基于DCT分类的边缘匹配矢量量化图像编码算法

Image Coding Algorithm Based on Classified Side-Match Vector Quantization in DCT Domain

提出一种基于DCT分类的边缘匹配矢量量化算法,充分考虑了当前处理图像块与其相邻图像块之间的相关性以及各码字与该输入矢量之间的边缘匹配失真。实验结果表明,该算法的峰值信噪比（PSNR）值高于基本边缘匹配矢量量化器且码率更低。本文对该方法进行了改进,提出一种新的基于DCT分类的边缘匹配矢量量化算法。该算法可以使运算时间缩短40%~50%。

The side-match vector quantizer（SMVQ） is suitable for encoding the image with a high correlation between neighboring image blocks.It is a branch of the finite-state vector quantizer.An image coding algorithm based on the classified side-match vector quantization in DCT domain is presented.Correlative predictions between neighboring image blocks are made in the algorithm.The match distortion between the input image block and the code vector is also considered.Experimental result shows that compared with basic SMVQ,it reduces bit rates and raises the PSNR value.Moreover,the algorithm is modified and a new algorithm is presented.The result shows that the new algorithm can reduce coding time by 40%—50%.