Spectral derivative feature coding for hyperspectral signature analysis

Chein-I Chang; Sumit Chakravarty

doi:10.1117/12.681662

1 September 2006 Spectral derivative feature coding for hyperspectral signature analysis

Chein-I Chang, Sumit Chakravarty

Proceedings Volume 6302, Imaging Spectrometry XI; 63020F (2006) https://doi.org/10.1117/12.681662
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

This paper presents a new approach to hyperspectral signature analysis, called Spectral Derivative Feature Coding (SDFC). It makes use of gradient changes in adjacent bands to characterize spectral variations so as to improve spectral discrimination and identification. In order to evaluate its performance, two binary coding methods, SPectral Analysis Manager (SPAM) and Spectral Feature-based Binary Coding (SFBC) are used to conduct comparative analysis. The experimental results demonstrate the proposed SDFC performs more effectively in capturing spectral characteristics.

Citation Download Citation

Chein-I Chang and Sumit Chakravarty "Spectral derivative feature coding for hyperspectral signature analysis", Proc. SPIE 6302, Imaging Spectrometry XI, 63020F (1 September 2006); https://doi.org/10.1117/12.681662

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