[1]王荔霞,谢维信,李利勇,等.一种遥感多光谱图像去云雾方法[J].深圳大学学报理工版,2013,30(No.6(551-660)):592-597.[doi:10.3724/SP.J.1249.2013.06592]
 Wang Lixia,Xie Weixin,Li Liyong,et al.A thin cloud and fog removal method for remote sensing multi-spectral images[J].Journal of Shenzhen University Science and Engineering,2013,30(No.6(551-660)):592-597.[doi:10.3724/SP.J.1249.2013.06592]
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一种遥感多光谱图像去云雾方法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第30卷
期数:
2013年No.6(551-660)
页码:
592-597
栏目:
光电工程
出版日期:
2013-09-30

文章信息/Info

Title:
A thin cloud and fog removal method for remote sensing multi-spectral images
文章编号:
20130607
作者:
王荔霞谢维信李利勇裴继红
深圳大学信息工程学院,深圳 518060
Author(s):
Wang Lixia Xie Weixin Li Liyong and Pei Jihong
College of Information Engineering, Shenzhen University, Shenzhen 518060, P.R.China
关键词:
遥感图像处理多光谱图像云雾去除雾天退化模型暗通道先验大气成分值透射率
Keywords:
remote sensing image processing multi-spectral image cloud and fog removal image degradation model dark channel prior atmospheric light transmission
分类号:
TP 751.1
DOI:
10.3724/SP.J.1249.2013.06592
文献标志码:
A
摘要:
提出一种基于暗通道先验的遥感多光谱图像云雾去除方法,扩展了图像云雾退化模型,使其从只能描述三通道彩色图像推广到可描述任意多波段遥感多光谱图像的情况.根据图像暗通道先验知识,推导出遥感多光谱图像的暗通道先验描述式,给出大气成分值和透射率计算公式,以及遥感多光谱图像的云雾去除公式,计算得到还原后的各波段图像.实验证明,该算法充分融合了遥感多光谱图像的各个波段信息,能有效去除薄云薄雾干扰,还原后得到的图像包含更丰富的细节信息和完整的空间特征信息.
Abstract:
A dark channel prior cloud and fog removal method for remote sensing multi-spectral images is proposed based on the prior knowledge of dark channel. Firstly, the image degradation model for three-channel color images is extended to enable the description of multi-channel remote sensing images. The proposed model includes more than three channels. Secondly, according to the prior knowledge of dark channel prior, the atmospheric light and transmission for remote sensing multi-spectral images are derived. Finally, based on the obtained atmospheric light and transmission, a new recovering model for remote sensing multi-spectral images is applied to obtain cloud-free and fog-free images. Experimental results show that the multi-spectral images after thin cloud and fog removal by our method are more distinctive with less loss of space information.

参考文献/References:

