Cited 0 time in
Cited 0 time in
Deblurring Low-Light Images with Light Streaks
- Deblurring Low-Light Images with Light Streaks
- Hu, Zhe; Cho, Sunghyun; Wang, Jue; Yang, Ming-Hsuan
- DGIST Authors
- Cho, Sunghyun
- Issue Date
- IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(10), 2329-2341
- Article Type
- Author Keyword
- Image deblurring; light streak; non-uniform blur
- BLIND DECONVOLUTION; KERNEL ESTIMATION; SINGLE IMAGE; MOTION; RESTORATION; SHAKEN; BLUR
- Images acquired in low-light conditions with handheld cameras are often blurry, so steady poses and long exposure time are required to alleviate this problem. Although significant advances have been made in image deblurring, state-of-the-art approaches often fail on low-light images, as a sufficient number of salient features cannot be extracted for blur kernel estimation. On the other hand, light streaks are common phenomena in low-light images that have not been extensively explored in existing approaches. In this work, we propose an algorithm that utilizes light streaks to facilitate deblurring low-light images. The light streaks, which commonly exist in the low-light blurry images, contain rich information regarding camera motion and blur kernels. A method is developed in this work to detect light streaks for kernel estimation. We introduce a non-linear blur model that explicitly takes light streaks and corresponding light sources into account, and pose them as constraints for estimating the blur kernel in an optimization framework. For practical applications, the proposed algorithm is extended to handle images undergoing non-uniform blur. Experimental results show that the proposed algorithm performs favorably against the state-of-the-art methods on deblurring real-world low-light images. © 2018 IEEE.
- IEEE Computer Society
- Related Researcher
Visual computing Lab
컴퓨터그래픽스, 컴퓨터 비전, 영상 처리, 계산사진학
There are no files associated with this item.
- Department of Information and Communication EngineeringVisual Computing Lab1. Journal Articles
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.