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A pretreatment to improve the quality metrics performance for encoding H264/AVC
Author(s) -
Ben Amor Mohamed,
Kammoun Fahmi,
Masmoudi Nouri
Publication year - 2016
Publication title -
journal of the society for information display
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 52
eISSN - 1938-3657
pISSN - 1071-0922
DOI - 10.1002/jsid.428
Subject(s) - computer science , codec , peak signal to noise ratio , artificial intelligence , mean squared error , human visual system model , computer vision , video quality , sensitivity (control systems) , coding (social sciences) , subjective video quality , image quality , scalable video coding , fast fourier transform , motion compensation , algorithm , mathematics , image (mathematics) , statistics , telecommunications , electronic engineering , metric (unit) , operations management , engineering , economics
Abstract The study of the human visual system is very interesting to quantify the quality of an image or to predict perceived information. The contrast sensitivity function is one of the main ways to incorporate the human visual system properties in an imaging system. It characterizes its sensitivity to spatial frequencies. In this paper, we are interested in establishing a pretreatment for existing metrics with full reference (“peak signal‐to‐noise ratio”, “digital video quality”) for the H.264/MPEG‐4 (Motion Picture Expert Group) advanced video coding standard. We realize in our algorithm the FFT transformation to apply the contrast sensitivity function. Our method is applicable to any size of image and video sequence by increasing its size at powers of two. This increase is achieved by adding “mirror image.” We evaluate the performance of the proposed pretreatment by using subjective “LIVE” video databases. The performance metrics, that is, Pearson (PLCC), Spearman correlation coefficients (SROCC) and root mean square prediction error (RMSE) indicate that the proposed method gives a good performance in H264 codec distortions.