基于CCSDS的低码率图像压缩优化算法

Low Bit-rate Image Compression Algorithm Based on CCSDS

为了提高空间数据系统咨询委员会（CCSDS）采用的图像压缩算法的编码效率,提出了一种二维预测模型。通过利用图像像素之间的空间相关性对直流系数的预测模式及其熵编码算法进行改进和优化,该算法在有效地提高了直流系数的压缩比的同时,也增强了其抗误码性能。试验结果表明,该算法在低码率条件下能获得更好的图像编码质量,与CCSDS原有算法相比,峰值信噪比值提高了0.1~0.3dB。算法可极大地满足星载图像压缩数据在低码率下传输的要求。

In order to improve the compression efficiency of the image data compression algorithm adopted by consulative committee for space data system（CCSDS）,a two-dimensional prediction model was proposed.By utilizing the spatial correlation of pixels existing in the image to improve and optimize the prediction of direct current（DC） coefficients and the entropy coding,the compression performance of DC coefficients as well as enhance the ability for error resiliency could be improved.Experimental results show that the algorithm can obtain better quality of image encoding at low bit-rate image and improve（S/N）P by 0.13~0.3dB compared with the original algorithm in CCSDS.Moreover,the proposed algorithm significantly meet the need of the low bit-rate transmission of the onboard image compression data.