Variable subspace model for hyperspectral anomaly detection

Author:

Lo Edisanter

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition

Reference24 articles.

1. Schaum AP (2007) Hyperspectral anomaly detection beyond RX. In: Proceeding of 13th SPIE conference on algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery, vol 6565, 656502

2. Stein DWJ, Beaven SG, Hoff LE, Winter EM, Schaum AP, Stocker AD (2002) Anomaly detection from hyperspectral imagery. IEEE Signal Process Mag 19:58–69

3. Schaum AP (2006) Hyperspectral detection algorithms: from old ideas to operational concepts to next generation. In: Proceeding of 12th SPIE conference on algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery, vol 6233, 623305

4. Horwitz HM, Nalepka RF, Hyde PD, Morgenstern JP (1971) Estimating the proportions of objects within a single resolution element of a multispectral sensor. In: Proceeding of 7th international symposium on remote sensing of environment (Ann Arbor, MI), pp 1307–1320

5. Stocker A, Schaum A (1997) Application of stochastic mixing models to hyperspectral detection problems. In: Proceeding of 3rd SPIE conference on algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery, vol 3071, pp 47–60

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Partitioned correlation model for hyperspectral anomaly detection;Optical Engineering;2015-12-29

2. Hyperspectral anomaly detection based on constrained eigenvalue–eigenvector model;Pattern Analysis and Applications;2015-09-22

3. Hyperspectral anomaly detection based on maximum likelihood method;SPIE Proceedings;2015-07-29

4. Progressive Band Processing of Anomaly Detection in Hyperspectral Imagery;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2015-07

5. Hyperspectral anomaly detection based on uniformly partitioned pixel;Pattern Analysis and Applications;2014-08-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3