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Conference Paper Measure and Prediction of HEVC Perceptually Lossy/Lossless Boundary QP Values
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Authors
Qin Huang, Haiqiang Wang, Sung Chang Lim, Hui Yong Kim, Se Yoon Jeong, C.-C. Jay Kuo
Issue Date
2017-04
Citation
Data Compression Conference (DCC) 2017, pp.1-10
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/DCC.2017.17
Abstract
Evaluation of coding efficiency is traditionally modeled as a continuous rate-distortion (R-D) function, where the peak signal-To-noise ratio (PSNR) is adopted as the quality measure. Although the PSNR-versus-bitrate curve offers some useful tradeoff information between video quality and coding bit-rates, it does not take human perceptual experience into account. In this work, by following the recent image/video quality assessment framework based on the just-noticeable-difference (JND) notion, we conduct a subjective test for HEVC (High Efficiency Video Codec) video to measure the QP value that lies in the boundary of perceptually lossless and lossy coded bit streams for each human subject. This is also known as the first JND point. It is observed that the statistics of the first JND points of 30 subjects follows the normal distribution for a great majority of test sequences. Finally, a machine-learning approach is proposed to predict the mean of the group-based JND distribution based on extracted video features. It is shown by experimental results that the mean JND point can be predicted accurately.
KSP Keywords
Bit rate, Coding efficiency, High Efficiency Video coding(HEVC), Human subjects, Learning approach, Normal Distribution, Peak-Signal-to-Noise-Ratio(PSNR), Quality measure, Rate-Distortion, Signal noise ratio(SNR), Subjective test