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潘海明, 田润, 刘春晓, 龚辰. 基于偏色校正和信息损失约束的沙尘暴降质图像增强算法[J]. 计算机辅助设计与图形学学报, 2018, 30(6): 992-999. DOI: 10.3724/SP.J.1089.2018.16711
引用本文: 潘海明, 田润, 刘春晓, 龚辰. 基于偏色校正和信息损失约束的沙尘暴降质图像增强算法[J]. 计算机辅助设计与图形学学报, 2018, 30(6): 992-999. DOI: 10.3724/SP.J.1089.2018.16711
Pan Haiming, Tian Run, Liu Chunxiao, Gong Chen. A Sand-Dust Degraded Image Enhancement Algorithm Based on Color Correction and Information Loss Constraints[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(6): 992-999. DOI: 10.3724/SP.J.1089.2018.16711
Citation: Pan Haiming, Tian Run, Liu Chunxiao, Gong Chen. A Sand-Dust Degraded Image Enhancement Algorithm Based on Color Correction and Information Loss Constraints[J]. Journal of Computer-Aided Design & Computer Graphics, 2018, 30(6): 992-999. DOI: 10.3724/SP.J.1089.2018.16711

基于偏色校正和信息损失约束的沙尘暴降质图像增强算法

A Sand-Dust Degraded Image Enhancement Algorithm Based on Color Correction and Information Loss Constraints

  • 摘要: 为了解决沙尘暴环境下拍摄的图像中存在的颜色偏移、对比度低等降质问题,提出基于偏色校正和信息损失约束的沙尘降质图像增强算法,主要包含偏色校正和对比度增强2个模块,在偏色校正模块中,通过分析沙尘降质图像的RGB 3个通道直方图分布特点,提出一个改进的基于高斯模型的偏色校正算法;在对比度增强模块中,通过结合基于暗通道先验和信息损失约束算法,提出一种基于大气散射模型的对比度增强算法.为了验证算法的有效性,通过与4种已有算法的大量实验结果对比发现:文中算法不但能够很好地增强不同种类的沙尘降质图像的对比度,而且可以有效地避免图像偏色现象,并且保持良好的色彩保真度和合适的亮度.

     

    Abstract: The outdoor images captured in sand storm environment have serious color cast, low contrast and low quality problem. In order to solve these problems, a sand-dust degraded image enhancement method based on color correction and information loss constraints is proposed, which mainly contains two modules, i.e. color correction and contrast enhancement. In the color correction module, by analyzing the RGB histograms distribution characteristics of the sand-dust degraded images, a Gaussian model based improved color correction algorithm is designed to adjust the color of the image. In the contrast enhancement module, by combining the information loss constraints method with the dark channel prior based method, an atmospheric scattering model based contrast enhancement algorithm is put forward to enhance the sand-dust degraded images. In order to verify the effectiveness of our algorithm, lots of experiments are carried out and compared with 4 existing methods. It is easy to see that our method not only effectively strengthens the contrast of different kinds of sand-dust degraded images, but also avoids the color casting phenomena and takes on good color fidelity and proper brightness.

     

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