Objective Image and Video Quality Assessment
Original Publication Date: 2002-Jan-07
Included in the Prior Art Database: 2003-Jun-20
Objective Video Quality Assessment I. INTRODUCTION Perceptual video quality is often essential in many video applications. For examples, video restoration and enhancement try to optimize certain quality metrics. In video coding and communications, a good quality metrics is fundamentally important throughout the system. At the encoder, it is used in optimal coding and pre-processing algorithms. At the decoder, it can be used in post-processing to improve the visual quality. Quality metrics is also very instrumental for video transcoders, network servers and switches to control and monitor the video service quality. The existing international standard for subjective video quality assessment relies on human experts. Indeed the industry has used this standard for many years. However, it is inconvenient and expensive. The goal of objective video quality assessment research is to develop some quality metrics that can be implemented by mathematical algorithm to automatically predict the perceptual quality of video. The most commonly used objective quality metrics is Peak Signal-to-Noise ratio (PSNR). However, PSNR is widely known to have poor correlation with perceptual image and video quality.