A method for assessing photorealistic image quality with high resolution

The article proposes a method for assessing photorealistic image quality based on a comparison of the detail coefficients in the original and distorted images. An algorithm for identifying fine structures of the original image uses operations of active pixels segmentation, which include point objects, thin lines and texture fragments. The number of active pixels is estimated by the value of a fine detail factor (FDF), which is determined by the ratio of active pixels to the total number of image pixels. The same algorithm is used to calculate the FDF of the distorted image and, further, the image quality deterioration is estimated by comparing the obtained values. Special features of the method include the fact that the identification of small structures and the segmentation of active pixels are performed in the normalized system N-CIELAB. The algorithm also takes into account the influence of false microstructures on the results of the restored image estimating. Features of the construction of neural networks SRCNN in the tasks of a qualitative increase in the image resolution with the restoration of fine structures are considered. Results of the analysis of the quality of enlarged images by the traditional metrics PSNR and SSIM, as well as by the proposed method are also presented.