A Novel Change Detection Method Using Independent Component Analysis and Oriented-Object Method

Xiao Chun Li; Chun Yang Jia; Wei Hua Li

doi:10.4028/www.scientific.net/AMM.548-549.633

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 548-549A Novel Change Detection Method Using Independent...

A Novel Change Detection Method Using Independent Component Analysis and Oriented-Object Method

Abstract:

hrough analyzing problems brought on change detection methods of high-resolution remote sensing images, a novel change detection algorithm is proposed. First, feature images of image’s objects extracted using oriented-object method serve as data of input vector to estimate sub-space for Independent Component Analysis(ICA), which can improve effect of noise suppression, simultaneously, a new algorithm using self-adapted weight is proposed in order to extract image’s object, which optimizes processing method on oriented-object deeply；new partitioning scheme using undecimated discrete wavelet transform(UDWT) overcomes effectively prominent problem which shrinking of the size of input vector becomes leads to unprecisely estimation of sub-space for ICA. Compared with typical algorithm, such as ICA and UDWT, simulation results show that new algorithm improves robust and veracity of change detection for high-resolution images greatly.

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Periodical:

Applied Mechanics and Materials (Volumes 548-549)

Pages:

633-636

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.548-549.633

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Online since:

April 2014

Authors:

Xiao Chun Li*, Chun Yang Jia, Wei Hua Li

Keywords:

Change Detection, ICA, Image’s Objects, UDWT

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