Research on Compressed Multiscale Retinex Image Enhancement Algorithms

LIU Mingzhu; SU Taoyu; WANG Yining

doi:10.15938/j.jhust.2020.05.013

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Research on Compressed Multiscale Retinex Image Enhancement Algorithms

更新时间：2026-08-31

- Research on Compressed Multiscale Retinex Image Enhancement Algorithms
- Vol. 25, Issue 5, Pages: 93-99(2020)
- 作者机构：
  
  哈尔滨理工大学测控技术与通信工程学院,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2020.05.013
  CLC： TN91173
- Published：2020
- 稿件说明：
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LIU Mingzhu, SU Taoyu, WANG Yining. Research on Compressed Multiscale Retinex Image Enhancement Algorithms[J]. 2020, 25(5): 93-99.
DOI：

LIU Mingzhu, SU Taoyu, WANG Yining. Research on Compressed Multiscale Retinex Image Enhancement Algorithms[J]. 2020, 25(5): 93-99. DOI： 10.15938/j.jhust.2020.05.013.

摘要

摘要: 在低照度条件下对人脸图像进行光照补偿和利用带色彩恢复的Retinex算法是传统图像增强算法中较为有效的一种。针对传统的MSRCR算法在处理图像后仍会产生清晰度低、细节模糊和色彩不饱满等问题。因此本文提出带色彩恢复的压扩多尺度Retinex算法—CMSRCR，利用多彩色通道变曲变换函数及因子修正法，对低照度人脸图像进行图像增强和色彩恢复。结果表明，CMSRCR算法能够使低照度图像在清晰度、细节和颜色恢复等方面都有明显的改善。

Abstract

Abstract: The Retinex algorithm for face image illuminationcompensation and color restoration is an effective one in the traditional imageenhancement algorithm under the condition of low illumination The traditionalMSRCR algorithm can still produce some problems such as low sharpness

blurreddetails and incomplete color after image processing Therefore

this paperproposes a compression expansion multiscale Retinex algorithm with colorrecoveryCMSRCR

which uses multicolor channel bending transformation functionand factor correction method to enhance and restore lowillumination face imagesThe results show that the CMSRCR algorithm can improve the sharpness

detailand color restoration of low illumination image

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