【摘要】 提出了一种压缩比自适应的矢量量化(VQ)编解码算法,将图像预先分为16×16的分块,根据图像块的平滑程度,减少重复搜索的运算量,大幅提高压缩比和编码速度,而解码图像的峰值信噪比(PSNR)只有很少下降。对于10幅标准图像的测试结果表明,与普通VQ相比,该文算法的压缩比平均提高54%,PSNR平均仅降低0.86%。对于单纯背景的图像,压缩比可达到200∶1左右。算法简单,适合硬件实现。更多还原

【Abstract】 A compression ratio adaptive algorithm for Vector Quantization(VQ) is proposed in this paper,which divides the image into 16×16 blocks,and estimates the smoothness of images,reduces the needless compute of encode,and improves the compression ratio and encode speed finally,while Peer Signal-Noise Ratio(PSNR) of the reconstructed image decreases only a little.To compare with standard VQ algorithm,an experiment over 10 standard images is conducted,and the result shows that compression ratio of these images can be improved by 54 percent average,while the mean PSNR decreases 0.86 percent.With particular image,the compression ratio can achieve 200∶1.The algorithm is simple to be implemented in hardware.更多还原