ArticleSensors (Basel, Switzerland)2016
Robust Image Restoration for Motion Blur of Image Sensors.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Improved Ultrasound Microvessel Imaging Using Deconvolution with Total Variation Regularization.Ultrasound in medicine & biology · 2021Article
- Image Deblurring Using Multi-Stream Bottom-Top-Bottom Attention Network and Global Information-Based Fusion and Reconstruction Network.Sensors (Basel, Switzerland) · 2020Article
- Combining Motion Compensation with Spatiotemporal Constraint for Video Deblurring.Sensors (Basel, Switzerland) · 2018Article
- Motion-Blur-Free High-Speed Video Shooting Using a Resonant Mirror.Sensors (Basel, Switzerland) · 2017Article
- Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring.Sensors (Basel, Switzerland) · 2017Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with these problems, we present a robust image restoration algorithm for motion blur of general image sensors in this paper. Firstly, we propose a self-adaptive structure extraction method based on the total variation (TV) to separate the reliable structures from textures and small details of a blurred image which may damage the kernel estimation and interim latent image restoration. Secondly, we combine the reliable structures with priors of the blur kernel, such as sparsity and continuity, by a two-step method with which noise can be removed during iterations of the estimation to improve the precision of the estimated blur kernel. Finally, we use a MR-based Wiener filter as the non-blind deconvolution algorithm to restore the final latent image. Experimental results demonstrate that our algorithm can restore large blur images with rich, small details effectively.
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Registered trials
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