Perceptual atributes of crosstalk in 3-D TV

Abstract onl

Issues with the construct of quality

This paper proposes an outline for a framework that aims to give a comprehensive view of perceived video quality, including physical characteristics, perceptual attributes and cognitive factors

Image dissimilarity

In this paper we compare the performance of a number of representative instrumental models for image dissimilarity with respect to their ability to predict both image dissimilarity and image quality, as perceived by human subjects. Two sets of experimental data, one for images degraded by noise and blur, and one for JPEG-coded images, are used in the comparison

The role of image dissimilarity in image quality models

Although the concept of image dissimilarity is very familiar in the context of instrumental measures for image quality, it is fairly uncommon to use it as an experimental paradigm. Most instrumental measures relate image quality to some distance, such as the root-mean-squared error (RMSE), between the original and the processed image, such that image dissimilarity arises naturally in this context. Dissimilarity can however also be judged consistently by subjects. In this paper we compare the performance of a number of representative instrumental models for image dissimilarity (such as the Sarnoff model and RMSE) with respect to their ability to predict both image dissimilarity and image quality, as perceived by human subjects. Two sets of experimental data, one for images degraded by noise and blur, and one for JPEG-coded images, are used in the comparison. In none of the examined cases could a clear advantage of complicated distance metrics (such as the Sarnoff model) be demonstrated over simple measures such as RMSE

A single-ended blockiness measure for JPEG-coded images

In three subjective experiments, dissimilarity data and numerical category scaling data were obtained to determine the underlying attributes of image quality in sequential baseline-coded JPEG images. Although several distortions were perceived, namely blockiness, ringing and blur, the subjective data for all attributes were highly correlated, so that image quality could approximately be described in one dimension. We therefore proceeded by developing an instrumental measure for one of the distortions, namely, blockiness. In this paper a single-ended blockiness measure is proposed, i.e., one that uses only the coded image. Our approach is therefore fundamentally di7erent from most (double-ended) image quality models that needboth the original andthe degradedimage. The proposedmeasure is basedon detecting the low-amplitude edges that result from blocking and estimating the edge amplitudes. Because of the approximate one-dimensionality of the underlying psychological space, the proposed blockiness measure also predicts the image quality of sequential baseline coded JPEG images

<title>Influence of processing method, bit rate, and scene content on perceived and predicted image quality</title>

In this paper we evaluate two objective quality measures, the root-mean-square-error and a model based on the human visual system (HVS), on their ability to predict the perceived image quality for variations in bit-rate, processing method, and scene content. In theory quality metrics should be able to predict the perceived image quality independent of these variations. However, one can imagine that in practice this is not trivial to meet. But also subjects might have difficulties in making comparisons across processing methods or across scenes. In order to test whether subjects use separate quality scales for each identifiable scene and processing method or whether they use a single quality scale, we set up experiments in which the influence of bit-rate, processing method, and scene content was measured. In all experiments subjects were instructed to judge the quality difference between two simultaneously presented images

Perceptual attributes of image quality in JPEG-coded images

The perceived overall image quality of sequential baseline-coded JPEG images depends on the achieved compression ratio, which is controlled by the 'quality parameter' of the coding algorithm. This 'quality parameter' can vary between 0 and 100, ranging from poor image quality with large visible distortions to high-quality images that cannot be distinguished from the original. In two experiments, dissimilarity data and categorical-numerical scaling data were gathered to determine the underlying attributes of image quality and their perceived strength. Although several distortions are perceived in IPEG images, blockiness, ringing and blur, the best fit of the dissimilarity data is a one-dimensional stimulus configuration. This is probably due to the fact that the distortions are highly correlated in sequential baseline-coded JPEG images

A single-ended blockiness measure for JPEG-coded images

In three subjective experiments, dissimilarity data and numerical category scaling data were obtained to determine the underlying attributes of image quality in sequential baseline-coded JPEG images. Although several distortions were perceived, namely blockiness, ringing and blur, the subjective data for all attributes were highly correlated, so that image quality could approximately be described in one dimension. We therefore proceeded by developing an instrumental measure for one of the distortions, namely, blockiness. In this paper a single-ended blockiness measure is proposed, i.e., one that uses only the coded image. Our approach is therefore fundamentally di7erent from most (double-ended) image quality models that needboth the original andthe degradedimage. The proposedmeasure is basedon detecting the low-amplitude edges that result from blocking and estimating the edge amplitudes. Because of the approximate one-dimensionality of the underlying psychological space, the proposed blockiness measure also predicts the image quality of sequential baseline coded JPEG images