Image fusion in compressed sensing based on non-subsampled contourlet transform

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Abstract

A fusion method based on non-subsampled contourlet transform (NSCT) in compressed sensing was proposed. The method decomposes two or more original images using NSCT, and gets the sparse matrix by the NSCT coefficients sparse representation, and fuses the sparse matrices with the coefficients absolute value maximum scheme. The compressed sample can be received through randomly observed. The fused image is recovered from the reduced samples by solving the optimization. The simulations show that the proposed CS-based image fusion algorithm has the advantages of simple structure and easy implementation, and also can achieve a better fusion performance.

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Zhou, X., Wang, W., & Liu, R. an. (2015). Image fusion in compressed sensing based on non-subsampled contourlet transform. In Lecture Notes in Electrical Engineering (Vol. 322, pp. 645–652). Springer Verlag. https://doi.org/10.1007/978-3-319-08991-1_66

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