Gabor传递函数相似性测度图像质量评价算法

Algorithm of Image Quality Evaluation with Gabor Transfer Function Similarity Measure

数字图像在压缩和融合等处理中会产生退化效应,当前对图像退化中质量评价指标如均方误差(MSE),峰值信噪比(PSNR)等不能有效反映图像在退化过程中传递性能,而只是单纯计算图像之间灰度值差异,对图像质量评价不准。提出一种利用Gabor传递函数相似性测度为评价指标的图像质量评价算法,采用图像的亮度、对比度和结构相似度为场景结构基准特征,设计Gabor传递函数。通过双正交滤波器得到Gabor传递函数相似性测度,该指标能有效反映图像退化演变过程中的传递性能,合理评价参考图像和失真图像质量。仿真实验表明,利用Gabor传递函数相似性测度指标评价图像质量,能准确反映图像失真等级,在几乎所有失真类型上都能有较满意的结果,评价结果比较稳定。

Digital image compression and fusion process produces will result in degradation effect, the current image quality evaluation index such as the mean square error （MSE）, peak signal to noise ratio （PSNR） and other objects cannot effective-ly reflect the performance degradation process of passing. The image quality evaluation is bad. An image quality evaluation algorithm called Gabor transfer function r similarity measure was proposed. The image brightness, contrast and structural similarity to the reference scenario structural characteristics were extracted. Gabor transfer function was designed. Similari-ty measure was got based on Gabor transfer function and biorthogonal filters. The index can effectively show the evolution of image degradation transfer performance evaluation of the reference image and the distortion reasonable image quality. Simulation results show that this algorithm can reflect the level of distortion on almost all types of distortions, and the evalu-ation results more stable.