文章基本信息

标题：Image Stitching with Robust Principal Component Analysis
本地全文：下载
作者：Wei Tao ; Zhang Yongxin ; Yuan Yating 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：12
页码：251
出版社：SERSC
摘要：An image stitchingalgorithm based on the robustness of principal component analysis (RPCA) isproposed in an effort to suppress the influence of noise in the image stitching quality. This algorithmrepresents high dimensional feature data by utilizing a lower dimensional linear subspace, and converts the image stitchingproblem into a principalcomponent matrix matching problem.Through the use of alow rank matrix, the extraction of salient image characteristics is recovered and the noise interference is reduced during the enhancement process. Together, with the advantages of the RPCA algorithm, thealgorithm improves the PSNR of the image while maintaining its strong matching ability. Experimental results show that the proposed scheme is able to significantly inhibit the noiseand improve the stitchingquality in comparison to the other existing stitchingmethods.
关键词：i;mage ;stitching; ;r;obust principal component analysis; ;f;eature points ;matching; ;s;aliency