无参考JP EG压缩图像质量评价改进算法

摘要

A fast and effective quality assessment algorithm based on no⁃reference was proposed to solve the problem of high computational cost in typical quality assessment algorithm for JPEG compressed images. The proposed algo⁃rithm introduced the characteristics of human visual system into the image quality assessment system, using the lo⁃cal variance to select the image blocks interested by human being instead of selecting the entire image. It conducted feature extraction only for the interested image blocks. Three eigenvalues of the image were calculated, and at last, all eigenvalues were integrated as one assessment value to obtain the objective quality evaluation parameters of the original entire image. The simulation results show that compared to the traditional method, the proposed algorithm is more consistent with the subjective evaluation results with the Pearson correlation coefficient increased 0.01 and less complex with half running time.%针对传统JPEG压缩图像质量评价算法存在高计算复杂度的问题，通过改进经典的JPEG压缩图像质量评价算法，以无参考为基础，提出一种快速有效的质量评价算法。该算法将人眼视觉系统特性引入到图像质量评价体系中，利用局部方差选取人眼感兴趣图像块代替整体图像，并只针对感兴趣图像块做特征提取处理，计算得出3个图像的特征值，最后将所有特征值整合为一个评价值，获取原始整体图像的客观质量评价参数。仿真测试结果表明，与传统整体图像JPEG压缩图像评价算法相比，该算法皮尔逊相关系数提高0．01，与主观评价结果更为一致；运算速度提高一倍，降低了运算复杂度。