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29 April 2022 Parallel enhanced network for image compressed sensing
Wenna Ma, Xiangjun Wu
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Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 122470D (2022) https://doi.org/10.1117/12.2636940
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China
Abstract
Despite the remarkable progress has made in deep compressed sensing (DCS), how to improve the reconstruction quality is still a major challenge. The existing DCS model generally still has some issues, especially in recovering details. In this paper, a new parallel enhanced network (PENet) is proposed for image compressed sensing. PENet is designed as a sampling network and a parallel network, which contains a basic network and an enhanced network. The basic network is designed to provide the initial reconstructed image. The enhanced network is trained to progressively acquire module details through the connections with each block of the basic network in stages. The final reconstructed image is the cumulative results between the parallel network. Experimental result shows that PENet has a high reconstruction quality and comparable running time complexity with existing advanced DCS methods.
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Wenna Ma and Xiangjun Wu "Parallel enhanced network for image compressed sensing", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 122470D (29 April 2022); https://doi.org/10.1117/12.2636940
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KEYWORDS
Compressed sensing
Neural networks
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