Nonlocal Low-Rank Residual Modeling for Image Compressive Sensing Reconstruction-Reference-Cited by-同舟云学术

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Nonlocal Low-Rank Residual Modeling for Image Compressive Sensing Reconstruction

Published:2023-10-08 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Image Processing (ICIP)
language:
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Author:

Zhang Junhao¹,Yap Kim-Hui¹,Chau Lap-Pui²,Zhu Ce³

Affiliation:

1. Nanyang Technological University,School of Electrical & Electronic Engineering,Singapore,639798

2. The Hong Kong Polytechnic University,Department of Electronic and Information Engineering,Hong Kong,China

3. University of Electronic Science and Technology of China,School of Information and Communication Engineering,Chengdu,China,611731

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10221937/10221892/10222196.pdf?arnumber=10222196

Reference33 articles.

1. Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries

2. Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision

3. Non-local sparse models for image restoration

4. Image compressive sensing recovery using adaptively learned sparsifying basis via L0 minimization

5. Image quality assessment: from error visibility to structural similarity;zhou;IEEE Transactions on Image Processing,2004

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