Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (24): 190-195.DOI: 10.3778/j.issn.1002-8331.1809-0299

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Adaptive Color Preserving Algorithm for Low Illumination Image Enhancement

ZHU Deli, YANG Degang, WAN Hui, YANG Yunong   

  1. 1.College of Computer and Information Science, Chongqing Normal University, Chongqing 401331, China
    2.Office of Academic Research, Chongqing Normal University, Chongqing 401331, China
    3.Office of Educational Administration, Chongqing Normal University, Chongqing 401331, China
  • Online:2019-12-15 Published:2019-12-11



  1. 1.重庆师范大学 计算机与信息科学学院,重庆 401331
    2.重庆师范大学 科研处,重庆 401331
    3.重庆师范大学 教务处,重庆 401331

Abstract: In the field of video surveillance and scene restoration, low illumination image has many noise points, low brightness and poor visual effect. However, the existing image processing technology is prone to color distortion and serious halo color block. In order to solve this problem, according to Weber-Fisher’s law, the pixels of the image are transformed into logarithmic space, and the preliminary enhanced image corresponding to the characteristics of the visual system is obtained adaptively. The average Gauss filtering results of the R channel of the image are calculated respectively to obtain the estimation of incident light. The difference between the pixel value of the preliminary enhanced image and the estimated incident light is taken as the result image of the multi-scale retinal algorithm. The RGB channel of the result image is mapped to the range of 0-255 according to the color proportion of the primary enhanced image. The final output image is obtained by fusing the three channels. Compared with MSR, MSRCR and MSRCP, the proposed algorithm can acquire the enhanced image adaptively according to the scene of different low illumination images, and is superior to MSR, MSRCR and MSRCP in contrast and chroma preservation. Experiments show that the algorithm has a good effect in low illumination image enhancement, restoration and chromaticity preservation, and has a good value for application in enhancing the effectiveness of video surveillance.

Key words: low illumination image, image restoration, image enhancement, Multi-Scale Retinex with Color Restoration(MSRCR), MSR with Chromaticity Preservation(MSRCP)

摘要: 视频监控、场景恢复等领域中低照度图像噪点多,亮度低,可视效果差,而现有的图像处理技术容易出现颜色失真、光晕色块严重。为解决这一问题,根据韦伯-费希纳定律,把图像的像素点转换到对数空间,自适应获得符合视觉系统特点的预增强图像;再根据多尺度视网膜算法,分别计算与增强图像的R通道在三个尺度上的平均高斯滤波结果,获得入射光估计,把对数域的自适应增强图像像素值与入射光估计的差值作为多尺度视网膜算法的结果图像。进一步处理结果图像,将其RGB通道按照预增强图像中的颜色比例关系映射到0~255的范围;最后融合三个通道获得最终图像输出。通过图像质量的评价对比,该算法对不同低照度场景图像的增强结果,在对比度、色度保持等方面优于MSR、MSRCR和MSRCP算法。实验证明该算法在低照度图像的恢复和色度保留等方面有较好的效果,在增强视频监控的有效性等方面有较好的应用价值。

关键词: 低照度图像, 图像恢复, 图像增强, 带色彩恢复的多尺度Retinex算法(MSRCR), MSRCP算法