Low illumination color image enhancement based on dynamic bistable stochastic resonance

Wen GAO; Hai-feng XIAO

doi:10.37188/CJLCD.2020-0283

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Low illumination color image enhancement based on dynamic bistable stochastic resonance

Image Processing | 更新时间：2021-05-28

- Low illumination color image enhancement based on dynamic bistable stochastic resonance
- Chinese Journal of Liquid Crystals and Displays Vol. 36, Issue 6, Pages: 861-868(2021)
- 作者机构：
  
  西安航空学院电子工程学院, 陕西西安 710000
- 作者简介：
- 基金信息：
  
  Natural Science Basic Research Plan of Shaanxi Province(2020JM-632);Key Research and Development Projects of Shaanxi Province(2019GY-112)
- DOI：10.37188/CJLCD.2020-0283
  CLC： TP394.1
- Received：19 October 2020，
  
  Revised：25 November 2020，
  
  Published：2021-06
- 稿件说明：
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Wen GAO, Hai-feng XIAO. Low illumination color image enhancement based on dynamic bistable stochastic resonance[J]. Chinese journal of liquid crystals and displays, 2021, 36(6): 861-868.
DOI：

Wen GAO, Hai-feng XIAO. Low illumination color image enhancement based on dynamic bistable stochastic resonance[J]. Chinese journal of liquid crystals and displays, 2021, 36(6): 861-868. DOI： 10.37188/CJLCD.2020-0283.

摘要

针对非均匀低照度图像增强问题，提出了一种动态双稳随机共振算法。该算法基于双稳态随机共振模型，将图像中的噪声能量转移到低照度区域，能有效对低照度图像进行亮度增强。在研究过程中设定了低照度像素的迭代阈值，避免了高亮度区域的过度增强，可保证图像具有较好的视觉感受。研究采用感知质量评估（PQA）和亮度阶误差（LOE）作为图像质量的评价指标，通过对比实验发现，所设计算法的PQA值最接近10，增强图像的质量最好，同时LOE值在67~204之间，图像自然性保存最优。

Abstract

A dynamic bistable stochastic resonance algorithm is proposed to solve the problem of non-uniform low illumination image enhancement. Based on the bistable stochastic resonance model

the noise energy in the image is transferred to the low illumination area

which can effectively enhance the brightness of the low illumination image. In the research process

the iterative threshold of low-illumination pixel is set to avoid the excessive enhancement in high-luminance areas

which can ensure the image has better visual perception. Perceived Quality Assessment (PQA) and Luminance Order Error(LOE) are used as the evaluation index of image quality. Through comparative experiments

it is found that the PQA value of the designed algorithm is closest to 10

which enhances the image quality best

while the LOE value is between 67 and 204

and the image nature is the best.

关键词

Keywords

references

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