利用反去马赛克减少色彩伪影

J. S. J. Li, S. Randhawa
{"title":"利用反去马赛克减少色彩伪影","authors":"J. S. J. Li, S. Randhawa","doi":"10.1109/DICTA.2010.27","DOIUrl":null,"url":null,"abstract":"Most digital cameras use a single image sensor to capture colour images. As a result, only one colour at each pixel location is acquired. Demosaicking is a technique to estimate all the other missing colour pixel information in order to produce a full colour image, while inverse demosaicking refers to the recovery of the single image sensor values from the full colour image. Early digital cameras using primitive demosaicking algorithms to produce a full colour image have resulted in inferior quality images with colour artifacts. Generally, the removal of those artifacts is not achievable by the application of direct filtering. If we can recover the actual image sensor values from a full colour image and re-demosaic it again using state-of-the-art recently developed demosaicking algorithms, a better image can be produced without filtering. In this paper, a novel technique using wavelet transform is proposed to inverse demosaic a full colour image in order to recover the actual sensor values. It is then re-demosaicked using an advanced recently developed demosaicking method to reproduce an output image with minimal colour artifacts.","PeriodicalId":246460,"journal":{"name":"2010 International Conference on Digital Image Computing: Techniques and Applications","volume":"906 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Reduction of Colour Artifacts Using Inverse Demosaicking\",\"authors\":\"J. S. J. Li, S. Randhawa\",\"doi\":\"10.1109/DICTA.2010.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most digital cameras use a single image sensor to capture colour images. As a result, only one colour at each pixel location is acquired. Demosaicking is a technique to estimate all the other missing colour pixel information in order to produce a full colour image, while inverse demosaicking refers to the recovery of the single image sensor values from the full colour image. Early digital cameras using primitive demosaicking algorithms to produce a full colour image have resulted in inferior quality images with colour artifacts. Generally, the removal of those artifacts is not achievable by the application of direct filtering. If we can recover the actual image sensor values from a full colour image and re-demosaic it again using state-of-the-art recently developed demosaicking algorithms, a better image can be produced without filtering. In this paper, a novel technique using wavelet transform is proposed to inverse demosaic a full colour image in order to recover the actual sensor values. It is then re-demosaicked using an advanced recently developed demosaicking method to reproduce an output image with minimal colour artifacts.\",\"PeriodicalId\":246460,\"journal\":{\"name\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"volume\":\"906 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Digital Image Computing: Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2010.27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2010.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

大多数数码相机使用单个图像传感器来捕捉彩色图像。因此,在每个像素位置只获得一种颜色。去马赛克是一种估计所有其他缺失的颜色像素信息以产生全彩色图像的技术,而逆去马赛克是指从全彩色图像中恢复单个图像传感器值。早期的数码相机使用原始的去马赛克算法来产生全彩色图像,导致图像质量较差,带有彩色伪影。一般来说,通过应用直接过滤是无法去除这些伪影的。如果我们能够从全彩图像中恢复实际的图像传感器值,并使用最新开发的最先进的去马赛克算法再次对其进行重新去马赛克,则可以在没有滤波的情况下产生更好的图像。本文提出了一种利用小波变换对全彩色图像进行反采样的新方法,以恢复传感器的实际值。然后使用先进的最近开发的去马赛克方法重新去马赛克,以最小的彩色伪影再现输出图像。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reduction of Colour Artifacts Using Inverse Demosaicking
Most digital cameras use a single image sensor to capture colour images. As a result, only one colour at each pixel location is acquired. Demosaicking is a technique to estimate all the other missing colour pixel information in order to produce a full colour image, while inverse demosaicking refers to the recovery of the single image sensor values from the full colour image. Early digital cameras using primitive demosaicking algorithms to produce a full colour image have resulted in inferior quality images with colour artifacts. Generally, the removal of those artifacts is not achievable by the application of direct filtering. If we can recover the actual image sensor values from a full colour image and re-demosaic it again using state-of-the-art recently developed demosaicking algorithms, a better image can be produced without filtering. In this paper, a novel technique using wavelet transform is proposed to inverse demosaic a full colour image in order to recover the actual sensor values. It is then re-demosaicked using an advanced recently developed demosaicking method to reproduce an output image with minimal colour artifacts.
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:481959085
Book学术官方微信