C.J. van den Branden Lambrecht

A working spatio-temporal model of the human visual system for image restoration and quality assessment applications

This paper describes a spatio-temporal model of the human visual system (HVS) for video imaging applications, predicting the response of the neurons of the primary visual cortex. The model simulates the behavior of the HVS with a three-dimensional filter bank which decomposes the data into perceptual channels, each one being tuned to a specific spatial frequency, orientation and temporal frequency. It further accounts for contrast sensitivity, inter-stimuli masking and spatio-temporal interaction. The free parameters of the model have been estimated by psychophysics. The model can then be used as the basis for many applications. As an example, a quality metric for coded video sequences is presented.This paper describes a spatio-temporal model of the human visual system (HVS) for video imaging applications, predicting the response of the neurons of the primary visual cortex. The model simulates the behavior of the HVS with a three-dimensional filter bank which decomposes the data into perceptual channels, each one being tuned to a specific spatial frequency, orientation and temporal frequency. It further accounts for contrast sensitivity, inter-stimuli masking and spatio-temporal interaction. The free parameters of the model have been estimated by psychophysics. The model can then be used as the basis for many applications. As an example, a quality metric for coded video sequences is presented.

Color moving pictures quality metric

This paper presents a comprehensive quality metric for color moving pictures which is based on a spatio-temporal vision model and on the opponent-colors theory. The metric is used to assess the quality of MPEG compressed video streams and is compared with a grayscale video quality metric.This paper presents a comprehensive quality metric for color moving pictures which is based on a spatio-temporal vision model and on the opponent-colors theory. The metric is used to assess the quality of MPEG compressed video streams and is compared with a grayscale video quality metric.

Efficient spatio-temporal decomposition for perceptual processing of video sequences

This paper presents a vision model for moving pictures. The model is an extension of a normalization model by Teo and Heeger (1994). It accounts for normalization of the cortical receptive field responses and inter-channel masking. The model is compared with a simpler vision model for video by presenting results on quality assessment of MPEG compressed video.

Quality assessment of motion rendition in video coding

This paper addresses the issue of testing and quality assessment of motion rendition in digital video coding. Motion estimation and compensation are critical modules in video coders, as they are the most demanding resources and largely account for the visual quality of the resulting compressed stream. The testing of such modules is thus very important. A computational metric, based on a spatiotemporal model of the human visual system and of human motion sensing, is proposed and used to evaluate MPEG-2 compressed video. The metric is able to assess the quality of motion rendition and exhibits a good correlation with subjective data.

Subband adaptive filtering: The mutual wavelet packets approach

The authors present a scheme for subband adaptive filtering, where the subband decomposition is performed using a novel mutual wavelet packets decomposition scheme. They contrast the performance and algorithmic complexity of this new structure to that of regular subband adaptive filtering and point out its usefulness in achieving better filtering performance. The use of this mutual wavelet packets decomposition allows the partitioning of the frequency axis into nonuniform subbands adapted to the spectral content of the signals to be filtered. A criterion maximizing the cross-correlation between the signals is proposed for this purpose. Simulations on both synthetic and real signals confirmed the improvement achieved in performance.<<ETX>>

Adaptive quantization using a perceptual visibility predictor

This work addresses the optimization of video services by improving the bit allocation stage in a video encoder. We first introduce a new block-based video metric based on a vision model, termed the perceptual visibility predictor (PVP), which accounts for spatial as well as temporal perceptual activities. In other words, we propose a way to classify sequence areas in terms of their relevance to human perception. We then briefly show how this metric may be used within a one-pass casual adaptive quantization scheme applied to MPEG-2 video encoding.

Analyzing pulmonary capillary pressure

A new mutual wavelet packets scheme is proposed for subband adaptive filtering. Its relation to the existing literature on the subject is outlined. The proposed scheme performs a decomposition of the two signals used in the adaptation process onto the same optimal basis. That basis is chosen so that it favors the adaptation performance. A new criterion, based on a functional of the two signals, is introduced. This proposed criterion consists in the maximization of the magnitude of the cross-correlation samples of the two signals considered. This maximizes the cross-correlation vector of the well known normal equations. At the expense of a slightly higher computational complexity, the mutual wavelet packets scheme reduces the aliasing drawback of regular subband adaptive filtering, preserving its main advantages. Simulations have been performed on pulmonary capillary pressure transients for respiratory interference cancelling. The method proved to be more efficient than classical methods. >

Automatically assessing MPEG coding fidelity

As the market and number of products for multimedia applications grow, the need for testing methods and fidelity metrics becomes critical. Testing devices are important for the development and evaluation of multimedia products. This article describes a testing method and prototype that can be used for assessing MPEG coding fidelity.

Quality assessment of image features in video coding

This paper describes an extension of a vision model for video that has been designed to estimate how specific features in moving pictures are rendered as a consequence of a compression process. The resulting model permits to evaluate the distortions on contours and textures in a sequence, as well as to estimate how strong the blocking effect (resulting from a block-DCT compression scheme) is. The model has been used to evaluate feature rendition in MPEG-2 compressed sequences.