Perceptually based scalable image coding for packet networks

The exchange of visual information in heterogeneous networks requires image compression algorithms that provide high quality images at several spatial resolutions and bit rates. Scalable coding provides images at several resolutions and bit rates, while perceptual coding incorporates human visual system characteris- tics. This paper presents an image compression algorithm that pro- vides both scalable and perceptual coding to produce an embedded stream suitable for transmission over packet networks. Scalable and perceptual coding are combined through intraband coding of per- ceptually significant image regions. Images are segmented into smooth, edge, and detailed regions, and these regions are then independently intraband coded and included in the stream in de- creasing order of visual importance with respect to both region type and scale. Visual importance is based on the results of two psycho- physical studies analyzing sensitivity to noise in different image re- gions and their roles in recognition. Locally adaptive quantization, based on study results, is also included in the compression algo- rithm. The resulting embedded stream provides spatial scalability and region-selective coding and performs well in the presence of packet loss. © 1998 SPIE and IS&T. (S1017-9909(98)00403-6)

[1]  Peter No,et al.  Digital Coding of Waveforms , 1986 .

[2]  Israel Cidon,et al.  Analysis of packet loss processes in high-speed networks , 1993, IEEE Trans. Inf. Theory.

[3]  Jean-Chrysotome Bolot.  End-to-end packet delay and loss behavior in the internet , 1993, SIGCOMM 1993.

[4]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  J. Robson,et al.  Application of fourier analysis to the visibility of gratings , 1968, The Journal of physiology.

[6]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[7]  Sheila S. Hemami,et al.  Psychovisually-based multiresolution image segmentation , 1997, Proceedings of International Conference on Image Processing.

[8]  Nariman Farvardin,et al.  A perceptually motivated three-component image model-part II: applications to image compression , 1995, IEEE Trans. Image Process..

[9]  Andrew B. Watson,et al.  Visually optimal DCT quantization matrices for individual images , 1993, [Proceedings] DCC `93: Data Compression Conference.

[10]  Nariman Farvardin,et al.  Optimum quantizer performance for a class of non-Gaussian memoryless sources , 1984, IEEE Trans. Inf. Theory.

[11]  Henrique S. Malvar,et al.  The LOT: transform coding without blocking effects , 1989, IEEE Trans. Acoust. Speech Signal Process..

[12]  John C. Baird,et al.  Fundamentals of scaling and psychophysics , 1978 .

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

[14]  Sheila S. Hemami,et al.  Edge-adaptive JPEG image compression , 1996, Other Conferences.

[15]  W. Richard Stevens,et al.  Unix network programming , 1990, CCRV.

[16]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[17]  Vern Paxson,et al.  End-to-end Internet packet dynamics , 1997, SIGCOMM '97.

[18]  Y. Meyer.  Wavelets and Operators , 1993 .

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

[20]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..

[21]  Nariman Farvardin,et al.  A perceptually motivated three-component image model-Part I: description of the model , 1995, IEEE Trans. Image Process..

[22]  Barry G. Sherlock,et al.  Optimum DCT quantization , 1993, [Proceedings] DCC `93: Data Compression Conference.

[23]  Chun-Hsien Chou,et al.  A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile , 1995, IEEE Trans. Circuits Syst. Video Technol..

[24]  I. Rock.  The Perceptual world: readings from Scientific American magazine , 1990 .

[25]  Stéphane Mallat,et al.  Singularity detection and processing with wavelets , 1992, IEEE Trans. Inf. Theory.

[26]  Robert M. Gray,et al.  Subband-coded image reconstruction for lossy packet networks , 1997, IEEE Trans. Image Process..

[27]  Peter N. Heller,et al.  Smoothness-constrained wavelet image compression , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[28]  D. Mitra,et al.  Stochastic theory of a data-handling system with multiple sources , 1982, The Bell System Technical Journal.

[29]  Joan L. Mitchell,et al.  JPEG: Still Image Data Compression Standard , 1992 .