Deep denoiser prior and smoothed projection landweber inspired block-wise compressed sensing Online publication date: Tue, 04-Oct-2022
by Chun-mei Zong; Yue-qin Zhang; Qing-Shan Zhao
International Journal of Computing Science and Mathematics (IJCSM), Vol. 15, No. 4, 2022
Abstract: How to use effective image prior to reconstruct high-quality images is a key problem in compressed sensing reconstruction. By introducing instantiation priors, traditional optimisation model-based compressed sensing reconstruction methods enjoy good structural analysis ability. To further improve the reconstruction quality, the optimisation model-based method is combined with deep learning to introduce a deep denoiser prior into BCS-SPL algorithm via a plug and play technique. Notably, the denoising operator is obtained by training a multi-scale residual network with data-driven discriminant learning method. Multi-scale network can extract different scale feature information about the image, and the introduced deep prior is beneficial for reconstructing high-quality images. Experimental results exhibit that the proposed method can effectively improve the image reconstruction quality without the expense of too much computational complexity.
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