no code implementations • 8 Feb 2021 • Moran Xu, Dianlin Hu, Weifei Wu, Weiwen Wu
Image restoration is a typical ill-posed problem, and it contains various tasks.
no code implementations • 28 Aug 2020 • Weiwen Wu, Dianlin Hu, Chuang Niu, Lieza Vanden Broeke, Anthony P. H. Butler, Peng Cao, James Atlas, Alexander Chernoglazov, Varut Vardhanabhuti, Ge Wang
To address the image deblurring problem associated with the $L_2^2$-loss, we propose a general $L_p^p$-loss, $p>0$ Furthermore, the images from different energy bins share similar structures of the same object, the regularization characterizing correlations of different energy bins is incorporated into the $L_p^p$-loss function, which helps unify the deep learning based methods with traditional compressed sensing based methods.
no code implementations • 4 Aug 2020 • Weiwen Wu, Dianlin Hu, Wenxiang Cong, Hongming Shan, Shao-Yu Wang, Chuang Niu, Pingkun Yan, Hengyong Yu, Varut Vardhanabhuti, Ge Wang
ACID synergizes a deep reconstruction network trained on big data, kernel awareness from CS-inspired processing, and iterative refinement to minimize the data residual relative to real measurement.