The effect of the point spread function on sub-pixel mapping

Wang, Qunming and Atkinson, Peter M. (2017) The effect of the point spread function on sub-pixel mapping. Remote Sensing of Environment, 193. pp. 127-137. ISSN 0034-4257

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Abstract Sub-pixel mapping (SPM) is a process for predicting spatially the land cover classes within mixed pixels. In existing SPM methods, the effect of point spread function (PSF) has seldom been considered. In this paper, a generic SPM method is developed to consider the PSF effect in SPM and, thereby, to increase prediction accuracy. We first demonstrate that the spectral unmixing predictions (i.e., coarse land cover proportions used as input for SPM) are a convolution of not only sub-pixels within the coarse pixel, but also sub-pixels from neighboring coarse pixels. Based on this finding, a new SPM method based on optimization is developed which recognizes the optimal solution as the one that when convolved with the PSF, is the same as the input coarse land cover proportion. Experimental results on three separate datasets show that the SPM accuracy can be increased by considering the PSF effect.

Item Type:
Journal Article
Journal or Publication Title:
Remote Sensing of Environment
Additional Information:
This is the author’s version of a work that was accepted for publication in Remote Sensing of Environment. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Remote Sensing of Environment, 193, 2017 DOI: 10.1016/j.rse.2017.03.002
Uncontrolled Keywords:
?? land cover mappingdownscalingsub-pixel mapping (spm)super-resolution mappingpoint spread function (psf)hopfield neural network (hnn)soil sciencecomputers in earth sciencesgeology ??
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Deposited On:
13 May 2017 02:30
Last Modified:
18 Dec 2023 01:45