Title :
Superresolution Reconstruction of Multispectral Data for Improved Image Classification
Author :
Li, Feng ; Jia, Xiuping ; Fraser, Donald
Author_Institution :
Sch. of Inf. Technol. & Electr. Eng., Univ. of New South Wales at The Australian Defence Force Acad., Canberra, ACT, Australia
Abstract :
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.
Keywords :
geophysical techniques; image classification; image reconstruction; pattern clustering; remote sensing; SR reconstruction; image classification; interpolation method; multispectral image clustering; remote sensing; spatial resolution; superresolution reconstruction; Clustering and classification; Moderate Resolution Imaging Spectroradiometer (MODIS); discrete wavelet transform; maximum a posteriori (MAP); superresolution (SR);
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2009.2023604
