The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, nous proposons une méthode de codage pour les images brutes d’appareil photo avec des plages dynamiques élevées. Notre encodeur a deux couches. Dans la première couche, une image à faible plage dynamique de 24 bits est codée par un codec conventionnel, puis l'image résiduelle qui représente la différence entre l'image brute et son approximation est codée dans la deuxième couche. L'approximation est dérivée par un ajustement polynomial. Le principal avantage de cette approche est que l’application du modèle polynomial réduit la corrélation entre les images brutes et 24 bits, ce qui augmente l’efficacité du codage. Les expériences montrent que l'efficacité de la compression est considérablement améliorée en prenant en compte un mappage de tonalité inverse.
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Masahiro OKUDA, Nicola ADAMI, "JPEG Compatible Raw Image Coding Based on Polynomial Tone Mapping Model" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 10, pp. 2928-2933, October 2008, doi: 10.1093/ietfec/e91-a.10.2928.
Abstract: In this paper, we propose a coding method for camera raw images with high dynamic ranges. Our encoder has two layers. In the first layer, 24 bit low dynamic range image is encoded by a conventional codec, and then the residual image that represents the difference between the raw image and its approximation is encoded in the second layer. The approximation is derived by a polynomial fitting. The main advantage of this approach is that applying the polynomial model reduces the correlation between the raw and 24 bit images, which increases coding efficiency. Experiments shows compression efficiency is significantly improved by taking an inverse tone mapping into account.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.10.2928/_p
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@ARTICLE{e91-a_10_2928,
author={Masahiro OKUDA, Nicola ADAMI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={JPEG Compatible Raw Image Coding Based on Polynomial Tone Mapping Model},
year={2008},
volume={E91-A},
number={10},
pages={2928-2933},
abstract={In this paper, we propose a coding method for camera raw images with high dynamic ranges. Our encoder has two layers. In the first layer, 24 bit low dynamic range image is encoded by a conventional codec, and then the residual image that represents the difference between the raw image and its approximation is encoded in the second layer. The approximation is derived by a polynomial fitting. The main advantage of this approach is that applying the polynomial model reduces the correlation between the raw and 24 bit images, which increases coding efficiency. Experiments shows compression efficiency is significantly improved by taking an inverse tone mapping into account.},
keywords={},
doi={10.1093/ietfec/e91-a.10.2928},
ISSN={1745-1337},
month={October},}
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TY - JOUR
TI - JPEG Compatible Raw Image Coding Based on Polynomial Tone Mapping Model
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2928
EP - 2933
AU - Masahiro OKUDA
AU - Nicola ADAMI
PY - 2008
DO - 10.1093/ietfec/e91-a.10.2928
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2008
AB - In this paper, we propose a coding method for camera raw images with high dynamic ranges. Our encoder has two layers. In the first layer, 24 bit low dynamic range image is encoded by a conventional codec, and then the residual image that represents the difference between the raw image and its approximation is encoded in the second layer. The approximation is derived by a polynomial fitting. The main advantage of this approach is that applying the polynomial model reduces the correlation between the raw and 24 bit images, which increases coding efficiency. Experiments shows compression efficiency is significantly improved by taking an inverse tone mapping into account.
ER -