Feature fusion algorithm based on DT-CWT texture

Approximate shift invariance, good directional selectivity, computational efficiency properties of DT-CWT make it a good candidate for representing the texture features. In this paper, we propose a method for efficiently using the properties of DT-CWT in finding the directional and spatial frequency characteristics of the patterns and classifying different texture patterns in terms of these characteristics. The paper adopts the arithmetic of the feature data fusion based on D-S evidence theory to fuse the multisource DT-CWT texture of the object. Experimental results show that the proposed feature extraction and the feature data fusion based D-S evidence theory is efficient in terms of detection object in multisource low distinguish remote image.