標題: Fast Imaging in the Dark by using Convolutional Network
作者: Chiu, Mian Jhong
Wang, Guo-Zhen
Chuang, Jen-Hui
交大名義發表
資訊工程學系
National Chiao Tung University
Department of Computer Science
關鍵字: light-weight convolutional network;low-light imaging
公開日期: 1-Jan-2019
摘要: While fast imaging in low-light condition is crucial for surveillance and robot applications, it is still a formidable challenge to resolve the seemingly inevitable high noise level and low photon count issues. A variety of image enhancement methods such as de-blurring and de-noising have been proposed in the past. However, limitations can still be found in these methods under extreme low-light condition. To overcome such difficulty, a learning-based image enhancement approach is proposed in this paper. In order to support the development of learning-based methodology, we collected a new low-lighting dataset (<0.1 lux) of raw short-exposure (6.67 ms) images, as well as the corresponding long-exposure reference images. Based on such dataset, we develop a light-weight convolutional network structure which is involved with fewer parameters and has lower computation cost compared with a regular-size network. The presented work is expected to make possible the implementation of more advanced edge devices, and their applications.
URI: http://hdl.handle.net/11536/152952
ISBN: 978-1-7281-0397-6
ISSN: 0271-4302
期刊: 2019 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS)
起始頁: 0
結束頁: 0
Appears in Collections:Conferences Paper