Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Information Technology Journal
  Year: 2009 | Volume: 8 | Issue: 3 | Page No.: 263-274
DOI: 10.3923/itj.2009.263.274
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Optimum Method Selection for Resolution Enhancement of Hyperspectral Imagery

F.A. Mianji, Y. Zhang and A. Babakhani

Abstract:
The study categorizes the most frequent researched areas of resolution enhancement in hyperspectral imagery and emphasizes on their applications, requirements, achievements and limitations of different approaches. An evaluation of the capabilities of different classes of super-resolution algorithms in hyperspectral imagery shows that there is no generic approach to optimally produce high-quality results on general hyperspectral images and the adequacy of an algorithm is a function of multiple factors, namely, access to multisource information, computational complexity, availability of reliable training data for learning-based methods, efficiency of the algorithm and the expected application. It is also shown that spectral mixture analysis based techniques are appropriate for developing high performance and fast super-resolution algorithms in hyperspectral imagery.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    A New Bands Selection Algorithm for Hyperspectral Image using Hyperspectral Derivative on Clifford Manifold
How to cite this article:

F.A. Mianji, Y. Zhang and A. Babakhani, 2009. Optimum Method Selection for Resolution Enhancement of Hyperspectral Imagery. Information Technology Journal, 8: 263-274.

DOI: 10.3923/itj.2009.263.274

URL: https://scialert.net/abstract/?doi=itj.2009.263.274

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 

Curve Bottom