Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (9): 189-193.DOI: 10.3778/j.issn.1002-8331.1612-0259

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Downhole image enhancement algorithm driven by human visual perception

WANG Yan, YANG Wei, WANG Yaheng   

  1. School of Electrical and Control Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China
  • Online:2018-05-01 Published:2018-05-15


王  焱,杨  威,王亚恒   

  1. 辽宁工程技术大学 电气与控制工程学院,辽宁 葫芦岛 125105

Abstract: In order to solve the traditional contrast enhancement method in the downhole image processing can not take into account the compressed dynamic range, adjust the brightness and enhance the image contrast and other issues, this paper proposes a contrast enhancement algorithm for downhole images based on human visual perceptual characteristics. Firstly, the image is divided according to the characteristic of human eye luminance masking, then, based on the non-linear luminance mapping model, different scales of different regions of the image are adjusted nonlinearly. Finally, adjust the brightness of the different regions after the combination of the new image. The experimental results show that this method can effectively enhance the contrast of low-light images and improve the visual effect of the image.

Key words: visual perception characteristics, downhole image, contrast enhancement, nonlinear mapping model

摘要: 为解决传统的对比度增强方法在对井下图像进行处理时不能兼顾压缩动态范围、调整亮度以及增强图像对比度等问题,提出一种基于人眼视觉感知特性的井下图像对比度增强算法。首先根据人眼亮度掩蔽特性对图像进行区域划分,然后基于非线性亮度映射模型,对图像的不同区域进行不同尺度的非线性调整,最后再将亮度调整后的不同区域组合成新的图像。实验结果表明,该方法能有效增强井下低照度图像的对比度,提升图像的视觉效果。

关键词: 视觉感知特性, 井下图像, 对比度增强, 非线性映射模型