Local inverse tone mapping for scalable high dynamic range image coding
Tone mapping operators (TMOs) and inverse TMOs (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the high nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this letter, we present a two-layer local iTMO estimat...
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sg-ntu-dr.10356-1421982020-06-17T04:46:19Z Local inverse tone mapping for scalable high dynamic range image coding Wei, Zhe Wen, Changyun Li, Zhengguo School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Edge-preserving Decomposition High Dynamic Range (HDR) Tone mapping operators (TMOs) and inverse TMOs (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the high nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this letter, we present a two-layer local iTMO estimation algorithm using an edge-preserving decomposition technique. The low dynamic range (LDR) image is first linearized and then decomposed into a base layer and a detail layer via a fast edge-preserving decomposition method. The base layer of the HDR image is generated by subtracting the LDR detail layer from the HDR image. An iTMO function is finally estimated by solving a novel quadratic optimization problem formulated on the pair of base layers rather than the pair of HDR and LDR images as in existing methods. Experimental results show that the proposed two-layer iTMO can recover the HDR accurately so that it is possible to use these local TMOs in scalable HDR image coding schemes. 2020-06-17T04:46:19Z 2020-06-17T04:46:19Z 2016 Journal Article Wei, Z., Wen, C., & Li, Z. (2018). Local inverse tone mapping for scalable high dynamic range image coding. IEEE Transactions on Circuits and Systems for Video Technology, 28(2), 550-555. doi:10.1109/TCSVT.2016.2611944 1051-8215 https://hdl.handle.net/10356/142198 10.1109/TCSVT.2016.2611944 2-s2.0-85041957633 2 28 550 555 en IEEE Transactions on Circuits and Systems for Video Technology © 2016 IEEE. All rights reserved. |
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Engineering::Electrical and electronic engineering Edge-preserving Decomposition High Dynamic Range (HDR) Wei, Zhe Wen, Changyun Li, Zhengguo Local inverse tone mapping for scalable high dynamic range image coding |
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Tone mapping operators (TMOs) and inverse TMOs (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the high nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this letter, we present a two-layer local iTMO estimation algorithm using an edge-preserving decomposition technique. The low dynamic range (LDR) image is first linearized and then decomposed into a base layer and a detail layer via a fast edge-preserving decomposition method. The base layer of the HDR image is generated by subtracting the LDR detail layer from the HDR image. An iTMO function is finally estimated by solving a novel quadratic optimization problem formulated on the pair of base layers rather than the pair of HDR and LDR images as in existing methods. Experimental results show that the proposed two-layer iTMO can recover the HDR accurately so that it is possible to use these local TMOs in scalable HDR image coding schemes. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Wei, Zhe Wen, Changyun Li, Zhengguo |
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Article |
author |
Wei, Zhe Wen, Changyun Li, Zhengguo |
author_sort |
Wei, Zhe |
title |
Local inverse tone mapping for scalable high dynamic range image coding |
title_short |
Local inverse tone mapping for scalable high dynamic range image coding |
title_full |
Local inverse tone mapping for scalable high dynamic range image coding |
title_fullStr |
Local inverse tone mapping for scalable high dynamic range image coding |
title_full_unstemmed |
Local inverse tone mapping for scalable high dynamic range image coding |
title_sort |
local inverse tone mapping for scalable high dynamic range image coding |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/142198 |
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1681056649581690880 |