Arithmetic Coding Based on Reflected Binary Codes Arithmetic coding is a lossless data compression technology on a sequence of symbols in independent and identically distributed (i.i.d.) distributions. In this paper, we pointed out that the conventional arithmetic coding has the possibility of burst outputs between the encoder and the output buffer, and this brings up a number of potential risks. To solve this issue, we present a new arithmetic coding which encodes the output bitstream in reflected binary codes. The analysis shows that the proposed coding method can avoid the burst outputs during the encoding. The comparisons with Huffman codes, conventional arithmetic codes and Asymmetric numeral system are discussed. Simulations show that the proposed approach has better throughput performance than the conventional approach.

Lossless and nearlossless image compression with successive refinement We present a technique that provides progressive transmission and nearlossless compression in one single framework. The proposed technique produces a bitstream that results in progressive reconstruction of the image justlike what one can obtain with a reversible wavelet codec. In addition, the proposed scheme provides nearlossless reconstruction with respect to a given bound after each layer of the successively refinable bitstream is decoded. We formulate the image data compression problem as one of asking the optimal questions to determine, respectively, the value or the interval of the pixel, depending on whether one is interested in lossless or nearlossless compression. New prediction methods based on the nature of the data at a given pass are presented and links to the existing methods are explored. The tradeoff between noncausal prediction and data precision is discussed within the context of successive refinement. Context selection for prediction in different passes is addressed. Finally, experimental results for both lossless and nearlossless cases are presented, which are competitive with the stateoftheart compression schemes.