A novel SAR image compress and reconstruction algorithm based on compressive sampling (CS) is proposed in this paper. Firstly, the image is represented sparsely by G-level contourlet. Secondly, a Gaussian random matri...
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ISBN:
(纸本)9781467362498;9781467362481
A novel SAR image compress and reconstruction algorithm based on compressive sampling (CS) is proposed in this paper. Firstly, the image is represented sparsely by G-level contourlet. Secondly, a Gaussian random matrices that proximate QR factorization is constructed to measure the high frequency coefficients and to realize data compression. Lastly, a modified sparsity adaptive matching pursuit algorithm(SAMP) is used to realize the precise reconstruction of SAR image. Experimental results demonstrate that the proposed algorithm can get better reconstruction performances and the convergence of the algorithm is much faster than the existed algorithms.
This paper introduces the fundamental knowledge of compressed sensing theory, and analyzes the important reconstruction algorithms such as orthogonal matchingpursuit, subspace pursuit, but we should know the sparse d...
详细信息
ISBN:
(纸本)9781479958368
This paper introduces the fundamental knowledge of compressed sensing theory, and analyzes the important reconstruction algorithms such as orthogonal matchingpursuit, subspace pursuit, but we should know the sparse degree. The sparsity adaptive matching pursuit algorithm can be terminated by setting the conditions to make adaptive sparse degree. This paper puts forward a modified sparsityadaptivealgorithm based on those three algorithms. The simulation results show that new algorithm can accurately reconstruct the original signal, and has better results than SAMP.
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