计算机科学 ›› 2019, Vol. 46 ›› Issue (8): 327-331.doi: 10.11896/j.issn.1002-137X.2019.08.054

• 图形图像与模式识别 • 上一篇    下一篇

Retinex自适应反射分量估计和对数图像处理减法后处理的

潘卫琼, 涂娟娟, 干宗良, 刘峰   

  1. (南京邮电大学江苏省图像处理与图像通信重点实验室 南京210003)
  • 收稿日期:2018-07-31 出版日期:2019-08-15 发布日期:2019-08-15
  • 通讯作者: 干宗良(1979-),男,博士,副教授,主要研究方向为分布式视频编码和图像视频信号处理等,E-mail:ganzl@njupt.edu.cn
  • 作者简介:潘卫琼(1992-),女,硕士生,主要研究方向为图像处理和计算机视觉;涂娟娟(1994-),女,硕士生,主要研究方向为图像处理与计算机视觉;刘峰(1964-),男,博士,教授,主要研究方向为图像处理与网络视频通信、高速DSP与嵌入式应用系统设计等
  • 基金资助:
    国家自然科学基金(60802021,61172118,61271240,6147120),江苏省高校自然科学重点研究项目(13KJA510004),江苏省自然科学基金青年基金(BK20130867),江苏省高校自然科学研究项目(12KJB510019)

Low Light Images Enhancement Based on Retinex Adaptive Reflectance Estimation and LIPS Post-processing

PAN Wei-qiong, TU Juan-juan, GAN Zong-liang, LIU Feng   

  1. (Jiangsu Province Key Lab on Image Processing and Image Communication,Nanjing University of Posts and Telecommunications,Nanjing 210003,China)
  • Received:2018-07-31 Online:2019-08-15 Published:2019-08-15

摘要: 在夜间采集到的图像由于受强灯光的影响,对比度较大,白天采集到的背光图像也是如此。对比度增强算法是常用的获得良好对比度图像的方法,但是这往往会造成亮区域过度增强的现象。为了解决对比度较大的这部分图像过度增强的问题,提出了一种基于Retinex自适应反射分量估计和对数图像处理减法后处理的低照度图像增强算法,该算法分为两部分:反射分量估计,基于对数图像处理减法(LIPS)模型的对比度增强。首先,用自适应双边滤波器代替传统的高斯滤波器来获得更精准的照明层。然后,根据最小可觉差(JND)阈值得到一个自适应因子来为对数域的照明分量加权,从而估计出图像的反射分量。这种方法可以有效防止高亮度区域的过度增强。最后,将基于标准偏差最大化的LIPS方法作用在反射层以增强图像的对比度,其中LIPS的参数范围由反射图像的累积分布函数(CDF)来确定。实验结果表明,文中所提算法在主观评价以及客观评价方面都优于其他对比算法。

关键词: 标准偏差最大化, 对数图像处理减法(LIPS), 反射分量估计, 最小可觉差

Abstract: Due to the influence of strong light,the images acquired at night have high contrast,the same situation also appears in backlit images collected in the daytime.Contrast enhancement method is usually applied to the images for obtaining images with favorable contrast.Whereas,over-enhancement commonly occurs in bright regions.Accordingly,in order to solve the problem of over-enhancement for high contrast images,a Retinex based low light image enhancement algorithm through adaptive reflection component estimation and logarithmic image processing subtraction post-proces-sing was proposed.The algorithm mainly includes into two parts:reflection component estimation and logarithmic image processing subtraction (LIPS) enhancement.First,adaptive parameter bilateral filters are used to get more accu-rate illumination layer data,instead of Gaussian filter.Moreover,the weighting estimation method is used to calculate the adaptive parameter to adjust the removal of the illumination and obtain the reflectance by just-noticeable-distortion (JND)factor.In this way,it can effectively prevent the over-enhancement in high-brightness regions.Then,the LIPS method based on maximum standard deviation of the histogram is applied to enhance reflectance component part,where the interval of the parameter is according to the cumulative distribution function (CDF).Experimental results demonstrate that the proposed method outperforms other competitive methods in terms of subjective and objective assessment

Key words: Just-noticeable-distortion, Logarithmic image processing subtraction, Maximum standard deviation, Reflectance estimation

中图分类号: 

  • TP391.41
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