Fast Progressive Lossless Image Compression

Abstract

We present a method for progressive lossless compression of still grayscale images that combines the speed of our earlier FELICS method with the progressivity of our earlier MLP method We use MLP s pyramid based pixel sequence and image and error modeling and coding based on that of FELICS In addition we introduce a new pre x code with some advantages over the previously used Golomb and Rice codes Our new progressive method gives compression ratios and speeds similar to those of non progressive FELICS and those of JPEG lossless mode also a non progressive method The image model in Progressive FELICS is based on a simple function of four nearby pixels We select two of the four nearest known pixels using the two with the middle non extreme values Then we code the pixel s intensity relative to the selected pixels using single bits adjusted binary codes and simple pre x codes like Golomb codes Rice codes or the new family of pre x codes introduced here We estimate the coding parameter adaptively for each context the context being the absolute value of the di erence of the predicting pixels we adjust the adaptation statistics at the beginning of each level in the progressive pixel sequence