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Library Sub-pixel mapping of remotely sensed imagery with hybrid intra- and inter-pixel dependence

Sub-pixel mapping of remotely sensed imagery with hybrid intra- and inter-pixel dependence

Sub-pixel mapping of remotely sensed imagery with hybrid intra- and inter-pixel dependence

Resource information

Date of publication
december 2013
Resource Language
ISBN / Resource ID
AGRIS:US201400148349
Pages
341-357

Sub-pixel mapping of remotely sensed imagery is often performed by assuming that land cover is spatially dependent both within and between image pixels. Intra- and inter-pixel dependencies are two widely used approaches to represent different land-cover spatial dependencies at present. However, merely using intra- or inter-pixel dependence alone often fails to fully describe land-cover spatial dependence, making current sub-pixel mapping models defective. A more reasonable object for sub-pixel mapping is maximizing both intra- and inter-pixel dependencies simultaneously instead of using only one of them. In this article, the differences between intra- and inter-pixel dependencies are discussed theoretically, and a novel sub-pixel mapping model aiming to maximize hybrid intra- and inter-pixel dependence is proposed. In the proposed model, spatial dependence is formulated as a weighted sum of intra-pixel dependence and inter-pixel dependence to satisfy both intra- and inter-pixel dependencies. By application to artificial and synthetic images, the proposed model was evaluated both visually and quantitatively by comparing with three representative sub-pixel mapping algorithms: the pixel swapping algorithm, the sub-pixel/pixel attraction algorithm, and the pixel swapping initialized with sub-pixel/pixel attraction algorithm. The results showed increased accuracy of the proposed algorithm when compared with these traditional sub-pixel mapping algorithms.

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Authors and Publishers

Author(s), editor(s), contributor(s)

Ling, Feng
Li, Xiaodong
Du, Yun
Xiao, Fei

Publisher(s)
Data Provider