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Guided image filtering in shape-from-focus: A comparative analysis

delete2021-03-01
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PRE
AI
U
Usman Ali
I
Ik Hyun Lee
M
Muhammad Tariq Mahmood *
DOI:10.1016/j.patcog.2020.107670delete
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摘要

摘要

En 中文
Mostly, shape from focus (SFF) methods do not consider any prior to extend the accuracy of the depth map. Ultimately, even the improved depth map might lack the accurate structure of the object. While reviewing the guided filters, it has been observed that SFF has not been considered as an application. In this study, we not only suggest to apply guided filtering for depth enhancement but also provide a comparative analysis of recently proposed guided filters for SFF framework in a systematic way. In addition, a set of potential guidance maps has been suggested and the performance of these guidance maps has been evaluated. The improved performance of guided filters has been ranked against the depth maps of synthetic and real image sequences where the corresponding scenes have diverse range of geometrical complexities. It has been observed that guided image filtering is effective in improving the initial depth maps in SFF. (C) 2020 Elsevier Ltd. All rights reserved.
Keyword:
Shape from focus (SFF)
Focus measure
Guided image filtering
Depth map
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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

Pattern Recognition 封面图
Pattern Recognition
IF:
7.6
论文数:
1.3W
被引数:
4.5W

机构

K
Korea Polytechnic University
学者数:
403
论文数: 434
被引数: 350
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