[1] Li Hongli, Shen Huanfeng, Du Bo, et al. A high-fidelity method of removing thin cloud from remote sensing digital images based on homomorphic filtering [J]. Remote Sensing Application, 2011, 10(1):41-44.(in Chinese).
李洪利,沈焕锋,杜博,等. 一种高保真同态滤波遥感影像薄云去除方法[J].遥感应用,2011,10(1):41-44.
[2] Cai Wenting, Liu Yongxue, Li Manchun, et al. A self-adaptive homomorphic filter method for removing thin cloud [C]// Proceedings of the 19th IEEE International Conference on Geoinformatics. Shanghai(China): IEEE Press, 2011: 1-4.
[3] Ren Huan, Li Liangchao, Jin Lanhai, et al. Study on cloud processing with MODIS data and application [C]// Proceedings of the 10th IEEE International Symposium on Antennas, Propagation & EM Theory (ISAPE). Xi’an(China): IEEE Press, 2012: 583-586.
[4] Kim T K, Paik J K, Kang B S. Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering [J]. IEEE Transactions on Consumer Electronics, 1998, 44(1):82-86.
[5] Inampud R B, Purimetla T N, Satyanarayana P G. Contrast degradation for improving quality of an image [J]. Geoscience and Remote Sensing Symposium, 2002, 6:3408-3410.
[6] Shi Wenxuan, Li Jie. Research on algorithms in defog of remote sensing image [J]. Spacecraft Recovery & Remote Sensing, 2010, 31(6): 46-51.(in Chinese)
石文轩, 李婕. 遥感图像去雾算法研究[J]. 航天返回与遥感, 2010, 31(6): 46-51.
[7] Parthasarathy S,Sankaran P.A retinex based haze removal method [C]// Proceedings of the 7th IEEE International Conference on Industrial and Information Systems (ICIIS).Chennai (India): IEEE Press, 2012:1-6.
[8] Ma Yunfei, He Wenzhang. Foggy day image enhancement method based on wavelet transform [J]. Computer Applications and Software, 2011, 28(2):71-73.(in Chinese).
马云飞, 何文章. 基于小波变换的雾天图像增强方法[J]. 计算机应用与软件, 2011, 28(2):71-73.
[9] He Kaiming, Sun Jian, Tang Xiao’ou. Single image haze removal using dark channel prior [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12):2341-2353.
[10] He Renjie, Wang Zhiyong, Xiong Hao, et al. Single image dehazing with white balance correction and image decomposition [C]// Proceedings of the International Conference on Digital Image Computing Techniques and Applications (DICTA).Fremantle (Australia): IEEE Press, 2012:1-7.
[11] Yang Hungyu, Chen Peiyin, Shiau Yeuhorng, et al. Low complexity underwater image enhancement based on dark channel prior [C]// Proceedings of the Second International Conference on Innovations in Bio-inspired Computing and Applications. Shenzhen(China): IEEE Press, 2011:17-20.
[12] Jin Wenbo, Mi Zengyuan, Wu Xiaotian, et al. Single image de-haze based on a new dark channel estimation method [C]// Proceedings of the IEEE International Conference on Computer Science and Automation Engineering (CSAE). Zhangjiajie(China): IEEE Press, 2012, 2:791-795.
[13] Wang Shizhen, Shi Huiqiong, Zeng Lingsha, et al. Haze removal methods of remote sensing image using dark channel prior [J]. Journal of Geomatics Science and Technology, 2011, 28(3):182-186.(in Chinese)
王时震, 石惠琼, 曾令沙, 等. 应用暗通道先验规律的遥感影像去雾技术[J]. 测绘科学技术学报, 2011, 28(3):182-186.
[14] Zhou Liya, Qin Zhiyuan. Uneven cloud and fog removing for satellite remote sensing image [C]// Proceedings of the 2nd International Conference on Mechanic Automation and Control Engineering (MACE). Hohhot(China): IEEE Press, 2011:5485-5488.
[15] Long Jiao, Shi Zhenwei, Tang Wei, et al. Single remote sensing image dehazing [J]. IEEE Geoscience and Remote Sensing Letters, 2013, 11(1): 59-63.

备注/Memo

备注/Memo:
Received:2013-09-08;Revised:2013-10-20
Foundation:National Defense Pre-Study Foundation of China (9140***9302);National Natural Science Foundation of China (61071206)
Corresponding author:Professor Pei Jihong. E-mail:jhpei@szu.edu.cn
Citation:Wang Lixia, Xie Weixin, Li Liyong, et al. A thin cloud and fog removal method for remote sensing multi-spectral images[J]. Journal of Shenzhen University Science and Engineering, 2013, 30(6): 592-597.(in Chinese)
基金项目:国防预研基金资助项目 (9140***9302);国家自然科学基金资助项目(61071206)
作者简介:王荔霞(1978-),女(汉族),福建省莆田市人,深圳大学博士研究生. E-mail:xixiccy@qq.com
引文:王荔霞,谢维信,李利勇,等.一种遥感多光谱图像去云雾方法[J]. 深圳大学学报理工版,2013,30(6):592-597.
更新日期/Last Update: 2013-11-20