Super-resolution target mapping from soft classified remotely sensed imagery

Atkinson, P.M. (2001) Super-resolution target mapping from soft classified remotely sensed imagery In Proceedings of the 5th International Conference on GeoComputation. University of Leeds..


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A simple, efficient algorithm is presented for super-resolution target mapping from remotely sensed images. Following an initial random allocation of pixel proportions to binary 'hard' sub-pixel classes, the algorithm works in a series of iterations, each of which contains two stages. For each iteration, a distance weighted function of neighbouring pixels is computed for all sub-pixels. Then, on a pixel-by-pixel basis, the '1' with the minimum value of the function is swapped with the '0' with the maximum value of the function, if the swap results in an increase in some objective function. The algorithm is demonstrated to work reasonably well with simple images, opening the way for further research to explore the algorithm, to extend the algorithm to multiple classes and to develop more efficient, but equally simple algorithms.

Item Type: Conference or Workshop Item (Paper)
Additional Information: CD-Rom
Venue - Dates: 5th International Conference on GeoComputation, 2001-01-01
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ePrint ID: 15694
Date :
Date Event
Date Deposited: 25 May 2005
Last Modified: 16 Apr 2017 23:28
Further Information:Google Scholar

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