose the Picture Distortion Metric (PDM) which integrates these new visual masking properties, and we evaluate its performance for image coding applications. We evaluate the performance at medium to high range of quality to predict subjective scores on a 0-10 numerical scale, and on a wide range of quality for the 1-5 CCIR impairment scale.

In image coding applications, quantitative quality metrics which approximate the perceived quality of an image can be used for evaluating the performance of coders, designing new coders and optimizing existing coders. In this paper, we consider images of high quality levels for which most of the errors are in the threshold region of perception, and perceptible errors are sparsely distributed. Two different methodologies are used; first, we use an objective Picture Quality Scale (PQS) which combines partial measures, denoted distortion factors, of random as well as structured perceived distortions due to coding. We also consider an alternative approach, applicable at high quality, that is based on a multi-channel vision model, the Visible Differences Predictor (VDP) proposed by Scott Daly. The VDP produces a probability detection map identifying regions in which errors are sub-threshold, threshold and supra-threshold. For the PQS, since distortion factors due to structured errors and errors in the vicinity of high contrast image transitions are most important at high quality, these two factors are analyzed to compute spatial distortion maps of their contributions. This paper compares the spatial distortion maps produced by both methods for high quality still images to experimental observations. Global values for the quality have been obtained by integrating the factor images obtained using PQS and yield a correlation of 0.9 with mean opinion of score values for JPEG, Subband and Wavelet coded images.

The design of very low bit rate coders, below 64 kilobits per second, presents a number of new challenges. Such low bit rate coders are targeted to small size images, say 176 X 144, or below and are limited to head and shoulders scenes. In this paper, we compare and rate the performance of several still image encoding methods such as DCT: Subband and Wavelets, using a new quality scale based on properties of human vision. These still image coders are embedded into video coders such as the H261 coder. The relative importance of intraframe and interframe quality and contributions to the total bit rate provide an overall design framework for these low bit rate video coders. We discuss and illustrate, for the encoding of low bit rate video. the still image and motion impairments that are perceptually most important.

Part I of the work presented the derivation and theoretical evaluation of new wideband maximum likelihood strategies for the estimation of blood velocity using acoustic signals. In Part II, the signal models and performance of the estimation strategies described in Part I are tested with experimental ultrasonic data. The ultrasonic data analyzed in the work verifies the theoretical model and predicted performance. The averaged correlation, verified experimentally, confirms that the correlation envelope can be used to estimate the velocity of scatterers, and that the shape of the correlation function conveys information regarding the velocity profile within tht sample volume. For both the wideband point and range spread estifl!lators, the predicted improvement in velocity resolution and the redu(tion in the height of subsidiary velocity peaks are demonstrated. Through the use of these estimation strategies, information regarding the mean velocity and velocity variation are available for each spatial location within the vessel. This information is presented using a three-dimensional (3-D) spatial velocity profile display, which appears to offer a number of advantages in the rapid identification of pathology.

In recent work, we have examined the performance of wavelet coders using a perceptually relevant image quality metric, the Picture Quality Scale (PQS). In that study, we considered some of the design options available with respect to choice of wavelet basis, quantizer, and method for error-free encoding of the quantized coefficients, including the EZW methodology. A specific combination of these design options provides the best trade off between performance and PQS quality. Here, we extend this comparison by evaluating the performance of JPEG and the previously chosen optimal wavelet scheme, focusing principally on the high quality range.

The derivation and theoretical evaluation of new wideband maximum likelihood strategies for the estimation of blood velocity using acoustic signals are presented. A model for the received signal from blood scatterers, using a train of short wideband pulses, is described. Evaluation of the autocorrelation of the signal based on this model shows that the magnitude, periodicity and phase of the autocorrelation are affected by the mean scatterer velocity, and the presence of a velocity spread target. New velocity estimators are then derived that exploit the effect of the scatterer velocity on both the signal delay and the shift in frequency. The wideband range spread estimator is derived using a statistical model of the target. Based on the point target assumption, a simpler wideband maximum likelihood estimator is also obtained. These new estimation strategies are analyzed for their local and global performance. Evaluation of the Cramer-Rao bound shows that the bound on the estimator variance is reduced using these estimators, in comparison with narrowband strategies. In order to study global accuracy, the expected estimator output is evaluated, and it is determined that the width of the mainlobe is reduced. In addition, it is shown that the height of subsidiary velocity peaks is reduced through the use of these new estimators.

Image coding requires an effective representation of images to provide dimensionality reduction, a quantization strategy to maintain image quality, and finally the error free encoding of quantized coefficients. In the coding of quantized coefficients, Huffman coding and arithmetic coding have been used most commonly and are suggested as alternatives in the JPEG standard. In some recent work, zerotree coding has been proposed as an alternate method, that considers the dependence of of quantized coefficients from subband to subband, and thus appears as a generalization of the context-based approach often used with arithmetic coding. In this paper, we propose to review these approaches and discuss them as special cases of an analysis based approach to the coding of coefficients. The requirements on causality and computational complexity implied by arithmetic and zero-tree coding will be studied and other schemes proposed for the choice of the predictive coefficient contexts that are suggested by image analysis.

The design of linear image filters based on properties of human visual perception has been shown to require the minimization of criterion functions in both the spatial and frequency domains. In this correspondence, we extend this approach to continuous filters of infinite support. For low pass filters, this leads to the concept of an ideal low pass image filter which provides a response that is superior perceptually to that of the classical ideal low pass filter.

The design of a wavelet image coder can be divided into three parts: wavelet representation, quantization, and error-free encoding. We evaluate each of these parts individually and synthesize them into complete coders. The evaluation is in the rate-distortion sense; two image quality metrics are used: a perception-based, quantitative picture quality scale (PQS) and the conventional distortion measure, peak signal-to-noise ratio (PSNR). Two representative wavelets, three quantizers, three encoders, and some combinations of these parts are comparatively evaluated. Our results provide an insight into the design issues of optimizing wavelet coders, as well as a good reference for application developers to choose from an increasingly large family of wavelet coders for their applications