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High Frame Rate Video Reconstruction and Deblurring Based on Dynamic and Active Pixel Vision Image Sensor.
- Source :
- IEEE Transactions on Circuits & Systems for Video Technology; Aug2021, Vol. 31 Issue 8, p2938-2952, 15p
- Publication Year :
- 2021
-
Abstract
- Active image sensors can only record scenes at low frame rates. The dynamic vision sensor (DVS) can capture high-speed scenes under challenging lighting conditions. However, DVS discards absolute light intensity information. The dynamic and active pixel vision image sensor (DAVIS) can output events and low-frame-rate grayscale images simultaneously. This paper proposes a high frame rate video reconstruction and deblurring algorithm based on events and low-speed blurred image sequences from DAVIS. First, we visualized events as a sequence of event images and performed image denoising process. Then, we used the extended 3D partial recursive search (E-3DPRS) method to generate high-performance motion vector field (MVF) between adjacent denoising event images with low computational complexity. MVF reflects the object motion trajectory with high time resolution. Furthermore, MVF is used as a priori information to restore potentially sharp images, which alleviates the highly ill-posed deblurring process. At last, we reconstructed a high frame rate sharp video based on a sharp image sequence and MVFs. Extensive experiments show that our proposed algorithm outperforms the existing state-of-the-art methods and achieves better average feature similarity and structural similarity. [ABSTRACT FROM AUTHOR]
- Subjects :
- IMAGE denoising
PIXELS
IMAGE sensors
VECTOR fields
OPTICAL flow
IMAGE reconstruction
Subjects
Details
- Language :
- English
- ISSN :
- 10518215
- Volume :
- 31
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Circuits & Systems for Video Technology
- Publication Type :
- Academic Journal
- Accession number :
- 153127913
- Full Text :
- https://doi.org/10.1109/TCSVT.2020.3034148