A compressive sensing approach to perceptual image coding

There exist limitations in the human visual system (HVS) which allow images and video to be reconstructed using fewer bits for the same perceived image quality. In this paper we will review the basis of spatial masking at edges and show a new method for generating a just-noticeable distortion (JND) threshold. This JND threshold is then used in a spatial noise shaping algorithm using a compressive sensing technique to provide a perceptual coding approach for JPEG2000 coding of images. Results of subjective tests show that the new spatial noise shaping framework can provide significant savings in bit-rate compared to the standard approach. The algorithm also allows much more precise control of distortion than existing spatial domain techniques and is fully compliant with part 1 of the JPEG2000 standard.

[1]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.

[2]  A. Vassilev.  Contrast sensitivity near borders: significance of test stimulus form, size and duration. , 1973, Vision research.

[3]  Mark R. Pickering,et al.  A perceptually efficient VBR rate control algorithm , 1994, IEEE Trans. Image Process..

[4]  B. Prasada,et al.  Adaptive quantization of picture signals using spatial masking , 1977, Proceedings of the IEEE.

[5]  Peter G. J. Barten,et al.  Contrast sensitivity of the human eye and its e ects on image quality , 1999 .

[6]  John D. Villasenor,et al.  Visibility of wavelet quantization noise , 1997, IEEE Transactions on Image Processing.

[7]  J. Limb,et al.  Thresholds at luminance edges under stabilized viewing conditions. , 1980, Journal of the Optical Society of America.

[8]  Zhen Liu,et al.  JPEG2000 encoding with perceptual distortion control , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

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

[10]  Bernd Girod,et al.  Psychovisual aspects of image communication , 1992, Signal Process..

[11]  James D. Johnston,et al.  Spatial noise shaping based on human visual sensitivity and its application to image coding , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  Sheila S. Hemami,et al.  Dynamic contrast-based quantization for lossy wavelet image compression , 2005, IEEE Transactions on Image Processing.

[13]  D. Chandler,et al.  Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.

[14]  Atul Puri,et al.  Motion-compensated video coding with adaptive perceptual quantization , 1991, IEEE Trans. Circuits Syst. Video Technol..

[15]  Cesar A. Gonzales,et al.  Motion video adaptive quantization in the transform domain , 1991, IEEE Trans. Circuits Syst. Video Technol..