Adaptive Predictor for Lossless Image Compression

The new method for lossless image compression of grey-level images is proposed. The image is treated as stacked bit planes. Its compressed version is represented as residuals of a non-linear local predictor spanning from the representative point in the current bit plane and a few neighbouring ones. Predictor configurations are grouped into couples that differ in one bit in the representative point only. The occurrence frequency of predictor configurations is checked in the input image. The predictor adapts automatically to the image, it is able to estimate the influence of cells in the neighbourhood and thus copes even with complicated structure or fine texture. Residuals between original and predicted image are those that correspond to the less frequent predictor configurations. Effectively coded residuals constitute the output image. To our knowledge, the proposed compression method is comparable with recent best methods of others in performance. Especially good results were obtained..