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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 8 , ISSUE 2 (June 2015) > List of articles


Yin Zhouping

Keywords : fusion algorithm, SAR, optical images, sparse representation, algorithm running time, Support Value Transform.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 2, Pages 1,123-1,141, DOI: https://doi.org/10.21307/ijssis-2017-799

License : (CC BY-NC-ND 4.0)

Received Date : 30-January-2015 / Accepted: 12-April-2015 / Published Online: 01-June-2015



Due to the different imaging mechanism of optical image and Synthetic Aperture Radar (SAR) image, they have the large different characteristics between the images, so fusing optical image and SAR image with image fusion technology could complement advantages and be able to better interpret the scenes information. A fusion algorithm of Synthetic Aperture Radar and optical image with fast sparse representation on low-frequency images was proposed. For the disadvantage of target information easily missing and the contrast low in fused image, and the fusion method with sparse representation could effectively retain target information of Synthetic Aperture Radar image, so the
paper fuses low frequency images of Synthetic Aperture Radar and optical images using sparse representation. Moreover a new sparse coefficient fusion rules is proposed, and sparse decomposition process is improved to reduce the algorithm running time. Experimental results demonstrate the effectiveness of the algorithm.

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