.png){kind=icon}
返回
Blind motion deblurring using multiple images
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jcp.2009.04.022.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recovery of degraded images due to motion blurring is a challenging problem in digital imaging. Most existing techniques on blind deblurring are not capable of removing complex motion blurring from the blurred images of complex structures. One promising approach is to recover the clear image using multiple images captured for the scene. However, in practice it is observed that such a multi-frame approach can recover a high-quality clear image of the scene only after multiple blurred image frames are accurately aligned during pre-processing, which is a very challenging task even with user interactions. In this paper, by exploring the sparsity of the motion blur kernel and the clear image under certain domains, we propose an alternative iteration approach to simultaneously identify the blur kernels of given blurred images and restore a clear image. Our proposed approach is not only robust to image formation noises, but is also robust to the alignment errors among multiple images. A modified version of linearized Bregman iteration is then developed to efficiently solve the resulting minimization problem. Experiments show that our proposed algorithm is capable of accurately estimating the blur kernels of complex camera motions with minimal requirements on the accuracy of image alignment. As a result, our method is capable of automatically recovering a high-quality clear image from multiple blurred images. (C) 2009 Elsevier Inc. All rights reserved.
Keyword:
Blind deconvolution
Tight frame
Motion blur
Image restoration
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.8
论文数:
1.6W
被引数:
7.4W
机构
引用论文
Risk-based testing of imported animals: A case study for bovine tuberculosis in The Netherlands
PREAI
分享收藏Study of irradiation damage induced by He2+ ion irradiation in Ni62Ta38 metallic glass and W metal
OAAI
OAAI分享收藏分享收藏Real-Time Error-Free Reversible Data Hiding in Encrypted Images Using (7, 4) Hamming Code and Most Significant Bit Prediction.png)
SymmetryOAAI
SymmetryIF0
OAAI分享收藏Family Businesses in Spain: Tracks Followed and Outcomes Reached by Those Among the Largest Thousand
PREAI
分享收藏
查看更多内容