Linking Bitstream Information to QoE: A Study on Still Images Using HEVC Intra Coding

Abstract

The coding tools used in image and video encoders aim at high perceptual quality for low bi-trates. Analyzing the results of the encoders in terms of quantization parameter, image partitioning, prediction modes or residuals may provide important insight into the link between those tools and the human perception. As a first step, this contribution analyzes the possibility to transcode reference images of three well-known image databases, i.e. IRCCyN/IVC, LIVE and TID2013, from their original, older formats to HEVC; thus creating a homogeneous database of 327 HEVC encoded images accompanied with bitstream parameters and values obtained from objective and subjective as-sessments. Secondly, it analyzes some of the HEVC intra coding parameters regarding their influence on the image quality by using machine learning, namely Support Vector Machine - Regression