Infrared and Visible Image Fusion Objective Evaluation Method

2019 ◽  
pp. 268-279
Author(s):  
Daniel Ledwoń ◽  
Jan Juszczyk ◽  
Ewa Pietka
Keyword(s):  
Image Fusion ◽  
Evaluation Method ◽  
Objective Evaluation ◽  
Visible Image

scholarly journals Infrared and visible image fusion via octave Gaussian pyramid framework

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Yan ◽  
Qun Hao ◽  
Jie Cao ◽  
Rizvi Saad ◽  
Kun Li ◽  
...  
Keyword(s):  
Image Fusion ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Visible Image ◽  
Composite Image ◽  
Multiscale Decomposition ◽  
Gaussian Pyramid ◽  
Fusion Methods ◽  
Scale Spaces ◽  
Fusion Framework

AbstractImage fusion integrates information from multiple images (of the same scene) to generate a (more informative) composite image suitable for human and computer vision perception. The method based on multiscale decomposition is one of the commonly fusion methods. In this study, a new fusion framework based on the octave Gaussian pyramid principle is proposed. In comparison with conventional multiscale decomposition, the proposed octave Gaussian pyramid framework retrieves more information by decomposing an image into two scale spaces (octave and interval spaces). Different from traditional multiscale decomposition with one set of detail and base layers, the proposed method decomposes an image into multiple sets of detail and base layers, and it efficiently retains high- and low-frequency information from the original image. The qualitative and quantitative comparison with five existing methods (on publicly available image databases) demonstrate that the proposed method has better visual effects and scores the highest in objective evaluation.

scholarly journals Fusion of Infrared and Visible Images Using Fast Global Smoothing Decomposition and Target-Enhanced Parallel Gaussian Fuzzy Logic

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 40
Author(s):  
Chaowei Duan ◽  
Changda Xing ◽  
Yiliu Liu ◽  
Zhisheng Wang
Keyword(s):  
Fuzzy Logic ◽  
Image Fusion ◽  
Visual Saliency ◽  
Fusion Rule ◽  
Objective Evaluation ◽  
Saliency Map ◽  
Visible Image ◽  
Structure Information ◽  
Visible Images ◽  
Image Pairs

As a powerful technique to merge complementary information of original images, infrared (IR) and visible image fusion approaches are widely used in surveillance, target detecting, tracking, and biological recognition, etc. In this paper, an efficient IR and visible image fusion method is proposed to simultaneously enhance the significant targets/regions in all source images and preserve rich background details in visible images. The multi-scale representation based on the fast global smoother is firstly used to decompose source images into the base and detail layers, aiming to extract the salient structure information and suppress the halos around the edges. Then, a target-enhanced parallel Gaussian fuzzy logic-based fusion rule is proposed to merge the base layers, which can avoid the brightness loss and highlight significant targets/regions. In addition, the visual saliency map-based fusion rule is designed to merge the detail layers with the purpose of obtaining rich details. Finally, the fused image is reconstructed. Extensive experiments are conducted on 21 image pairs and a Nato-camp sequence (32 image pairs) to verify the effectiveness and superiority of the proposed method. Compared with several state-of-the-art methods, experimental results demonstrate that the proposed method can achieve more competitive or superior performances according to both the visual results and objective evaluation.

Infrared and Visible Image Fusion Based on Deep Decomposition Network and Saliency Analysis

2021 ◽  
pp. 1-1
Author(s):  
Lihua Jian ◽  
Rakiba Rayhana ◽  
Ling Ma ◽  
Shaowu Wu ◽  
Zheng Liu ◽  
...  
Keyword(s):  
Image Fusion ◽  
Visible Image ◽  
Saliency Analysis

scholarly journals Blur Regional Features Based Infrared And Visible Image Fusion Using An Improved C3Net Model

2021 ◽  
Vol 1820 (1) ◽  
pp. 012169
Author(s):  
Zhao Xu ◽  
Gang Liu ◽  
Li Li Tang ◽  
Yan Hui Li
Keyword(s):  
Image Fusion ◽  
Visible Image ◽  
Regional Features

