Technique based on image pyramid and bayes rule for noise reduction in unsupervised change detection |
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Authors: | Zhi-qiang Li hong Huo Tao Fang Ju-lian Zhu Wei-li Ge |
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Institution: | (1) Department of Information Engineering and Computer Science, University of Trento, via Sommarive, 14-38123 Trento, Italy |
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Abstract: | In this paper, a technique based on image pyramid and Bayes rule for reducing noise effects in unsupervised change detection
is proposed. By using Gaussian pyramid to process two multitemporal images respectively, two image pyramids are constructed.
The difference pyramid images are obtained by point-by-point subtraction between the same level images of the two image pyramids.
By resizing all difference pyramid images to the size of the original multitemporal image and then making product operator
among them, a map being similar to the difference image is obtained. The difference image is generated by point-by-point subtraction
between the two multitemporal images directly. At last, the Bayes rule is used to distinguish the changed pixels. Both synthetic
and real data sets are used to evaluate the performance of the proposed technique. Experimental results show that the map
from the proposed technique is more robust to noise than the difference image. |
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Keywords: | change detection change vector analysis multitemporal images image pyramid |
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