Multi-source image fusion algorithm based on fast weighted guided filter

被引：5

作者：

Wang Jian ^{[1
,2
]}

Yang Ke ^{[1
]}

Ren Ping ^{[1
]}

Qin Chunxia ^{[1
]}

Zhang Xiufei ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Elect & Informat Engn, Xian 710072, Shaanxi, Peoples R China

[2] Northwestern Polytech Univ, Inst 365, Xian 710065, Shaanxi, Peoples R China

来源：

JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2019年 / 30卷 / 05期

基金：

中国国家自然科学基金;

关键词：

fast guided filter; image fusion; visual feature; decision map; QUALITY ASSESSMENT;

D O I：

10.21629/JSEE.2019.05.02

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In last few years, guided image fusion algorithms become more and more popular. However, the current algorithms cannot solve the halo artifacts. We propose an image fusion algorithm based on fast weighted guided filter. Firstly, the source images are separated into a series of high and low frequency components. Secondly, three visual features of the source image are extracted to construct a decision graph model. Thirdly, a fast weighted guided filter is raised to optimize the result obtained in the previous step and reduce the time complexity by considering the correlation among neighboring pixels. Finally, the image obtained in the previous step is combined with the weight map to realize the image fusion. The proposed algorithm is applied to multi-focus, visible-infrared and multi-modal image respectively and the final results show that the algorithm effectively solves the halo artifacts of the merged images with higher efficiency, and is better than the traditional method considering subjective visual consequent and objective evaluation.

引用

页码：831 / 840

页数：10

共 26 条

[1]

[Anonymous], 2000, P 3 INT C IM FUS

[2] Dual hybrid medical watermarking using walsh-slantlet transform [J].

Bamal, Roopam ;

Kasana, Singara Singh .

MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (13) :17899-17927

[3] A review of remote sensing image fusion methods [J].

Ghassemian, Hassan .

INFORMATION FUSION, 2016, 32 :75-89

[4] Objective Quality Assessment for Multiexposure Multifocus Image Fusion [J].

Hassen, Rania ;

Wang, Zhou ;

Salama, Magdy M. A. .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 24 (09) :2712-2724

[5] Guided Image Filtering [J].

He, Kaiming ;

Sun, Jian ;

Tang, Xiaoou .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (06) :1397-1409

[6] Analysis of sagittal alignment parameters following anterior cervical hybrid decompression and fusion of multilevel cervical Spondylotic myelopathy [J].

Huang, Yuming ;

Lan, Zhibin ;

Xu, Weihong .

BMC MUSCULOSKELETAL DISORDERS, 2019, 20 (1)

[7] Adaptive fusion method of visible light and infrared images based on non-subsampled shearlet transform and fast non-negative matrix factorization [J].

Kong, Weiwei ;

Lei, Yang ;

Zhao, Huaixun .

INFRARED PHYSICS & TECHNOLOGY, 2014, 67 :161-172

[8] Gradient Domain Guided Image Filtering [J].

Kou, Fei ;

Chen, Weihai ;

Wen, Changyun ;

Li, Zhengguo .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 24 (11) :4528-4539

[9] Pixel- and region-based image fusion with complex wavelets [J].

Lewis, John J. ;

O'Callaghan, Robert J. ;

Nikolov, Stavri G. ;

Bull, David R. ;

Canagarajah, Nishan .

INFORMATION FUSION, 2007, 8 (02) :119-130

[10] Image Fusion with Guided Filtering [J].

Li, Shutao ;

Kang, Xudong ;

Hu, Jianwen .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (07) :2864-2875

← 1 2 3 →