Cart (Loading....) | Create Account
Close category search window
 

A Novel Adaptive Scheme for Evaluating Spectral Similarity in High-Resolution Urban Scenes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Bin Chen ; Digital Imaging & Remote Sensing Lab., Rochester Inst. of Technol., Rochester, NY, USA ; Vodacek, A. ; Cahill, N.D.

The analysis of high-spatial-resolution urban images for object recognition must deal with variable illumination conditions and many spectrally similar materials in the built environment. Spectral similarity measures have the potential to contribute to the effective analysis of urban scenes, however, without readily available surface reflectance conversion, the characteristics of existing spectral measures may lead to unacceptable performance. To better account for these spectral imaging scenarios for an urban environment, a simplified in-scene radiometric calibration approach is presented to preserve data collinearity, and a novel spectral similarity measure based on the geometric characteristics of the Mahalanobis distance is developed to incorporate both spectral direction and spectral magnitude. With a minimum of human input to define representative pixels, the experimental results demonstrate through the analysis of ROC curves the potential advantages of the novel distance measure when applied to the identification of materials in urban images.

Published in:

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:6 ,  Issue: 3 )

Date of Publication:

June 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.