.png){kind=icon}
返回
Deep-Learned Regularization and Proximal Operator for Image Compressive Sensing
.png){kind=icon}
OA
AI
DOI：10.1109/TIP.2021.3088611.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Deep learning has recently been intensively studied in the context of image compressive sensing (CS) to discover and represent complicated image structures. These approaches, however, either suffer from nonflexibility for an arbitrary sampling ratio or lack an explicit deep-learned regularization term. This paper aims to solve the CS reconstruction problem by combining the deep-learned regularization term and proximal operator. We first introduce a regularization term using a carefully designed residual-regressive net, which can measure the distance between a corrupted image and a clean image set and accurately identify to which subspace the corrupted image belongs. We then address a proximal operator with a tailored dilated residual channel attention net, which enables the learned proximal operator to map the distorted image into the clean image set. We adopt an adaptive proximal selection strategy to embed the network into the loop of the CS image reconstruction algorithm. Moreover, a self-ensemble strategy is presented to improve CS recovery performance. We further utilize state evolution to analyze the effectiveness of the designed networks. Extensive experiments also demonstrate that our method can yield superior accurate reconstruction (PSNR gain over 1 dB) compared to other competing approaches while achieving the current state-of-the-art image CS reconstruction performance. The test code is available at https://github.com/zjut-gwl/CSDRCANet.
Keyword:
Image reconstruction
Optimization
Neural networks
Loss measurement
Iterative algorithms
Approximation algorithms
Noise reduction
Compressive sensing (CS)
image reconstruction
neural networks
state evolution (SE)
proximal operator
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
引用论文
Presenting Concerns of Veterans Entering Treatment for Posttraumatic Stress Disorder提出退伍军人进入创伤后应激障碍治疗的担忧
.png){kind=icon}
PREAI
分享收藏
查看更多内容