DocumentCode :
71390
Title :
Super-Resolution Land Cover Mapping Based on Multiscale Spatial Regularization
Author :
Jianlong Hu ; Yong Ge ; Yuehong Chen ; Deyu Li
Author_Institution :
Sch. of Comput. & Inf. Technol., Shanxi Univ., Taiyuan, China
Volume :
8
Issue :
5
fYear :
2015
fDate :
May-15
Firstpage :
2031
Lastpage :
2039
Abstract :
Super-resolution mapping (SRM) is a method for allocating land cover classes at a fine scale according to coarse fraction images. Based on a spatial regularization framework, this paper proposes a new regularization method for SRM that integrates multiscale spatial information from the fine scale as a smooth term and from the coarse scale as a penalty term. The smooth term is considered a homogeneity constraint, and the penalty term is used to characterize the heterogeneity constraint. Specifically, the smooth term depends on the local fine scale spatial consistency, and is used to smooth edges and eliminate speckle points. The penalty term depends on the coarse scale local spatial differences, and suppresses the over-smoothing effect from the fine scale information while preserving more details (e.g., connectivity and aggregation of linear land cover patterns). We validated our method using simulated and synthetic images, and compared the results to four representative SRM algorithms. Our numerical experiments demonstrated that the proposed method can produce more accurate maps, reduce differences in the number of patches, visually preserve smoother edges and more details, reject speckle points, and suppress over-smoothing.
Keywords :
geophysical image processing; image classification; image resolution; land cover; terrain mapping; SRM land cover; fine scale information; fraction image; image simulation; land cover class; linear land cover pattern aggregation; linear land cover pattern connectivity; local fine scale spatial consistency; multiscale spatial information; multiscale spatial regularization; over-smoothing effect; penalty term; regularization method; smooth edge; smooth term; spatial regularization framework; speckle point elimination; super-resolution mapping; synthetic image; Accuracy; Indexes; Linear programming; Manganese; Remote sensing; Spatial resolution; Fraction images; heterogeneity; homogeneity; multiscale; regularization; remote sensing; spatial dependence; super-resolution mapping (SRM);
fLanguage :
English
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
Publisher :
ieee
ISSN :
1939-1404
Type :
jour
DOI :
10.1109/JSTARS.2015.2399509
Filename :
7045474
Link To Document :
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