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Title: High dynamic range image and video compression
Author: Zhang, Yang
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2015
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High dynamic range (HDR) technology (capture and display) call offer high levels of immersion through a dynamic range that meets and exceeds that of the Human visual system (HVS). This increase in immersion comes at the cost of higher bit-depth, bandwidth and memory requirements, which are significantly higher than those of conventional Low dynamic range (LDR) content. The challenge is thus to develop a coding solution to efficiently compress HDR images and video into a manageable bitrate without compromising perceptual quality. Over the past century, a large number of psycho-visual experiments have been carried out by psychologists and physiologists with the goal of understanding how the HVS works. One of the human vision phenomena concerns reduced sensitivity to patterns of low and high spatial-frequencies. This phenomenon is parametrized by the contrast sensitivity function (CSF). In this thesis, proper luminance and chrominance CSFs have been employed, in conjunction with an optimised wavelet 1mb-band weighting method. Experimental results indicate that the proposed method ontperforms previous approaches and operates in accordance with the characteristics of the HVS, when tested objectively using a HDR Visible Difference Predictor (VDP), and subjective evaluation. The HVS shows non-linear sensitivity to the distortion introduced by lossy image and video coding. Two psycho-visual experiments were performed using of a high dynamic range display, in order to determine the potential differences between LDR and HDR edge masking (EM) and luminance masking (LM) effects. The EM experimental results indicate that the visibility threshold is higher for the case of HDR content than for LDR, especially on the dark background side of an edge. The LM experimental results suggest that the HDR visibility threshold is higher compared to that of SDR for both dark and bright luminance backgrounds. A novel perception-based quantization method that exploits luminance masking in the HVS in order to enhance the performance of the High Efficiency Video Coding (HEVC) standard for the case of HDR video content has been proposed in this thesis . The proposed method has been integrated into the reference codec considered for the HEVC range extensions and its performance was assessed by measuring the bitrate reduction against the codec without perceptual quantization. The results indicate that the proposed method achieves significant bitrate savings, up to 42.2%, compared to HEVC at the same objective quality (based on HDR-VDP- 2) and subjective evaluation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available