No-reference Remote Sensing Image Quality Assessment Based on Natural Scene Statistical in Wavelet Domain

Remote sensing images are most likely affected by both blur and noise, which makes the quality of them are difficult to obtain for they can not come down to one certain distortion type. Based on the natural scene statistical feature of natural image, the means of wavelet subbands coefficient amplitudes decrease approximately linearly with scale index. This linear feature can be destroyed by both noise and blurness in different ways, according to the quantitative analysis of the destroyed degree, both blur strength and noise strength of an image can be obtained. Finally, the weighted sum of them are considered as the eventual quality index of the remote sensing image. The experiment shows that, compare with the Peak Signal-Noise Rate (PSNR) index, the proposed index has better consistence with the Structure SIMilarity (SSIM) index, and can make an effective and correct evaluation of noise image, blur image or image with both noise and blur.