1. A Novel Change Detection Method Using Independent Component Analysis and Oriented-Object Method
- Author
-
Chun Yang Jia, Xiao Chun Li, and Wei Hua Li
- Subjects
Discrete wavelet transform ,business.industry ,Computer science ,Feature (computer vision) ,Computer vision ,Pattern recognition ,General Medicine ,Artificial intelligence ,Object (computer science) ,business ,Independent component analysis ,Change detection ,Image (mathematics) - 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.
- Published
- 2014