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}
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.