.png){kind=icon}
返回
Improving defocus blur measures using robust regularization
.png){kind=icon}
OA
AI
DOI：10.1016/j.icte.2021.11.001.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a robust regularization scheme for the enhancement of initial blur map in single image blur detection. The proposed technique considers the structural differences between guidance and initial blur map. Specifically, we propose to improve the initial blur map by optimizing a nonconvex energy function that jointly leverages structural information from guidance and blur map. Nonconvex problem is solved by majorize-minimize algorithm and an improved blur map is obtained that is adequately smooth and has better edge-preserving properties. Ultimately, this results in high-quality blur segmentation. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.
Keyword:
Blur measure
Blur segmentation
Robust regularization
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:
4.2
论文数:
998
被引数:
2.5K
机构
暂无机构信息
引用论文
Prevalence of aortic valve abnormalities in the elderly: An echocardiographic study of a random population sample老年人主动脉瓣异常的患病率: 随机人群样本的超声心动图研究
PREAI
分享收藏Systemic or mucosal administration of immunostimulatory DNA inhibits early and late phases of murine allergic conjunctivitis.全身或黏膜给予免疫刺激DNA可抑制小鼠过敏性结膜炎的早期和晚期阶段。.png)
IF0
PREAI
分享收藏Crystal Structure of Human FtsJ homolog 2 (E.coli) protein in complex with S-adenosylmethionine
IF0
PREAI
分享收藏
查看更多内容