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Super-resolution target mapping from soft classified remotely sensed imagery

Atkinson, P.M. (2005) Super-resolution target mapping from soft classified remotely sensed imagery Photogrammetric Engineering and Remote Sensing, 71, (7), pp. 839-846.

Record type: Article


A simple, efficient algorithm is presented for sub-pixel target mapping from remotely-sensed images. Following an initial random allocation of “soft” pixel proportions to “hard” sub-pixel binary classes, the algorithm works in a series of iterations, each of which contains three stages. For each pixel, for all sub-pixel locations, a distance-weighted function of neighboring sub-pixels is computed. Then, for each pixel, the sub-pixel representing the target class with the minimum value of the function, and the sub-pixel representing the background with the maximum value of the function are found. Third, these two sub-pixels are swapped if the swap results in an increase in spatial correlation between sub-pixels. The new algorithm predicted accurately when applied to simple simulated and real images. It represents an accessible tool that can be coded and applied readily by remote sensing investigators.

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Published date: July 2005


Local EPrints ID: 54927
ISSN: 0099-1112
PURE UUID: 94888c37-7922-4e5e-90c4-09863fb9bd76

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Date deposited: 01 Aug 2008
Last modified: 17 Jul 2017 14:34

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