scholarly journals Image Fusion Algorithm Selection Based on Fusion Validity Distribution Combination of Difference Features

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1752
Author(s):  
Linna Ji ◽  
Fengbao Yang ◽  
Xiaoming Guo
Keyword(s):  
Image Fusion ◽  
Combination Method ◽  
Infrared Images ◽  
Dual Mode ◽  
Fusion Algorithm ◽  
Algorithm Selection ◽  
Fuzzy Operator ◽  
Features Fusion ◽  
Feature Score ◽  
Selection Of

Aiming at addressing the problem whereby existing image fusion models cannot reflect the demand of diverse attributes (e.g., type or amplitude) of difference features on algorithms, leading to poor or invalid fusion effect, this paper puts forward the construction and combination of difference features fusion validity distribution based on intuition-possible sets to deal with the selection of algorithms with better fusion effect in dual mode infrared images. Firstly, the distances of the amplitudes of difference features between fused images and source images are calculated. The distances can be divided into three levels according to the fusion result of each algorithm, which are regarded as intuition-possible sets of fusion validity of difference features, and a novel construction method of fusion validity distribution based on intuition-possible sets is proposed. Secondly, in view of multiple amplitude intervals of each difference feature, this paper proposes a distribution combination method based on intuition-possible set ordering. Difference feature score results are aggregated by a fuzzy operator. Joint drop shadows of difference feature score results are obtained. Finally, the experimental results indicate that our proposed method can achieve optimal selection of algorithms that has relatively better effect on the fusion of difference features according to the varied feature amplitudes.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Infrared Image Fusion Algorithm Selection Based on Joint Drop Shadow of Possibility Distributions

2021 ◽  
Vol 50 (4) ◽  
pp. 228-240
Author(s):  
吉琳娜 Linna JI ◽  
郭小铭 Xiaoming GUO ◽  
杨风暴 Fengbao YANG ◽  
张雅玲 Yaling ZHANG
Keyword(s):  
Image Fusion ◽  
Infrared Image ◽  
Fusion Algorithm ◽  
Algorithm Selection ◽  
Possibility Distributions

Optimal multi-focus contourlet-based image fusion algorithm selection

2016 ◽  
Author(s):  
Adam Lutz ◽  
Michael Giansiracusa ◽  
Neal Messer ◽  
Soundararajan Ezekiel ◽  
Erik Blasch ◽  
...  
Keyword(s):  
Image Fusion ◽  
Fusion Algorithm ◽  
Algorithm Selection

Fuzzy Transform-Based Fusion of Multiple Images

2017 ◽  
Vol 17 (02) ◽  
pp. 1750008 ◽  
Author(s):  
Meenu Manchanda ◽  
Rajiv Sharma
Keyword(s):  
Image Fusion ◽  
State Of The Art ◽  
Fusion Rule ◽  
Infrared Images ◽  
Recent Past ◽  
Fuzzy Transform ◽  
Fusion Algorithm ◽  
Multiple Images ◽  
Fused Image ◽  
Combine Information

Extensive development has taken place in the field of image fusion and various algorithms of image fusion have attracted the attention of many researchers in the recent past. Various algorithms of image fusion are used to combine information from multiple source images into a single fused image. In this paper, fusion of multiple images using fuzzy transform is proposed. Images to be fused are initially decomposed into same size blocks. These blocks are then fuzzy transformed and fused using maxima coefficient value-based fusion rule. Finally, the fused image is obtained by performing inverse fuzzy transform. The performance of the proposed algorithm is evaluated by performing experiments on multifocus, medical and visible/infrared images. Further, the performance of the proposed algorithm is compared with the state-of-the-art image fusion algorithms, both subjectively and objectively. Experimental results and comparative study show that the proposed fusion algorithm fuses the multiple images effectively and produces better fusion results for medical and visible/infrared images.

scholarly journals Multi-sensor Image Fusion Algorithm Based on Multiresolution Analysis

2018 ◽  
Vol 14 (06) ◽  
pp. 44 ◽  
Author(s):  
Zhi-guo Wang ◽  
Wei Wang ◽  
Baolin Su
Keyword(s):  
Image Fusion ◽  
Quality Evaluation ◽  
Color Image ◽  
Infrared Image ◽  
Principal Component ◽  
Infrared Images ◽  
Fusion Algorithm ◽  
Time Intervals ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

<p class="0abstract">To solve the fusion problem of visible and infrared images, based on image fusion algorithm such as region fusion, wavelet transform, spatial frequency, Laplasse Pyramid and principal component analysis, the quality evaluation index of image fusion was defined. Then, curve-let transform was used to replace the wavelet change to express the superiority of the curve. It integrated the intensity channel and the infrared image, and then transformed it to the original space to get the fused color image. Finally, two groups of images at different time intervals were used to carry out experiments, and the images obtained after fusion were compared with the images obtained by the first five algorithms, and the quality was evaluated. The experiment showed that the image fusion algorithm based on curve-let transform had good performance, and it can well integrate the information of visible and infrared images. It is concluded that the image fusion algorithm based on curve-let change is a feasible multi-sensor image fusion algorithm based on multi-resolution analysis. </p>

scholarly journals Thermal Fault Diagnosis of Electrical Equipment in Substations Based on Image Fusion

2021 ◽  
Vol 38 (4) ◽  
pp. 1095-1102
Author(s):  
Mingshu Lu ◽  
Haiting Liu ◽  
Xipeng Yuan
Keyword(s):  
Fault Diagnosis ◽  
Image Fusion ◽  
Infrared Image ◽  
Electrical Equipment ◽  
True Temperature ◽  
Infrared Images ◽  
Fusion Algorithm ◽  
Infrared Thermal Imaging ◽  
Proposed Model ◽  
Target Extraction

Infrared thermal imaging can diagnose whether there are faults in electrical equipment during non-stop operation. However, the existing thermal fault diagnosis algorithms fail to consider an important fact: the infrared image of a single band cannot fully reflect the true temperature information of the target. As a result, these algorithms fail to achieve desired effects on target extraction from low-quality infrared images of electrical equipment. To solve the problem, this paper explores the thermal fault diagnosis of electrical equipment in substations based on image fusion. Specifically, a registration and fusion algorithm was proposed for infrared images of electrical equipment in substations; a segmentation and recognition model was established based on mask region-based convolutional neural network (R-CNN) for the said images; the steps of thermal fault diagnosis were detailed for electrical equipment in substations. The proposed model was proved effective through experiments.

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