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Superresolution Reconstruction of Multispectral Data for Improved Image Classification

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3 Author(s)
Feng Li ; Sch. of Inf. Technol. & Electr. Eng., Univ. of New South Wales at The Australian Defence Force Acad., Canberra, ACT, Australia ; Xiuping Jia ; Fraser, D.

In this letter, the application of superresolution (SR) techniques to multispectral image clustering and classification is investigated and tested using satellite data. A set of multispectral images with better spatial resolution is obtained after an SR technique is applied to several data sets recorded within a short period over a study area. Improved clustering and classification performance is demonstrated visually and quantitatively by comparison with the original low-resolution data or enlarged images using a conventional interpolation method. This letter illustrates the possibility and feasibility of the use of SR reconstruction for the classification of remote sensing data, which is encouraging as a means of breaking through current satellite detectors' resolution limits.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:6 ,  Issue: 4 )