Learning to display high dynamic range images

Qiu, Guoping, Duan, Jiang and Finlayson, Graham D. (2007) Learning to display high dynamic range images. Pattern Recognition, 40 (10). pp. 2641-2655. ISSN 0031-3203

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Abstract

In this paper, we present a learning-based image processing technique. We have developed a novel method to map high dynamic range scenes to low dynamic range images for display in standard (low dynamic range) reproduction media. We formulate the problem as a quantization process and employ an adaptive conscience learning strategy to ensure that the mapped low dynamic range displays not only faithfully reproduce the visual features of the original scenes, but also make full use of the available display levels. This is achieved by the use of a competitive learning neural network that employs a frequency sensitive competitive learning mechanism to adaptively design the quantizer. By optimizing an L2 distortion function, we ensure that the mapped low dynamic images preserve the visual characteristics of the original scenes. By incorporating a frequency sensitive competitive mechanism, we facilitate the full utilization of the limited displayable levels. We have developed a deterministic and practicable learning procedure which uses a single variable to control the display result. We give a detailed description of the implementation procedure of the new learning-based high dynamic range compression method and present experimental results to demonstrate the effectiveness of the method in displaying a variety of high dynamic range scenes.

Item Type:	Article
Additional Information:	See also "Erratum to 'Learning to display high dynamic range images'" Pattern Recognition, Volume 41, Issue 4, April 2008, Page 1428, Guoping Qiu, Jiang Duan, Graham D. Finlayson
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Interactive Graphics and Audio Faculty of Science > Research Groups > Colour and Imaging Lab
Depositing User:	Vishal Gautam
Date Deposited:	03 Mar 2011 09:59
Last Modified:	24 Sep 2024 09:37
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23672
DOI:	10.1016/j.patcog.2007.02.012

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