基于人类视觉感知和多曝光融合的滑坡易发区监测系统图像增强技术

S. Keerativittayanun, Kittikom Sangrit, Pattanun Srisukanun, Pitisit Dillon, Jessada Karnjana
{"title":"基于人类视觉感知和多曝光融合的滑坡易发区监测系统图像增强技术","authors":"S. Keerativittayanun, Kittikom Sangrit, Pattanun Srisukanun, Pitisit Dillon, Jessada Karnjana","doi":"10.23919/SICE.2019.8859933","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new technique for enhancing image quality and generating a representative image from a set of input images taken from a landslide-prone area monitoring camera at different times of a day. Thus, less-visible areas in the input images are different from one another. First, the proposed technique enhances each input image by deploying a scaling function based on human visual perception. Then, it fuses all input images and all enhanced images by using Gaussian and Laplacian pyramid-based blending. Experimental results show that the resulting image can improve the visibility of some shadowed details and that the objective evaluation results regarding image enhancement metric, universal image quality index, and perceptual similarity index are satisfying.","PeriodicalId":147772,"journal":{"name":"2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image Enhancement Technique Based on Human Visual Perception and Multi-exposure Fusion for a Landslide-prone Area Monitoring System\",\"authors\":\"S. Keerativittayanun, Kittikom Sangrit, Pattanun Srisukanun, Pitisit Dillon, Jessada Karnjana\",\"doi\":\"10.23919/SICE.2019.8859933\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new technique for enhancing image quality and generating a representative image from a set of input images taken from a landslide-prone area monitoring camera at different times of a day. Thus, less-visible areas in the input images are different from one another. First, the proposed technique enhances each input image by deploying a scaling function based on human visual perception. Then, it fuses all input images and all enhanced images by using Gaussian and Laplacian pyramid-based blending. Experimental results show that the resulting image can improve the visibility of some shadowed details and that the objective evaluation results regarding image enhancement metric, universal image quality index, and perceptual similarity index are satisfying.\",\"PeriodicalId\":147772,\"journal\":{\"name\":\"2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/SICE.2019.8859933\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/SICE.2019.8859933","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在本文中,我们提出了一种新的技术来提高图像质量,并从一天中不同时间从滑坡易发地区的监控摄像机拍摄的一组输入图像中生成具有代表性的图像。因此,输入图像中较不可见的区域彼此不同。首先,该技术通过部署基于人类视觉感知的缩放函数来增强每个输入图像。然后,采用基于高斯和拉普拉斯金字塔的混合方法对所有输入图像和所有增强图像进行融合。实验结果表明,所得到的图像可以提高部分阴影细节的可见性,并且在图像增强指标、通用图像质量指标和感知相似度指标方面的客观评价结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image Enhancement Technique Based on Human Visual Perception and Multi-exposure Fusion for a Landslide-prone Area Monitoring System
In this paper, we propose a new technique for enhancing image quality and generating a representative image from a set of input images taken from a landslide-prone area monitoring camera at different times of a day. Thus, less-visible areas in the input images are different from one another. First, the proposed technique enhances each input image by deploying a scaling function based on human visual perception. Then, it fuses all input images and all enhanced images by using Gaussian and Laplacian pyramid-based blending. Experimental results show that the resulting image can improve the visibility of some shadowed details and that the objective evaluation results regarding image enhancement metric, universal image quality index, and perceptual similarity index are satisfying.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信