Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning
Very high resolution (VHR) image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (...
Main Authors: | Yuan Xu, Kun Ding, Chunlei Huo, Zisha Zhong, Haichang Li, Chunhong Pan |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2015-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2015/947695 |
Similar Items
-
Adaptive Multiscale Methods for Sparse Image Representation and Dictionary Learning
by: Budinich, Renato
Published: (2019) -
Multiscale Sparse Dictionary Learning With Rate Constraint for Seismic Data Compression
by: Xin Tian
Published: (2019-01-01) -
Robust Visual Tracking with Discrimination Dictionary Learning
by: Yuanyun Wang, et al.
Published: (2018-01-01) -
COMBINING LOCAL FEATURES AND PROGRESSIVE SUPPORT VECTOR MACHINE FOR URBAN CHANGE DETECTION OF VHR IMAGES
by: C. Huo, et al.
Published: (2012-07-01) -
Paired Dictionary Learning Based on Discriminant Reconstruction Analysis For Sparse Representation
by: Hui-Hung Wang, et al.
Published: (2015)