Multiple object detection in hyperspectral imagery using spectral fringe-adjusted joint transform correlator

Paheding Sidike; Vijayan K. Asari; Mohammad S. Alam

doi:10.1117/12.2076798

27 February 2015 Multiple object detection in hyperspectral imagery using spectral fringe-adjusted joint transform correlator

Paheding Sidike, Vijayan K. Asari, Mohammad S. Alam

Author Affiliations +

Proceedings Volume 9405, Image Processing: Machine Vision Applications VIII; 940502 (2015) https://doi.org/10.1117/12.2076798
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

Abstract

Hyperspectral imaging (HSI) sensors provide plenty of spectral information to uniquely identify materials by their reflectance spectra, and this information has been effectively used for object detection and identification applications. Joint transform correlation (JTC) based object detection techniques in HSI have been proposed in the literatures, such as spectral fringe-adjusted joint transform correlation (SFJTC) and with its several improvements. However, to our knowledge, the SFJTC based techniques were designed to detect only similar patterns in hyperspectral data cube and not for dissimilar patterns. Thus, in this paper, a new deterministic object detection approach using SFJTC is proposed to perform multiple dissimilar target detection in hyperspectral imagery. In this technique, input spectral signatures from a given hyperspectral image data cube are correlated with the multiple reference signatures using the classassociative technique. To achieve better correlation output, the concept of SFJTC and the modified Fourier-plane image subtraction technique are incorporated in the multiple target detection processes. The output of this technique provides sharp and high correlation peaks for a match and negligible or no correlation peaks for a mismatch. Test results using real-life hyperspectral data cube show that the proposed algorithm can successfully detect multiple dissimilar patterns with high discrimination.

Citation Download Citation

Paheding Sidike, Vijayan K. Asari, and Mohammad S. Alam "Multiple object detection in hyperspectral imagery using spectral fringe-adjusted joint transform correlator", Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 940502 (27 February 2015); https://doi.org/10.1117/12.2076798

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available