无损自适应分布式算术编码的研究及应用

Research on lossless adaptive-distributed arithmetic coding and its applications

目前分布式算术编码研究都是基于先验概率已知的有损压缩,为了实现概率自适应的无损压缩,研究了采用结束字符和概率自适应的编码方式来实现编码,提出了无损自适应分布式算术编码。实验结果表明,该算法拥有更好的压缩效果和更低的解码复杂度,并且在实际应用中,编解码可以同时进行。由于无损自适应分布式算术编码具有编码简单、压缩效果好的优点,故将它和比特面编码结合实现超光谱图像压缩,并将仿真结果与3D-SPECK算法比较,结果表明了该方法可以使信噪比提高0.13-0.37dB。

Currently, most of the DAC （distributed arithmetic coding） research methods focus on the lossy compression on the conditionthat the prior knowledge is known in advance. To realize adaptive and lossless compression,LADAC （ lossless adaptive-distributed arithmetic coding ） is proposed, which adopts the method of EOF （end of the file） and the adaptive encoding. Experimental result shows that LADAC processes the better compression performance and lower decoder complexity, and encoding and decoding can be done simultaneously in practice. Because of these merits of simple encoding and good compression performance, LADAC is combined with bit-plane coding to achieve hyper-spectral images compression, and experimental result shows that, compared with 3D-SPECK, this method can improve SNR by 0.13-0.3 7dB.