Visual masking model for perceptual color image compression

The quality of compressed images can be remarkabley improved if the dictates of the Human Visual System (HVS) requirements are followed. To achieve this goal, our strategy is to exploit human visual masking effect using a subband decomposition. A combination of both intra channel and inter channel masking property is then performed. This scheme exploits the lowpass character of the perceptual masking for natural color images in estimating the amount of available masking. Results obtained show an improvement of the quality of reconstructed color images compared to existing compression schemes like standard JPEG2000.

[1]  E. Peli.  Contrast in complex images. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[2]  E. Peli.  In search of a contrast metric: Matching the perceived contrast of gabor patches at different phases and bandwidths , 1997, Vision Research.

[3]  C. van den Branden Lambrecht.  Color moving pictures quality metric , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[4]  Murat Kunt,et al.  Human Vision Models for Perceptually Optimized Image Processing – A Review , 2000 .

[5]  Stefan Winkler,et al.  Computing isotropic local contrast from oriented pyramid decompositions , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[6]  R. J. Safranek,et al.  A perceptually tuned sub-band image coder with image dependent quantization and post-quantization data compression , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[7]  J. M. Foley,et al.  Contrast masking in human vision. , 1980, Journal of the Optical Society of America.

[8]  Patrick Le Callet,et al.  Interactions of chromatic components in the perceptual quantization of the achromatic component , 1999, Electronic Imaging.