Affiliation:
1. Wuxi University
2. HorizonFlow Laboratory
3. Jiangnan University
4. Chinese Academy of Sciences
5. Nanjing Agricultural University
Abstract
To obtain an image with both high spatial resolution and a large field of view (FoV), we designed a deep space-bandwidth product (SBP)-expanded framework (Deep SBP+). Combining a single-captured low-spatial-resolution image with a large FoV and a few captured high-spatial-resolution images in sub-FoVs, an image with both high spatial resolution and a large FoV can be reconstructed via Deep SBP+. The physical model-driven Deep SBP+ reconstructs the convolution kernel as well as up-samples the low-spatial resolution image in a large FoV without relying on any external datasets. Compared to conventional methods relying on spatial and spectral scanning with complicated operations and systems, the proposed Deep SBP+ can reconstruct high-spatial-resolution and large-FoV images with much simpler operations and systems as well as faster speed. Since the designed Deep SBP+ breaks through the trade-off of high spatial resolution and large FoV, it is a promising tool for photography and microscopy.
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
Subject
Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials