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Applying Image Fusion Technique with MRFKMC for Change Detection in SAR Images

Vasireddy Pravalya, J Krishna Chaithanya, T. Ramashri. Published in Image Processing.

Communications on Applied Electronics
Year of Publication: 2015
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Vasireddy Pravalya, J Krishna Chaithanya, T. Ramashri
10.5120/cae2015651741

Vasireddy Pravalya, Krishna J Chaithanya and T Ramashri. Article: Applying Image Fusion Technique with MRFKMC for Change Detection in SAR Images. Communications on Applied Electronics 2(4):38-42, July 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Vasireddy Pravalya and J Krishna Chaithanya and T. Ramashri},
	title = {Article: Applying Image Fusion Technique with MRFKMC for Change Detection in SAR Images},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {2},
	number = {4},
	pages = {38-42},
	month = {July},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

In this paper, a novel framework for change detection in synthetic aperture radar (SAR) images based on image fusion and clustering algorithms have been carried out. The significance of image fusion technique is to generate a difference image (DI) by using complementary information from a mean-ratio image and a log-ratio image. Dual - tree complex discrete wavelet transform (DTCWT) fusion technique is considered in this paper. To restrain the background information and enhance the information of changed regions in the fused image, DTCWT fusion algorithm is applied on ratio images. The approach then classifies changed and unchanged regions by Markov random field K-means (MRFKMC) clustering algorithm. Theoretical analysis experiments are carried out on SAR images by applying MRFKMC and compared the results with MRFFCM.

References

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Keywords

Dual tree complex wavelet transform, difference image, image fusion, K-means clustering, Markov random field, synthetic aperture radar.