一种基于纹理方向自适应预测和游程哥伦布编码的帧存无损压缩算法

摘要

To improve the compression performance,a frame memory lossless compression using grain-directional adaptive prediction and Golomb run-length entropy coding is proposed.First,the optimal reference pixels were obtained through double-scan and multi-directional prediction;then,the pixel differences were calculated and entropy-coded through Golomb and run-length.In this way,the compression performance is improved.Simulation results show that compared with those of reference frame lossless compression based on intra prediction and Golomb entropy coding,the average compression ratio is increased by 16％ while the average coding time is reduced when using the proposed algorithm.%为了进一步提高参考帧无损压缩的压缩性能,本文提出了一种基于纹理方向预测和游程哥伦布编码的帧存无损压缩算法.本算法首先采用双扫描和自适应预测的方法,按纹理方向,为每个像素选取最优的参考像素,并进行预测以获得预测残差;然后对预测残差进行哥伦布游程混合熵编码,从而提高了参考帧无损压缩的压缩性能.实现结果显示,与帧内预测哥伦布编码算法相比,本文算法不但平均压缩率提高了16％,而且降低了平均编码时间.