Optics and Precision Engineering, Volume. 31, Issue 14, 2135(2023)
Image reconstruction based on deep compressive sensing combined with global and local features
Fig. 1. Global-to-Local Compressive Sensing Image Reconstruction Model Structure
Fig. 3. Sampling rate is 10%, and the reconstruction images of each algorithm on the image House are compared
Fig. 4. Sampling rate is 20%, and the reconstruction image comparison of each algorithm on the image Monarch
Fig. 5. Change curve of loss with the number of training iterations (epochs) at 20% sampling rate
Fig. 6. G2LNet reconstruction image and filter flow visualization at 30% sampling rate
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Yuanhong ZHONG, Qianfeng XU, Yujie ZHOU, Shanshan WANG. Image reconstruction based on deep compressive sensing combined with global and local features[J]. Optics and Precision Engineering, 2023, 31(14): 2135
Category: Information Sciences
Received: Dec. 6, 2022
Accepted: --
Published Online: Aug. 2, 2023
The Author Email: ZHONG Yuanhong (zhongyh@cqu.edu.cn)