IMAGE FUSION AND RECOGNITION BASED ON COMPRESSED SENSING THEORY

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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

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VOLUME 8 , ISSUE 1 (March 2015) > List of articles

IMAGE FUSION AND RECOGNITION BASED ON COMPRESSED SENSING THEORY

Qiuchan Bai / '> Chunxia Jin

Keywords : Mage fusion, target recognition, compressed sensing, wavelet transform.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 1, Pages 159-180, DOI: https://doi.org/10.21307/ijssis-2017-753

License : (CC BY-NC-ND 4.0)

Received Date : 30-October-2014 / Accepted: 08-January-2015 / Published Online: 01-March-2015

ARTICLE

ABSTRACT

As the compressed sensing theory can offer a better performance than Nyquist sampling theorem when dealing with large amounts of data, it becomes very popular for image fusion and target recognition in image processing. In this paper, a new image fusion algorithm based on compressed sensing was proposed. By discrete cosine transform, it fused images through weighted coefficient, recovered the fusion images by basic pursuit algorithm. Moreover, a recognition algorithm in compressed sensing was also studied, which obtained a sample matrix using preprocessing based on a wavelet transform, calculated the approximate coefficient by orthogonal matching pursuit, and made a
classification using the with minimum distance formula. Finally, experiments were designed to demonstrate the effectiveness of the proposed algorithms.

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