Multi-focus image fusion algorithm based on focused region extraction

详细信息    查看全文

• 作者：Baohua Zhang^a ; ^bAuthor Vitae ; Xiaoqi Lu^a ; ^b ; ^{zbh_wj2004@imust.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Haiquan Pei^bAuthor Vitae ; He Liu^bAuthor Vitae ; Ying Zhao^bAuthor Vitae ; Wentao Zhou^bAuthor Vitae
• 关键词：Multi-focus image fusion ; Saliency analysis ; Watershed algorithm ; Shearlet transform
• 刊名：Neurocomputing
• 出版年：2016
• 出版时间：22 January 2016
• 年：2016
• 卷：174
• 期：part_PB
• 页码：733-748
• 全文大小：12929 K

文摘

Detection of the focused region is the key issue of the multi-focus image fusion algorithm. The blurred boundary of the focused region increases the difficulty of identifying focused regions accurately. According to the principles that the focused region of the source image should be directly fused as much as possible, this paper proposes a novel multi-focus image fusion algorithm based on saliency analysis, Graph-based visual saliency (GBVS) algorithm is used to locate the focused region in the source image. Then, watershed and morphological methods are used to get the enclosed region of the saliency map and remove the pseudo-focus region. Finally, the focused region is fused directly and the remaining regions are fused based on the Shearlet transform. Experiments demonstrate that the proposed approach can accurately extract the focused region, the fused image preserves more features and it is superior to traditional methods in subjective and objective evaluations.