25 October 2013 Compressed sensing image processing in the wavelet transform domain
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Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 89191A (2013) https://doi.org/10.1117/12.2030391
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Multi-resolution is the good characteristics of wavelet transform. In wavelet transform domain, high frequency subband of image is sparse. Less high frequency coefficient can be sampled by compressed sensing technology. In this study, for an image, a sparse representation in the wavelet transform domain is found. Image is reconstructed by the orthogonal matching pursuit (OMP) , compressive sampling matching pursuit (CoSaMP), iteratively reweighted least square (IRLS) and Suspace Pursuit (SP), respectively. Different wavelet basis and sampling rate which affect the quality of the reconstruction are discussed. Experimental result shows that performance of IRLS is the best, OMP are easy implementation and fast speed, and Coif3 has a better performance than the other wavelet basis.
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Zhen-kun Lu, Ping Gong, Jin-hu Peng, "Compressed sensing image processing in the wavelet transform domain", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 89191A (25 October 2013); doi: 10.1117/12.2030391; https://doi.org/10.1117/12.2030391
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