Low-light-level image super-resolution reconstruction via deep learning network

Bowen Wang; Yan Zou; Yuhai Li; Wenlin Lu; Chao Zuo

doi:10.1117/12.2606215

24 November 2021 Low-light-level image super-resolution reconstruction via deep learning network

Bowen Wang, Yan Zou, Yuhai Li, Wenlin Lu, Chao Zuo

Proceedings Volume 12065, AOPC 2021: Optical Sensing and Imaging Technology; 1206527 (2021) https://doi.org/10.1117/12.2606215
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

Wide ﬁeld-of-view (FOV) and high-resolution (HR) imaging systems have become indispensable information acquisition equipment in many applications, such as video surveillance, target detection and remotely sensed imagery. However, due to the constraints of spatial sampling and detector processing level, the ability of remote sensing to obtain high spatial resolution is limited, especially in the wide FOV imaging. To solve these problems, we propose a multi-scale feature extraction (MSFE) network to realize super-resolution imaging in a low-light-level (LLL) environment. In order to perform data fusion and information extraction for low resolution (LR) images, the network extracts high-frequency detail information from diﬀerent dimensions by combining the channel attention mechanism module and skip connection module. In this way, redundant low-frequency signals can pass through the network tail-ends, furthermore, the more important high-frequency components calculation can be focused. The qualitative and quantitative analysis results show that the proposed method achieves the most advanced performance compared with other state-of-the-art methods, which shows the superiority of the design framework and the eﬀectiveness of presenting modules.

Citation Download Citation

Bowen Wang, Yan Zou, Yuhai Li, Wenlin Lu, and Chao Zuo "Low-light-level image super-resolution reconstruction via deep learning network", Proc. SPIE 12065, AOPC 2021: Optical Sensing and Imaging Technology, 1206527 (24 November 2021); https://doi.org/10.1117/12.2606215

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KEYWORDS

Feature extraction

Super resolution

Image processing

Image sensors

Imaging systems

Sensors

Image resolution

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