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
Como o método de desembaçamento baseado no canal escuro anterior (DCP) é ineficaz na área do céu e causará o problema de muito escuro e distorção de cor da imagem, propomos um novo método de desembaçamento baseado na segmentação da área do céu e na fusão de imagens. Primeiro segmentamos a imagem de acordo com as características da área do céu e da área fora do céu da imagem, depois estimamos a luz atmosférica e o mapa de transmissão de acordo com o DCP e os corrigimos e, em seguida, fundimos a imagem original após a equalização do histograma adaptativo de contraste para melhorar as informações detalhadas da imagem. Experimentos ilustram que nosso método tem um bom desempenho na desembaçamento e pode reduzir a distorção da imagem.
Xiangyang CHEN
Anqing Medical College
Haiyue LI
Chizhou University
Chuan LI
Chongqing College of International Business and Economics
Weiwei JIANG
Beijing University of Posts and Telecommunications
Hao ZHOU
Chizhou University,Chongqing College of International Business and Economics,Anhui University of Technology
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Xiangyang CHEN, Haiyue LI, Chuan LI, Weiwei JIANG, Hao ZHOU, "Single Image Dehazing Based on Sky Area Segmentation and Image Fusion" in IEICE TRANSACTIONS on Information,
vol. E106-D, no. 7, pp. 1249-1253, July 2023, doi: 10.1587/transinf.2023EDL8010.
Abstract: Since the dark channel prior (DCP)-based dehazing method is ineffective in the sky area and will cause the problem of too dark and color distortion of the image, we propose a novel dehazing method based on sky area segmentation and image fusion. We first segment the image according to the characteristics of the sky area and non-sky area of the image, then estimate the atmospheric light and transmission map according to the DCP and correct them, and then fuse the original image after the contrast adaptive histogram equalization to improve the details information of the image. Experiments illustrate that our method performs well in dehazing and can reduce image distortion.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2023EDL8010/_p
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@ARTICLE{e106-d_7_1249,
author={Xiangyang CHEN, Haiyue LI, Chuan LI, Weiwei JIANG, Hao ZHOU, },
journal={IEICE TRANSACTIONS on Information},
title={Single Image Dehazing Based on Sky Area Segmentation and Image Fusion},
year={2023},
volume={E106-D},
number={7},
pages={1249-1253},
abstract={Since the dark channel prior (DCP)-based dehazing method is ineffective in the sky area and will cause the problem of too dark and color distortion of the image, we propose a novel dehazing method based on sky area segmentation and image fusion. We first segment the image according to the characteristics of the sky area and non-sky area of the image, then estimate the atmospheric light and transmission map according to the DCP and correct them, and then fuse the original image after the contrast adaptive histogram equalization to improve the details information of the image. Experiments illustrate that our method performs well in dehazing and can reduce image distortion.},
keywords={},
doi={10.1587/transinf.2023EDL8010},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Single Image Dehazing Based on Sky Area Segmentation and Image Fusion
T2 - IEICE TRANSACTIONS on Information
SP - 1249
EP - 1253
AU - Xiangyang CHEN
AU - Haiyue LI
AU - Chuan LI
AU - Weiwei JIANG
AU - Hao ZHOU
PY - 2023
DO - 10.1587/transinf.2023EDL8010
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E106-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2023
AB - Since the dark channel prior (DCP)-based dehazing method is ineffective in the sky area and will cause the problem of too dark and color distortion of the image, we propose a novel dehazing method based on sky area segmentation and image fusion. We first segment the image according to the characteristics of the sky area and non-sky area of the image, then estimate the atmospheric light and transmission map according to the DCP and correct them, and then fuse the original image after the contrast adaptive histogram equalization to improve the details information of the image. Experiments illustrate that our method performs well in dehazing and can reduce image distortion.
ER -