@inproceedings{192ec6b9f9fd4fdf94d1dcd6f2896fec,
title = "Unrolling Multi-channel Weighted Nuclear Norm Minimization for Image Denoising",
abstract = "We propose an unrolled deep network that integrates the flexibility of model-based algorithms and the advantages of learning-based algorithms. Specifically, based on the multi-channel optimization model for real color image denoising under the weighted nuclear norm minimization formulation, we propose an algorithm for image denoising that can learn the weights for nuclear norm from training datasets through end-to-end training. Experimental results show that the proposed algorithm achieves better performance than traditional iterative algorithms.",
keywords = "Image denoising, unrolled optimization",
author = "Pham, {Thuy Thi} and Mai, {Truong Thanh Nhat} and Chul Lee",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 ; Conference date: 05-07-2022 Through 08-07-2022",
year = "2022",
doi = "10.1109/ITC-CSCC55581.2022.9894978",
language = "English",
series = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "243--244",
booktitle = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
address = "United States",
}