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Difference of Convolution for Deep Compressive Sensing

2019-09-22IEEE International Conference on Image Processing 2019Code Available0· sign in to hype

Canh, Thuong Nguyen; Jeon, Byeungwoo

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Abstract

Deep learning-based compressive sensing (DCS) has improved the compressive sensing (CS) with fast and high reconstruction quality. Researchers have further extended it to multi-scale DCS which improves reconstruction quality based on Wavelet decomposition. In this work, we mimic the Difference of Gaussian via convolution and propose a scheme named as Difference of convolution-based multi-scale DCS (DoC-DCS). Unlike the multi-scale DCS based on a well-designed filter in wavelet domain, the proposed DoC-DCS learns decomposition, thereby, outperforms other state-of-the-art compressive sensing methods.

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