A shaped collaborative representation-based detector for hyperspectral anomaly detection

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-11-02 DOI:10.1080/2150704x.2023.2275549

Maryam Imani

{"title":"A shaped collaborative representation-based detector for hyperspectral anomaly detection","authors":"Maryam Imani","doi":"10.1080/2150704x.2023.2275549","DOIUrl":null,"url":null,"abstract":"ABSTRACTA modified version of the collaborative representation-based detector (CRD) is proposed for hyperspectral anomaly detection. In contrast to the conventional CRD, which uses a rectangular dual window, the shaped CRD (SCRD) selects the most appropriate neighbours from the dual window and discards the inappropriate ones. To this end, similarity of the neighbouring pixels to the centre is computed based on the cosine distance to utilize the local information. In addition, the low/high occurrence probability of anomalies/background exhibited in the histogram of the whole image is utilized as global information to find the closest neighbours to the background. The shaped dual window is used for linear approximation of pixels through the collaborative representation. SCRD improves the anomaly detection results with respect to some related works. Experiments on two hyperspectral images show that SCRD results in more accurate detection maps with a bit higher running time compared to CRD.KEYWORDS: collaborative representationdual windowhyperspectral imageanomaly detection Disclosure statementNo potential conflict of interest was reported by the author.","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/2150704x.2023.2275549","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

ABSTRACTA modified version of the collaborative representation-based detector (CRD) is proposed for hyperspectral anomaly detection. In contrast to the conventional CRD, which uses a rectangular dual window, the shaped CRD (SCRD) selects the most appropriate neighbours from the dual window and discards the inappropriate ones. To this end, similarity of the neighbouring pixels to the centre is computed based on the cosine distance to utilize the local information. In addition, the low/high occurrence probability of anomalies/background exhibited in the histogram of the whole image is utilized as global information to find the closest neighbours to the background. The shaped dual window is used for linear approximation of pixels through the collaborative representation. SCRD improves the anomaly detection results with respect to some related works. Experiments on two hyperspectral images show that SCRD results in more accurate detection maps with a bit higher running time compared to CRD.KEYWORDS: collaborative representationdual windowhyperspectral imageanomaly detection Disclosure statementNo potential conflict of interest was reported by the author.

查看原文本刊更多论文

基于形状协同表示的高光谱异常检测

提出了一种改进的基于协同表示的高光谱异常检测方法(CRD)。与使用矩形双窗口的传统CRD相比，形状CRD (SCRD)从双窗口中选择最合适的邻居，并丢弃不合适的邻居。为此，基于余弦距离计算邻近像素与中心的相似性，以利用局部信息。此外，利用整幅图像直方图中显示的异常/背景的低/高出现概率作为全局信息，寻找与背景最近的邻居。通过协同表示，利用形状双窗口对像素进行线性逼近。SCRD改进了一些相关工作的异常检测结果。在两幅高光谱图像上的实验表明，与CRD相比，SCRD可以获得更精确的检测图，但运行时间略长。关键词:协同表示双窗超光谱图像异常检测披露声明作者未报道潜在利益冲突。

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分钟内获得全文求助全文

来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.