Title :
Some simple parametric lossless image compressors
Author :
Slyz, Marko J. ; Neuhoff, David L.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Abstract :
This paper proposes lossless image compressors that are simpler than existing ones and yet still work well. The compressors process images in raster-scan order, and to code a pixel first estimate that pixel´s value by using a linear function of already-coded pixels. Next the compressors estimate the uncertainty in the first estimate by using a nonlinear function of already-coded pixels. Finally, based on these estimates, they select a discretized Laplacian with which an arithmetic coder represents the pixel. Alternatively, the compressors may select Golomb codewords based on the estimates, and thus directly represent the pixels. These compressors´ rates come within 6 to 8% of CALIC, a highly-effective image compressor. Another benefit is that a simple theoretical motivation exists for the chosen uncertainty estimators
Keywords :
Laplace transforms; adaptive codes; arithmetic codes; data compression; image coding; nonlinear functions; transform coding; Golomb codewords; Laplacian based adaptive coder; arithmetic coder; coded pixels; compressor rates; discretized Laplacian; linear function; nonlinear function; parametric lossless image compressors; pixel coding; pixel representation; pixel value estimation; raster-scan order; uncertainty estimators; Arithmetic; Compressors; Gaussian distribution; Image coding; Integral equations; Laplace equations; Laser sintering; Pixel; Predictive models; Uncertainty;
Conference_Titel :
Image Processing, 2000. Proceedings. 2000 International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-6297-7
DOI :
10.1109/ICIP.2000.900910