一种基于HSV空间的微光图像增强方法

Libing Zhou, Xiaojing Chen, Baisong Ye, Xueli Jiang, Sheng Zou, Liang Ji, Zhengqian Yu, Jianjian Wei, Yexin Zhao, Tianyu Wang
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引用次数: 0

摘要

摘要为了提高低照度图像的视觉性能,对大量低照度图像进行了分析。在此基础上,提出了一种基于HSV空间和半隐式ROF模型的弱光图像增强方法。首先,将低照度图像分解到HSV空间进行饱和度去噪和亮度增强;然后,应用贝叶斯规则对饱和度和值进行融合。将HSV空间中的三个分量转换为RGB空间,得到粗糙增强图像。最后,引入半隐式ROF模型对全局噪声进行去噪,得到增强图像。这种综合的方法可以提高低照度图像的清晰度。实验结果表明,该算法的PSNR得分分别为26.48、6.29、0.8947和28.4124,在比较算法中PSNR得分最高。在低光图像数据集上的实验也表明,该方法可以有效地提高低光图像的可见性,为低光图像增强提供了一种简单有效的方法。关键词:图像增强,深度学习,hsv颜色空间,贝叶斯规则,高斯噪声,结构相似性,峰值信噪比披露声明,作者未报告潜在的利益冲突。周立冰,硕士,毕业于中国合肥工业大学。现就职于天地(常州)自动化有限公司。主要研究方向为矿山机电系统智能化、智能检测与控制。陈晓晶,副研究员。现就职于天地(常州)自动化有限公司。目前主要研究方向为煤矿工业控制、物联网与智能技术。叶白松,2013年毕业于中国科学技术大学,获博士学位。现就职于天地(常州)自动化有限公司。主要研究方向为煤矿光电探测系统及智能应用技术。姜雪莉,博士,2021年毕业于中国科学技术大学合肥分校。现就职于天地(常州)自动化有限公司。他目前的研究重点是运动控制。余胜正谦,2020年毕业于美国新泽西州史蒂文斯理工学院,获硕士学位。现就职于天地(常州)自动化有限公司。他目前的研究兴趣包括定位、目标检测和障碍物感知。梁继健,魏建建,2022年毕业于中国西安科技大学,获硕士学位。现就职于天地(常州)自动化有限公司。他目前的研究兴趣包括定位,目标检测。邹正谦,2019年毕业于中国衡阳华南大学,获硕士学位。现就职于天地(常州)自动化有限公司。主要研究方向为煤矿视觉图像处理。纪卫亮,2019年毕业于中国矿业大学,获硕士学位。现就职于天地(常州)自动化有限公司。他目前的研究兴趣包括矿山智能、人工智能和深度学习。赵业新,2020年毕业于中国西安长安大学,获硕士学位。现就职于天地(常州)自动化有限公司。他目前的研究兴趣包括自动驾驶的决策控制。王天宇,2019年毕业于中国江苏大学镇江分校,获硕士学位。现就职于天地(常州)自动化有限公司。他目前的研究方向包括控制、自动化和结构设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A low-light image enhancement method based on HSV space
ABSTRACTTo enhance the visual performance of low-illumination images, many low-illumination images are analyzed. Based on this, a low-light image enhancement method based on HSV space and semi-implicit ROF model is proposed. First, the low-illumination image is decomposed into HSV space for saturation denoising and brightness enhancement. Then, the Bayesian rules are applied to fuse the saturation and value. The three components in HSV space are converted to the RGB space and obtain a rough enhanced image. Finally, the semi-implicit ROF model is introduced to denoise the global noise and obtain the enhanced image. Such a comprehensive method can improve the low illumination image more clearly. The experimental results show that the algorithm has a PSNR score of 26.48, 6.29, 0.8947, and 28.4124, and the PSNR score is the highest in the comparison algorithm. The experiments on the Low-Light image data set also show that the proposed method can effectively improve the visibility of low-light images, and can provide a simple and effective method for low-light image enhancement.KEYWORDS: Image enhancementDeep learningHSV color spaceBayesian ruleROFGaussian noiseStructure SimilarityPeak Signal Noise Ratio Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsLibing ZhouLibing Zhou received master's degree from Hefei University of Technology, Hefei, China. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include mine electromechanical system intelligent, intelligent detection and control.Xiaojing ChenXiaojing Chen is an associate research fellow. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include coal mine industrial control, Internet of Things and intelligent technology.Baisong YeBaisong Ye received PhD degree from the University of Science and Technology of China, Hefei, China, in 2013. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests includecoal mine photoelectric detection system and intelligent application technology.Xueli JiangXueli Jiang received PhD degreefrom the University of Science and Technology of China, Hefei,China, in 2021. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research focuses on motor control.Sheng ZouZhengqian Yu received master's degree from the Stevens Institute of Technology, New Jersey,USA, in 2020. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include positioning, object detection and obstacle perception.Liang JiJianjian Wei received master's degree from Xi'an University of Science and Technology, Xi'an,China, in 2022. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include positioning, object detection.Zhengqian YuSheng Zou received master's degree from University of South China, Hengyang,China, in 2019. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include visual image processing in coal mine.Jianjian WeiLiang Ji received master's degree from China University of Mining and Technology, Xuzhou,China, in 2019. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include mine intelligence, artificial intelligence and deep learning.Yexin ZhaoYexin Zhao received master's degree from Chang'an University, Xi'an, China, in 2020. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include decision control for autonomous driving.Tianyu WangTianyu Wang received master's degree from Jiangsu University, Zhenjiang, China, in 2019. Now he works at Tiandi(Changzhou) Automation Co., Ltd. His current research interests include control, automation and structural design.
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