吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (8): 2301-2306.doi: 10.13229/j.cnki.jdxbgxb.20230235

• 计算机科学与技术 • 上一篇    下一篇

基于视觉信息补偿的光照不均图像增强方法

王欣(),党电太   

  1. 湖南工业大学 电气与信息工程学院,湖南 株洲 412000
  • 收稿日期:2023-03-17 出版日期:2024-08-01 发布日期:2024-08-30
  • 作者简介:王欣(1971-),女,教授,博士.研究方向:复杂工业过程建模与优化控制.E-mail:wangxin11223@126.com
  • 基金资助:
    湖南省自然科学基金项目(2021JJ50006);国家自然科学基金项目(62033014)

Image enhancement method of uneven illumination based on visual information compensation

Xin WANG(),Dian-tai DANG   

  1. School of Electrical and Information Engineering,Hunan University of Technology,Zhuzhou 412000,China
  • Received:2023-03-17 Online:2024-08-01 Published:2024-08-30

摘要:

针对因光照不均导致图像灰度值分布不均、噪声大、视觉传达效果差等问题,提出基于视觉信息补偿的光照不均图像增强方法。计算图像中不同目标和背景区域的像素灰度值,构建灰度衰减序列,构建衰减函数对最弱像素点周围的每一个背景点进行加权处理,采用同态滤波函数根据图像中光线的分量值变化去噪。采用视觉信息补偿法计算图中每个区域的像素值,并转换为分量值模式,按照亮度总量值和局部值进行互补增强。实验数据表明:本文方法增强效果佳,图像清晰度得到了提高,细节刻画效果好。

关键词: 视觉信息补偿, 光照不均, 图像增强, 灰度衰减函数, 亮度总量值

Abstract:

Aiming at the problems of uneven distribution of grayscale values and high noise in images caused by uneven lighting, as well as poor visual communication effect, a visual information compensation based method for enhancing images with uneven lighting is proposed. Calculate the pixel grayscale values of different targets and background regions in the image, construct a grayscale attenuation sequence, construct an attenuation function to weight each background point around the weakest pixel, and use a homomorphic filtering function to denoise based on changes in the component of light in the image. By using the visual information compensation method to calculate the pixel values of each region in the graph, and converting them into component modes, complementary enhancement is implemented based on the total brightness value and local values. The experimental data proves that the proposed method has good enhancement effect, improved image clarity, and good detail characterization effect.

Key words: visual information compensation, uneven illumination, image enhancement, gray attenuation function, total brightness value

中图分类号: 

  • TP327

图1

视觉分离前后结果"

图2

3种方法图像光照增强结果"

图3

基于像素直方图比对结果"

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