Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (10): 3046-3052.DOI: 10.11772/j.issn.1001-9081.2019040642

• Virtual reality and multimedia computing • Previous Articles     Next Articles

Low-illumination image enhancement algorithm based on multi-scale gradient domain guided filtering

LI Hong, WANG Ruiyao, GENG Zexun, HU Haifeng   

  1. School of Information Engineering, Pingdingshan University, Pingdingshan Henan 467000, China
  • Received:2019-04-16 Revised:2019-06-23 Online:2019-10-10 Published:2019-08-21
  • Supported by:
    This work is partially supported by the Pingdingshan Science and Technology Project (201700812), the Youth Fund of Pingdingshan University (PXY-QNJJ-2019010).

基于多尺度梯度域引导滤波的低照度图像增强算法

李红, 王瑞尧, 耿则勋, 胡海峰   

  1. 平顶山学院 信息工程学院, 河南 平顶山 467000
  • 通讯作者: 李红
  • 作者简介:李红(1981-),女,重庆人,讲师,硕士,主要研究方向:图像处理、嵌入式系统;王瑞尧(1989-),男,河南平顶山人,助教,硕士,主要研究方向:图像处理、嵌入式系统;耿则勋(1958-),男,河南孟州人,教授,博士生导师,博士,主要研究方向:图像处理、计算机视觉;胡海峰(1982-),男,河南平顶山人,副教授,硕士,主要研究方向:传感器网络。
  • 基金资助:
    平顶山市科技攻关项目(201700812);平顶山学院青年基金资助项目(PXY-QNJJ-2019010)。

Abstract: An improved low-illumination image enhancement algorithm was proposed to solve the problems that the overall intensity of low-illumination color image is low, the color in the enhanced image is easy to be distorted, and some enhanced image details are drowned in the pixels with low gray value. Firstly, an image to be processed was converted to the Hue Saturation Intensity (HSI) color space, and the nonlinear global intensity correction was carried out for the intensity component. Then, an intensity enhancement model based on multi-scale guided gradient domain filtering was put forward to enhance the corrected intensity component, and the intensity correction was further performed to avoid color distortion. Finally, the image was converted back into Red Green Blue (RGB) color space. Experimental results show that the enhanced images have the intensity increased by more than 90.0% on average, and the sharpness increased by more than 123.8% on average, which are mainly due to the better intensity smoothing and enhancement ability of multi-scale gradient domain guided filtering. At the same time, due to the reduction of color distortion, the detail performance of enhanced images increases by more than 18.2% on average. The proposed low-illumination image enhancement algorithm is suitable for enhancing color images under night and other weak light source conditions, because of using intensity enhancement model based on multi-scale gradient domain guided filtering and histogram adaptive intensity correction algorithm.

Key words: low-illumination image, image enhancement, gradient domain guided filtering, Retinex theory, HSI color space

摘要: 针对低照度彩色图像整体亮度较低,增强图像中颜色易失真,部分图像细节淹没在较低灰度值像素中等问题,提出一种改进的低照度图像增强算法。首先,把待处理图像转换到色调、饱和度、亮度(HSI)颜色空间,对亮度分量进行非线性全局亮度校正;然后,提出多尺度梯度域引导滤波的亮度增强模型,利用该模型对校正后的亮度分量进行增强,接着对增强后的亮度分量进一步实施避免颜色失真的亮度校正;最后,将图像再转换回红绿蓝(RGB)颜色空间。实验结果表明,增强后的图像亮度平均提高90.0%以上,清晰度平均提高123.8%以上,这主要得益于多尺度梯度域引导滤波具有更好的亮度平滑和增强能力;同时由于减小了颜色失真,使增强图像的细节表现能力平均提高18.2%以上;由于采用了多尺度梯度域引导滤波的亮度增强模型与直方图自适应的亮度校正算法,使提出的低照度图像增强算法适宜应用于夜间等弱光源条件下的彩色图像增强。

关键词: 低照度图像, 图像增强, 梯度域引导滤波, Retinex理论, HSI颜色空间

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