Abstract:
We present a new method for lossless image compression that gives compression comparable to JPEG lossless mode with about five times the speed. Our method, called ELICS, is based on a novel use of two neighboring pixels for both prediction and error modeling. For coding we use single bits, adjusted binary codes, and Golomb Rice codes. For the latter we present and analyze a provably good method for estimating the single coding parameter. Efficient, lossless image compression system (ELICS) algorithm, which consists of simplified adjusted binary code and Golomb–Rice code with storage-less k parameter selection, is proposed to provide the lossless compression method for high-throughput applications. The simplified adjusted binary code reduces the number of arithmetic operation and improves processing speed. According to theoretical analysis, the storage-less k parameter selection applies a fixed value in Golomb–Rice code to remove data dependency and extra storage for cumulation table.

Keywords: Binary adjusted coding, Golomb-Rice coding, Intensity distribution, lossless data compression, predictive coding, wavelet transform