Psychovisual quality metric based on multiscale image texture analysis

Thierry Eude; Abdelhalim Mayache; Claude Milan

doi:10.1117/12.348445

19 May 1999 Psychovisual quality metric based on multiscale image texture analysis

Thierry Eude, Abdelhalim Mayache, Claude Milan

Proceedings Volume 3644, Human Vision and Electronic Imaging IV; (1999) https://doi.org/10.1117/12.348445
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

Abstract

This paper describes a perceptual measure for still image compression system. Considering the fact that the conventional PSNR cannot sufficiently reflect the result of subjective assessment, other quality measure have been considered to design the variable bit-rate coders. Indeed, there is a growing interest for perceptual quality measure. Some works have been carried out in the field of still picture quality evaluation while trying to introduce some properties of the human visual system. In the recent literature there are roughly three properties that are identified as being useful. The best known, and generally most widely used properly, is the modulation transfer function of the human visual system. The other tow properties can be described as luminance masking and texture masking. A large number of image quality measures of this kind have been developed, with different degrees of success. In previous works, we provided a rigorous evaluation of metrics which take into account artifacts generated by compression method like JPEG. The results show that these metrics are highly correlated with the subjective quality grading but also depend on the complexity of the images under study. Then, we propose a new perceptual metric for still image compression based on multiresolution decomposition. It allows characterize image texture, better takes into account masking effect and don't depend on compression method.

Citation Download Citation

Thierry Eude, Abdelhalim Mayache, and Claude Milan "Psychovisual quality metric based on multiscale image texture analysis", Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); https://doi.org/10.1117/12.348445

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