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
Une synthèse d'image HDR (High Dynamic Range) est une méthode qui consiste à photographier des scènes avec une large plage de luminance et à reproduire des images proches de scènes visuelles réelles sur un écran LDR (Low Dynamic Range). En général, les images HDR sont reproduites en prenant des images avec différentes expositions de caméra et en utilisant la synthèse tonale de plusieurs images. Dans cet article, nous proposons une méthode de mappage de tonalité d'image HDR basée sur une fonction de luminosité visuelle utilisant des images à double exposition et un algorithme de synthèse basé sur le surround local. L'algorithme proposé a amélioré les erreurs de limite et la balance des couleurs par rapport aux méthodes existantes. En outre, il améliore le flou et l’amplification du bruit grâce au mixage des images.
Sung-Hak LEE
Kyungpook National University
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Sung-Hak LEE, "HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion" in IEICE TRANSACTIONS on Electronics,
vol. E102-C, no. 11, pp. 802-809, November 2019, doi: 10.1587/transele.2019DIP0001.
Abstract: An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.2019DIP0001/_p
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@ARTICLE{e102-c_11_802,
author={Sung-Hak LEE, },
journal={IEICE TRANSACTIONS on Electronics},
title={HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion},
year={2019},
volume={E102-C},
number={11},
pages={802-809},
abstract={An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.},
keywords={},
doi={10.1587/transele.2019DIP0001},
ISSN={1745-1353},
month={November},}
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TY - JOUR
TI - HDR Image Synthesis Using Visual Brightness Mapping and Local Surround-Based Image Fusion
T2 - IEICE TRANSACTIONS on Electronics
SP - 802
EP - 809
AU - Sung-Hak LEE
PY - 2019
DO - 10.1587/transele.2019DIP0001
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E102-C
IS - 11
JA - IEICE TRANSACTIONS on Electronics
Y1 - November 2019
AB - An HDR (High Dynamic Range) image synthesis is a method which is to photograph scenes with wide luminance range and to reproduce images close to real visual scenes on an LDR (Low Dynamic Range) display. In general, HDR images are reproduced by taking images with various camera exposures and using the tone synthesis of several images. In this paper, we propose an HDR image tone mapping method based on a visual brightness function using dual exposed images and a synthesis algorithm based on local surround. The proposed algorithm has improved boundary errors and color balance compared with existing methods. Also, it improves blurring and noise amplification due to image mixing.
ER -