一种基于改进量化表的 JPEG 图像压缩算法

目的结合人眼视觉特性,研究一种基于改进量化表的JPEG图像压缩算法(JPEG-HVS)。方法利用人眼亮度对比度敏感函数(CSF)生成一种新的量化表,来代替传统JPEG标准推荐的亮度量化表,并通过Matlab7.0对不同种类图像进行了仿真实验。通过计算不同种类图像的压缩质量评价指标,将提出的压缩算法与传统JPEG压缩算法及JPEG区域法进行对比。结果 JPEG-HVS实现的压缩比比JPEG实现的压缩比平均高出53.56%,比JPEG区域法平均高出18.75%。3种压缩方法的峰值信噪比(PSNR)波动不大,JPEG的PSNR值最大,JPEG-HVS次之,平均结构相似度(MSSIM)从大到小排列依次为JPEGJPEG-HVSJPEG区域法。JPEG-HVS编解码所需时间要明显少于JPEG。同时依靠主观评价可以发现,经JPEG-HVS解压的重构图像仍具有良好的视觉特性。结论在保证了压缩质量的同时,提出的JPEG-HVS压缩算法相比于传统JPEG压缩算法、JPEG区域法,可以实现更大的压缩比和更快的编解码速度,更有利于图像的存储与传输。

An Algorithm of JPEG Image Compression Based on Improved Quantization Table

JPEG image compression algorithm (JPEG-HVS) was studied based on improved quantization table combined with characteristics of Human Vision System. It calculated a new kind of quantization table according to the human visual luminance contrast sensitivity function and used it to take place of the luminance quantization table form JPEG standard, and carried out the simulation experiment on different classes of images via Matlab7.0. By comparison, the JPEG-HVS had a better compression ratio, 53.56% higher than the traditional JPEG compression algorithm and 18.75% higher than the JPEG zone method. The difference of peak-signal-to-noise ratio (PSNR) among the three was very small, i.e. JPEG>JPEG-HVS>JPEG zone method. The mean structural similarity index measure (MSSIM) of the three was JPEG>JPEG-HVS>JPEG zone method. The time of coding and decoding of JPEG-HVS was far less than that of JPEG. Meanwhile, images decompressed by JPEG-HVS still had a good visual effect by observation. Compared with the other two, with the quality of compression image guaranteed at the same degree, the JPEG-HVS can reach higher compression ratio and faster coding and decoding, which will benefit the storage and transmission of images.