Adjusted Spectral Matched Filter for Target Detection in Hyperspectral Imagery

Remote Sensing

Lianru Gao²  Bin Yang²  Qian Du³  Bing Zhang²  George P. Petropoulos¹ 

[1] Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;;Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; E-Mails:;Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, USA; E-Mail:

关键词: hyperspectral imagery;    adjusted spectral matched filter;    constrained energy minimization (CEM);    Reed-Xiaoli detector (RXD);    receiver operating characteristics (ROC);   

DOI  :  10.3390/rs70606611

来源: mdpi

【 摘 要 】

Supervised target detection and anomaly detection are widely used in various applications, depending upon the availability of target spectral signature. Basically, they are based on a similar linear process, which makes them highly correlated. In this paper, we propose a novel adjusted spectral matched filter (ASMF) for hyperspectral target detection, which aims to effectively improve target detection performance with anomaly detection output. Specifically, a typical case is presented by using the Reed-Xiaoli (RX) anomaly detector to adjust the output of supervised constrained energy minimization (CEM) detector. The adjustment is appropriately controlled by a weighting parameter in different detection scenarios. Experiments were implemented by using both synthetic and real hyperspectral datasets. Compared to the traditional single detection method (e.g., CEM), the experimental results demonstrate that the proposed ASMF can effectively improve its performance by utilizing the result from an anomaly detector (e.g., RX), particularly in situations with a complex background or strong anomalies.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.