Open AccessSliding Window-based Probabilistic Change Detection for Remote-sensed Images
Author(s) -
Seokyong Hong,
Ranga Raju Vatsavai
Publication year - 2016
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2016.05.438
Subject(s) - change detection , computer science , probabilistic logic , sliding window protocol , grid , window (computing) , pixel , artificial intelligence , extension (predicate logic) , remote sensing , occupancy grid mapping , computer vision , pattern recognition (psychology) , data mining , geology , geodesy , programming language , mobile robot , robot , operating system
A recent probabilistic change detection algorithm provides a way for assessing changes on remote-sensed images which is more robust to geometric and atmospheric errors than existing pixel-based methods. However, its grid (patch)-based change detection results in coarse-resolution change maps and often discretizes continuous changes that occur across grid boundaries. In this study, we propose a sliding window-based extension of the probabilistic change detection approach to overcome such artificial limitations
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