Image Compression: A Survey <s> Conditional arithmetic coding prediction and adaptive lifting: <s> A new algorithm for fractal compression of greyscale images is presented. It uses some previous results allowing the compression process to be reduced to a nearest neighbors problem, and is essentially based on a geometrical partition of the image block feature space. Experimental comparisons with previously published methods show a significant improvement in speed with no quality loss. <s> BIB001 </s> Image Compression: A Survey <s> Conditional arithmetic coding prediction and adaptive lifting: <s> The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using first quincunx sampling and then simple row-column sampling. In each case, the efficiency of the linear predictors is enhanced nonlinearly. Directional postprocessing is used in the quincunx case, and adaptive-length postprocessing in the row-column case. Both methods are seen to perform well. The resulting nonlinear interpolation schemes achieve extremely efficient image decorrelation. We further investigate context modeling and adaptive arithmetic coding of wavelet coefficients in a lossless compression framework. Special attention is given to the modeling contexts and the adaptation of the arithmetic coder to the actual data. Experimental evaluation shows that the best of the resulting coders produces better results than other known algorithms for multiresolution-based lossless image coding. <s> BIB002
In reducing prediction mistake due to variance of stationary signal. In general dimensional case optimal predictors is first calculated of a lifting scheme. With corresponding update filters optimal predictor filter is applied by sampling and row column for lossless compression of still images. In quincunx case to improve the results for enhancing efficiency of linear predictors in nonlinear means by directional post processing BIB001 BIB002 . Table 5 shows some Lossless Image Compression Algorithms.