Multi-exposure X-ray image fusion quality evaluation based on CSF and gradient amplitude similarity

2021 ◽  
pp. 1-13
Author(s):  
Yanjie Qi ◽  
Zehui Yang ◽  
Lin Kang
Keyword(s):  
Image Fusion ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Dynamic Range ◽  
Reference Image ◽  
Subjective Perception ◽  
Steel Component ◽  
Imaging Device ◽  
X Ray ◽  
Gradient Amplitude

Due to the limitation of dynamic range of the imaging device, the fixed-voltage X-ray images often produce overexposed or underexposed regions. Some structure information of the composite steel component is lost. This problem can be solved by fusing the multi-exposure X-ray images taken by using different voltages in order to produce images with more detailed structures or information. Due to the lack of research on multi-exposure X-ray image fusion technology, there is no evaluation method specially for multi-exposure X-ray image fusion. For the multi-exposure X-ray fusion images obtained by different fusion algorithms may have problems such as the detail loss and structure disorder. To address these problems, this study proposes a new multi-exposure X-ray image fusion quality evaluation method based on contrast sensitivity function (CSF) and gradient amplitude similarity. First, with the idea of information fusion, multiple reference images are fused into a new reference image. Next, the gradient amplitude similarity between the new reference image and the test image is calculated. Then, the whole evaluation value can be obtained by weighting CSF. In the experiments of MEF Database, the SROCC of the proposed algorithm is about 0.8914, and the PLCC is about 0.9287, which shows that the proposed algorithm is more consistent with subjective perception in MEF Database. Thus, this study demonstrates a new objective evaluation method, which generates the results that are consistent with the subjective feelings of human eyes.

scholarly journals A multi-objective evaluation method based on connection numbers theory of hazardous chemical accidents emergency medical rescue capability

2019 ◽  
Vol 27 (3) ◽  
pp. 125-133
Author(s):  
Yapeng Wang ◽  
Jinguo Zhang ◽  
Yundou Wang ◽  
Xiaowen Xiong ◽  
Xin Zhao
Keyword(s):  
Index System ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Objective Evaluation ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Chemical Accidents ◽  
Hazardous Chemical ◽  
Emergency Medical ◽  
Partial Connection

Background: An objective, comprehensive and scientific evaluation of emergency medical rescue capability (EMRC) is of great realistic significance in assisting the health administrative department to grasp the overall response capability of all emergency medical rescue teams, enabling each team to have a full understanding of its own strengths and weakness and improve itself accordingly. At present, the research on the evaluation of EMRC in Hazardous Chemicals Accidents (HCA) is not systematic and in-depth, and the existing research results also have some shortcomings, such as, the lack of strong theoretical support for the evaluation index system, the relatively single function of evaluation methods, and so on. Objectives: The objective of this article is to research the evaluation index system and a new evaluation method of EMRC in HCA to overcome the above shortcomings. Methods: It establishes an emergency medical rescue capability model by employing the competency model and then constructs the evaluation index system on the basis of the analysis of all the factors of emergency medical rescue capability in hazardous chemical accidents and sets up an evaluation model based on the theory of connection numbers and partial connection numbers. It determines the competence ranking of several emergency medical rescue teams and the competence state of an individual emergency medical rescue team by calculating the connection principal value, and it also predicts how the emergency medical rescue capability will develop based on the values of partial connection numbers. Results: The example shows that the calculation process of this model is relatively simple, and its assessment results are objective and authentic, and moreover, its multi-functions can make up for the deficiency of the simplified function of other evaluation models. Conclusion: This method is scientific and rational to some extent and can provide reference for evaluation problems of the same kind.

scholarly journals Airborne Infrared and Visible Image Fusion Combined with Region Segmentation

Sensors ◽  
2017 ◽  
Vol 17 (5) ◽  
pp. 1127 ◽  
Author(s):  
Yujia Zuo ◽  
Jinghong Liu ◽  
Guanbing Bai ◽  
Xuan Wang ◽  
Mingchao Sun
Keyword(s):  
Image Fusion ◽  
Visible Image ◽  
Region Segmentation
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