赵文达   

Associate Professor
Supervisor of Master's Candidates

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Language:English

Paper Publications

Title of Paper:Local binary pattern metric-based multi-focus image fusion

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First Author:Yin, Weiling

Correspondence Author:Zhao, WD (reprint author), Dalian Univ Technol, Sch Informat & Commun Engn, Dalian, Peoples R China.

Co-authors:Zhao, Wenda,You, Di,Wang, Dong

Date of Publication:2019-02-01

Journal:OPTICS AND LASER TECHNOLOGY

Included Journals:SCIE、Scopus

Volume:110

Issue:,SI

Page Number:62-68

ISSN No.:0030-3992

Key Words:Multi-focus image fusion; Local binary pattern; Connected area judgment strategy

Abstract:Multi-focus image fusion is to integrate the partially focused images into one single image which is focused everywhere. Nowadays, it has become an important research topic due to the applications in more and more scientific fields. However, preserving more information of the low-contrast area in the focus area and maintaining the edge information are two challenges for existing approaches. In this paper, we address these two challenges with presenting a simple yet efficient multi-focus fusion method based on local binary pattern (LBP). In our algorithm, we measure the clarity using the LBP metric and construct the initial weight map. And then we use the connected area judgment strategy (CADS) to reduce the noise in the initial map. Afterwards, the two source images are fused together by weighted arranging. The experimental results validate that the proposed algorithm outperforms state-of-the-art image fusion algorithms in both qualitative and quantitative evaluations, especially when dealing with low contrast regions and edge information. (C) 2018 Elsevier Ltd. All rights reserved.

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