CNN-SICE Learner Based Image Contrast Enhancement

Pooja Patel
{"title":"CNN-SICE Learner Based Image Contrast Enhancement","authors":"Pooja Patel","doi":"10.30954/2322-0465.1.2020.6","DOIUrl":null,"url":null,"abstract":"Producing the natural scene with good contrast, vivid color and rich details is an essential goal of digital photography. The acquired images, however, are often under-exposed or over-exposed because of poor lighting conditions and the limited dynamic range of imaging device. Contrast enhancement is thus an important step to improve the quality of recorded images and make the image details more visible. Many research work have been done for image enhancement. In this paper, different techniques and algorithms using machine learning approach are studied and Block based CNN Learner is designed for contrast enhancement.","PeriodicalId":7884,"journal":{"name":"Andalasian International Journal of Applied Science, Engineering and Technology","volume":"11 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Andalasian International Journal of Applied Science, Engineering and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30954/2322-0465.1.2020.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Producing the natural scene with good contrast, vivid color and rich details is an essential goal of digital photography. The acquired images, however, are often under-exposed or over-exposed because of poor lighting conditions and the limited dynamic range of imaging device. Contrast enhancement is thus an important step to improve the quality of recorded images and make the image details more visible. Many research work have been done for image enhancement. In this paper, different techniques and algorithms using machine learning approach are studied and Block based CNN Learner is designed for contrast enhancement.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于CNN-SICE学习器的图像对比度增强
产生具有良好的对比度,生动的色彩和丰富的细节的自然场景是数码摄影的基本目标。然而,由于光照条件差和成像设备的动态范围有限,所获得的图像往往曝光不足或曝光过度。因此,对比度增强是提高记录图像质量和使图像细节更清晰的重要步骤。在图像增强方面已经做了很多研究工作。本文研究了使用机器学习方法的不同技术和算法,并设计了基于块的CNN学习者用于对比度增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Determination of Resultant Forces for 2D Hyperstatic Frames using Android-Based Frame Design Application and Finite Element Analysis Enhancing Current Density and Specific Capacitance of Nata de Coco, TEMPO, and MXene Composites through Boiling Time Variations Integration of Photovoltaic Distributed Generation in Grid Distribution Network: A Literature Review Overcurrent and Directional Overcurrent Protection for Microgrid Study of Laccase Activity as a Biosensor for Peatland Degradation in Oil Palm Plantations in Pesisir Selatan of West Sumatra
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1