Deep SBP+ 2.0: a physics-driven generation capability enhanced framework to reconstruct a space-bandwidth product expanded image from two image shots

Author:

Li Chen1,Xiao Zhibo12ORCID,Wang Shouyu1ORCID

Affiliation:

1. Wuxi University

2. HorizonFlow Laboratory

Abstract

The space-bandwidth product (SBP) limitation makes it difficult to obtain an image with both a high spatial resolution and a large field of view (FoV) through commonly used optical imaging systems. Although FoV and spectrum stitch provide solutions for SBP expansion, they rely on spatial and spectral scanning, which lead to massive image captures and a low processing speed. To solve the problem, we previously reported a physics-driven deep SBP-expanded framework (Deep SBP+) [J. Opt. Soc. Am. A 40, 833 (2023)JOAOD60740-323210.1364/JOSAA.480920]. Deep SBP+ can reconstruct an image with both high spatial resolution and a large FoV from a low-spatial-resolution image in a large FoV and several high-spatial-resolution images in sub-FoVs. In physics, Deep SBP+ reconstructs the convolution kernel between the low- and high-spatial-resolution images and improves the spatial resolution through deconvolution. But Deep SBP+ needs multiple high-spatial-resolution images in different sub-FoVs, inevitably complicating the operations. To further reduce the image captures, we report an updated version of Deep SBP+ 2.0, which can reconstruct an SBP expanded image from a low-spatial-resolution image in a large FoV and another high-spatial-resolution image in a sub-FoV. Different from Deep SBP+, the assumption that the convolution kernel is a Gaussian distribution is added to Deep SBP+ 2.0 to make the kernel calculation simple and in line with physics. Moreover, improved deep neural networks have been developed to enhance the generation capability. Proven by simulations and experiments, the receptive field is analyzed to prove that a high-spatial-resolution image in the sub-FoV can also guide the generation of the entire FoV. Furthermore, we also discuss the requirement of the sub-FoV image to obtain an SBP-expanded image of high quality. Considering its SBP expansion capability and convenient operation, the updated Deep SBP+ 2.0 can be a useful tool to pursue images with both high spatial resolution and a large FoV.

Funder

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Qinglan Project of Jiangsu Province of China

Wuxi University Research Start-up Fund for Introduced Talents

Publisher

Optica Publishing Group

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3