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Information Technology Journal
  Year: 2009 | Volume: 8 | Issue: 3 | Page No.: 263-274
DOI: 10.3923/itj.2009.263.274
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Optimum Method Selection for Resolution Enhancement of Hyperspectral Imagery

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

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.
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  •    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






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