Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
447680 | AEU - International Journal of Electronics and Communications | 2013 | 9 Pages |
Abstract
This article proposes a study of the reduced quaternion wavelet transform (RQWT) which has one shift-invariant magnitude and three angle phases at each scale from digital image analysis application. A new multiscale texture classifier which uses features extracted from the sub-bands of the RQWT decomposition is proposed in the transform domain. The proposed method can achieve a high texture classification rate. The experimental results can demonstrate the robustness of the proposed method and achieve a higher texture classification accuracy rate than a famous wavelet transform based classifier.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Shan Gai, Guowei Yang, Sheng Zhang,