吉林大学学报(理学版) ›› 2023, Vol. 61 ›› Issue (3): 601-611.

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基于模拟曝光融合的非均匀光照图像增强

王若状, 臧景峰, 张朋朋   

  1. 长春理工大学 电子信息工程学院, 长春 130022
  • 收稿日期:2022-03-03 出版日期:2023-05-26 发布日期:2023-05-26
  • 通讯作者: 臧景峰 E-mail:zangjingfeng@cust.edu.cn

Non-uniform Illumination Image Enhancement Based on Simulated Exposure Fusion

WANG Ruozhuang, ZANG Jingfeng, ZHANG Pengpeng   

  1. School of Electronic and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China
  • Received:2022-03-03 Online:2023-05-26 Published:2023-05-26

摘要: 针对非均匀光照图像存在的场景细节被掩盖、 图像信息获取较难的问题, 提出一种基于模拟曝光融合的非均匀光照图像增强方法. 首先, 在HSV颜色空间下使用改进的自适应伽马校正算法处理亮度分量, 将其作为中等曝光图像; 其次, 对亮度分量通过动态阈值划分过曝光像素集, 对其使用最大信息熵估计及相机响应模型合成模拟的过曝光图像; 再次, 对原图像、 中等曝光图像、 过曝光图像组成的多曝光图像序列使用改进的质量度量方法以及基于导向滤波的权重优化方法得到融合图像; 最后, 融合结果经过多尺度细节增强处理得到最终的图像增强结果. 实验结果表明, 该算法能有效改善非均匀光照图像的视觉效果, 通过主客观评价的数据对比, 表明本文算法优于同类算法.

关键词: 非均匀光照, 自适应伽马校正, 模拟曝光图像, 多曝光融合, 导向滤波

Abstract: Aiming at the problems of scene details being covered up and image information being difficult to obtain in non-uniform illumination images, we proposed a non-uniform illumination image enhancement method based on simulated exposure fusion. Firstly, an improved adaptive Gamma correction algorithm was used in HSV color space to process the brightness component  as a medium exposure image. Secondly, the over-exposure pixel set was divided by dynamic threshold for the brightness component, and the simulated over-exposure image was synthesized by using maximum information entropy estimation and camera response model. Thirdly, the improved quality measurement method and the weight optimization method based on the guided filtering were used to obtain the fused image for the multi-exposure image sequences composed of the original images, the medium-exposure images and the over-exposure images.  Finally, the fusion result was processed by multi-scale detail enhancement to obtain the final image enhancement result. The experimental results show that the proposed algorithm can effectively improve the visual effect of non-uniform illumination images. The comparison of subjective and objective evaluation data shows that the proposed algorithm is superior to similar algorithms.

Key words: non-uniform illumination, adaptive Gamma correction, simulated exposure image, multi-exposure fusion, guided filtering

中图分类号: 

  • TP391