A region-based image fusion algorithm for detecting trees in forests

被引:0
作者
Yu, Zheng [1 ]
Yan, Lei [1 ]
Han, Ning [1 ]
机构
[1] School of Technology, Beijing Forestry University, Beijing
关键词
Fuzzy logic; Live wire segmentation; NSCT; Region based ımage fusion; Tree detection;
D O I
10.2174/1874110X01408010540
中图分类号
学科分类号
摘要
Multi-sensor image fusion has been widely used in many areas. In this paper, a region-based method using NSCT and fuzzy logic is proposed to enhance trees’ contour and enrich the information in images. Firstly, the required source images are segmented, which are then decomposed using the NSCT transform. In low frequency domain, the fuzzy fusion method is used. And in high frequency domain, a region-based rule is proposed to highlight the objects’ detail within images. Finally, the fused images are obtained by an inverse NSCT transform. Nine pieces of objective criteria and computation time are adopted to evaluate the fusion result. Moreover 30 groups of collected images are utilized to prove the robustness of the proposed method. The results show that the algorithm could provide fused images which have a higher visual effect, combine more information and consume less time. Furthermore, this process could better capture the contour and texture of the trees. © Yu et al.
引用
收藏
页码:540 / 545
页数:5
相关论文
共 50 条
[41]   An algorithm for multi-sensor image fusion using maximum a posteriori and nonsubsampled contourlet transform [J].
Anandhi, D. ;
Valli, S. .
COMPUTERS & ELECTRICAL ENGINEERING, 2018, 65 :139-152
[42]   A Color Multi-Focus Image Fusion Algorithm with Nonsubsampled Contourlet Transform in Space Domain [J].
Wei, Sun ;
Zheng, Xiang ;
Xu Siyu .
2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 3, 2010, :32-35
[43]   Feature Extraction Using DPSO for Medical Image Fusion Based on NSCT [J].
Mahima ;
Padmavathi, N. B. ;
Karki, Maya V. .
2017 2ND IEEE INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ELECTRONICS, INFORMATION & COMMUNICATION TECHNOLOGY (RTEICT), 2017, :265-269
[44]   A novel image fusion approach based on wavelet transform and fuzzy logic [J].
Li, Tao ;
Liu, Jian ;
Wang, Zhicheng .
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2006, 4 (04) :617-626
[45]   Enhanced Robotic Vision System Based on Deep Learning and Image Fusion [J].
Alabdulkreem, A. ;
Sedik, Ahmed ;
Algarni, Abeer D. ;
El Banby, Ghada M. ;
Abd El-Samie, Fathi E. ;
Soliman, Naglaa F. .
CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 73 (01) :1845-1861
[46]   IFSepR: A General Framework for Image Fusion Based on Separate Representation Learning [J].
Luo, Xiaoqing ;
Gao, Yuanhao ;
Wang, Anqi ;
Zhang, Zhancheng ;
Wu, Xiao-Jun .
IEEE TRANSACTIONS ON MULTIMEDIA, 2023, 25 :608-623
[47]   Neutrosophic-CNN-based image and text fusion for multimodal classification [J].
Wajid, Mohd Anas ;
Zafar, Aasim ;
Terashima-Marin, Hugo ;
Saif Wajid, Mohammad .
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 45 (01) :1039-1055
[48]   Vision Model based Image Fusion in Nonsubsampled Contourlet Transform Domain [J].
Hu, Yanxiang ;
Zhang, Rui .
PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, :1270-1275
[49]   Remote Sensing Image Fusion Based on Fuzzy Logic and Salience Measure [J].
Yang, Yong ;
Lu, Hangyuan ;
Huang, Shuying ;
Tu, Wei .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (11) :1943-1947
[50]   Infrared and Visible Image Fusion Method Based on NSST and Guided Filtering [J].
Zhou Jie ;
Li Wenjuan ;
Zhang Peng ;
Luo Jun ;
Li Sijing ;
Zhao Jiong .
ICOSM 2020: OPTOELECTRONIC SCIENCE AND MATERIALS, 2020, 11606