期刊文献+

基于颜色失真去除与暗通道先验的水下图像复原 被引量:30

Underwater Image Restoration Based on Color Cast Removal and Dark Channel Prior
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摘要 水下图像成像过程与雾天图像虽然类似,但因水对光的选择性吸收和光的散射作用,水下图像存在颜色衰减并呈现蓝(绿)色基调,传统的去雾方法用于水下图像复原时效果欠佳。针对这类方法出现的缺点,该文根据先去除颜色失真后去除背景散射的思路,提出一种新的水下图像复原方法。结合光在水中的衰减特性,提出适用于水下图像的颜色失真去除方法,并利用散射系数与波长的关系修正各通道透射率;另外,该文改进的背景光估计方法可有效避免人工光源、白色物体、噪声等影响。实验结果证明,该文方法在恢复场景物体原本颜色和去除背景散射方面效果良好。 The imaging process of the underwater image is similar to the haze image. However, the dehazing methods fail when used in the underwater image restoration because of the color attenuation and blue (green) color tone, caused by the selective absorption of water and light scattering. Thus, this paper proposes a new approach for underwater images restoration based on the idea of removing backscattering after the color cast removal. Due to the attenuation of light in water, a color cast removal approach is proposed. The relationship between scattering coefficient and wavelength is used to obtain a more accurate transmission estimation for each color channel. In addition, an improved algorithm for background light estimation is presented, which can effectively avoid the influence of artificial light, white object and noise. Experimental results demonstrate the effectiveness of the proposed method in restoring the original color of the scene and removing the backscattering.
出处 《电子与信息学报》 EI CSCD 北大核心 2015年第11期2541-2547,共7页 Journal of Electronics & Information Technology
基金 国家自然科学基金(61372145 61472274 61201371)~~
关键词 图像处理 颜色失真 背景散射 暗通道先验 透射率 Image processing Color cast Backscattering Dark channel prior Transmission map
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参考文献19

  • 1Schettini R and Corchs S. Underwater image processing: state of the art of restoration and image enhancement methods[J]. EURASIP Journal on Advances in Signal Processing, 2010(1), 2010: 1-14.
  • 2Ancuti C, Ancuti C (), Haber T, et al.. Enhancing underwater images and videos by fusion[C]. IEEE Conference oil Computer Vision and Pattern Recognition, Providence, USA, 2012: 81--88.
  • 3Fu Xue-yang, Zhuang Pei-xian, Huang Yue, et al.. A retinex- based enhancing al)proach for single underwater image[C]. IEEE Irlternational Conference on Image Processing, Paris, 2014: 4572-4576.
  • 4张问一,胡东辉,丁赤飚.基于Goldstein滤波器的SAR海洋图像增强方法[J].电子与信息学报,2012,34(9):2263-2267. 被引量:1
  • 5Hou W L, Gray D J, "Weidemmm A D, et al.. Automated underwater image restoration and retrieval of related optical properties[C]. IEEE International Geoscience and Remote Sensing Symposium, Barcelona, 2007: 1889-1892.
  • 6Stephan T, Frtihberger P, Werling S, et al.. Model based image restoration fbr underwater images[C]. SPIE Optical Metrology 2013.
  • 7International Society for Optics and Photonics, Munich, 2013: 87911F-87911F-9. Chiang J Y and Chen Ying-Ching. Underwater image enhancement by wavelength compensation and dehazing[J]. IEEE Transactions on Image Processing, 2012, 21(4): 1756-1769.
  • 8Li Yu-Jie, Lu Hui-min, Zhang Li-feng, et al.. Real-time visualization system for deep-sea surveying[J]. Mathematical Problems in Engineering, 2014, 2014:110.
  • 9Jaffe J S. Computer modeling and the design of optimal underwater imaging systems[J]. IEEE Journal of OceanicEngineering, 1990, 15(2): 101 111.
  • 10Jaffe J S. Underwater optical imaging: the past, tile present, and the prospects[J]. IEEE ,Jour"rml of Oce~mic Er~g'ir~eeT~ir~g, 2014, 4O(3): 683-700.

二级参考文献9

  • 1Vehel J L. Evolutionary signal enhancement based on Holder regularity analysis[OL], http://www-rocq.inria.fr/fractales, 2006.
  • 2Carlson G E. Wavelet processing of SAR ocean wave images[C]. Proceedings of 1995 Geoscience and Remote Sensing Symposium, Firenze, Italy, 1995: 679-681.
  • 3Jackson C R, Apel J R, et al.. Synthetic Aperture Radar Marine User's Manual[M]. Washington DC, 2004: 139-169.
  • 4Zhang M, Zhao Y W, Chen H, et al.. SAR Imaging simulation for composite model of ship on dynamic ocean scene[J]. Progress in Electromagnetics Research, 2011, 113: 395-412.
  • 5Goldsteia R M and Werner C L. Radar interferogram filtering for geophysical applications[J]. Geophysical Research Letters, 1998, 25(21): 4035-4038.
  • 6Cai Y N and Chong J S. Parameter assessment for texture feature quality evaluation in SAR ocean image[C]. 2nd Asian-Pacific Conference on Synthetic Aperture Radar, Xi'an, China, 2009: 852-855.
  • 7蒋永馨,王孝通,徐晓刚,黄华.海洋合成孔径雷达图像斑点噪声的滤除[J].高技术通讯,2009,19(6):586-590. 被引量:3
  • 8白皓,王小青,陈永强.一种基于曲波域的SAR图像特征增强新方法[J].中国科学院研究生院学报,2011,28(2):228-234. 被引量:1
  • 9赵凤军,刘凡,邓云凯,禹卫东,冯锦.一种基于灰度互相关法的扫描模式下的风场反演算法[J].电子与信息学报,2011,33(7):1667-1670. 被引量:3

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