基于新兴的压缩感知(Compressed Sensing, CS)理论, 提出了一种抗丢包能力强且结构简单易实现的多描述编 码方法.首先对变换后的图像进行交织抽取分块, 再对各子块进行随机观测、量化、打包形成多个描述子码流.解码 端根据接收码流情况通过求解优化问题重建原图像.由于随机观测过程简单易实现, 故该方法可以以较低的计算 复杂度构造出较多的描述子.实验结果表明, 在同样的丢包率下, 本文方法的重构质量(PSNR)明显优于SPIHT多 描述编码方法, 且计算复杂度较低.

Based on compressed sensing (CS), a new multiple description coding method (CS-MDC) was presented. The new method is robust to packet loss or bit error, and has the advantages of simple structure and easy implementation. The method partitioned an image into several blocks by interleaving extracting in the wavelet domain, and made random measurements of the image blocks, and then formed multiple descriptions after quantizing and packing. At the decoding end, it reconstructed the original image approximately or exactly with the received bit streams by solving an optimization problem. The proposed method can construct more descriptions with lower complexity because the process of random measuring is simple and easy to realize. Experimental results show that the proposed method exhibits its superiority over SPIHT-MDC with the same packet loss probability, and it can easily generate more descriptions.