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Proceedings Paper

Image and video compression for HDR content
Author(s): Yang Zhang; Erik Reinhard; Dimitris Agrafiotis; David R Bull
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Paper Abstract

High Dynamic Range (HDR) technology can offer high levels of immersion with a dynamic range meeting and exceeding that of the Human Visual System (HVS). A primary drawback with HDR images and video is that memory and bandwidth requirements are significantly higher than for conventional images and video. Many bits can be wasted coding redundant imperceptible information. The challenge is therefore to develop means for efficiently compressing HDR imagery to a manageable bit rate without compromising perceptual quality. In this paper, we build on previous work of ours and propose a compression method for both HDR images and video, based on an HVS optimised wavelet subband weighting method. The method has been fully integrated into a JPEG 2000 codec for HDR image compression and implemented as a pre-processing step for HDR video coding (an H.264 codec is used as the host codec for video compression). Experimental results indicate that the proposed method outperforms previous approaches and operates in accordance with characteristics of the HVS, tested objectively using a HDR Visible Difference Predictor (VDP). Aiming to further improve the compression performance of our method, we additionally present the results of a psychophysical experiment, carried out with the aid of a high dynamic range display, to determine the difference in the noise visibility threshold between HDR and Standard Dynamic Range (SDR) luminance edge masking. Our findings show that noise has increased visibility on the bright side of a luminance edge. Masking is more consistent on the darker side of the edge.

Paper Details

Date Published: 15 October 2012
PDF: 13 pages
Proc. SPIE 8499, Applications of Digital Image Processing XXXV, 84990H (15 October 2012); doi: 10.1117/12.931500
Show Author Affiliations
Yang Zhang, Univ. of Bristol (United Kingdom)
Erik Reinhard, Univ. of Bristol (United Kingdom)
Max-Planck-Institut für Informatik (Germany)
Dimitris Agrafiotis, Univ. of Bristol (United Kingdom)
David R Bull, Univ. of Bristol (United Kingdom)


Published in SPIE Proceedings Vol. 8499:
Applications of Digital Image Processing XXXV
Andrew G. Tescher, Editor(s)

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