Event-Guided Image Super-Resolution Reconstruction

doi:10.3390/s23042155

CIOMP OpenIR

	Event-Guided Image Super-Resolution Reconstruction
	G. Guo; Y. Feng; H. Lv; Y. Zhao; H. Liu and G. Bi
	2023
发表期刊	Sensors
ISSN	14248220
卷号	23 期号:4
摘要	The event camera efficiently detects scene radiance changes and produces an asynchronous event stream with low latency, high dynamic range (HDR), high temporal resolution, and low power consumption. However, the large output data caused by the asynchronous imaging mechanism makes the increase in spatial resolution of the event camera limited. In this paper, we propose a novel event camera super-resolution (SR) network (EFSR-Net) based on a deep learning approach to address the problems of low spatial resolution and poor visualization of event cameras. The network model is capable of reconstructing high-resolution (HR) intensity images using event streams and active sensor pixel (APS) frame information. We design the coupled response blocks (CRB) in the network that are able of fusing the feature information of both data to achieve the recovery of detailed textures in the shadows of real images. We demonstrate that our method is able to reconstruct high-resolution intensity images with more details and less blurring in synthetic and real datasets, respectively. The proposed EFSR-Net can improve the peak signal-to-noise ratio (PSNR) metric by 1–2 dB compared with state-of-the-art methods. © 2023 by the authors.
DOI	10.3390/s23042155
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收录类别	sci ; ei
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67494
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	G. Guo,Y. Feng,H. Lv,et al. Event-Guided Image Super-Resolution Reconstruction[J]. Sensors,2023,23(4).
APA	G. Guo,Y. Feng,H. Lv,Y. Zhao,&H. Liu and G. Bi.(2023).Event-Guided Image Super-Resolution Reconstruction.Sensors,23(4).
MLA	G. Guo,et al."Event-Guided Image Super-Resolution Reconstruction".Sensors 23.4(2023).

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