Comparison of Image Quality Assessment: PSNR, HVS, SSIM, UIQI

Abstract

Abstract — Measuring the quality of the image is a complicated and hard process since humans opinion is affected by physical and psychological parameters. Many techniques are proposed for measuring the quality of the image but none of it is considered to be perfect for measuring the quality. Image quality assessment plays an important role in the field of image processing. Many studies have been done on image quality measurements based on different techniques such as pixel- difference, correlation, edge detection, neural networks (NN), region of interest(ROI), human visual system (HVS). The good IQM must be accurate and consistent in predicting the quality. Most IQ metrics are related to the difference between two images (the original and the distorted image).