Fusion Algorithm of Infrared and TV Image Based on Image Quality Evaluation Method

2014 ◽  
Vol 513-517 ◽  
pp. 570-574
Author(s):  
Bin Zhou ◽  
Xiao Hui Luo

The main method of Infrared and TV image fusion is based on image transform and fusion rule selection. The study implies that the information quantity of Infrared and TV image has significant effect on the result of fusion. This paper proposes one fusion algorithm of infrared and TV image based on image quality evaluation method. The basic idea of the algorithm is that the whole image or the image areas which contains better quantity of information play a leading role in the fusion process. Firstly, algorithm performs the global quality evaluation of infrared image and TV image, and then selects the corresponding fusion strategy according to the quantity of information. The source image has been divided into the high frequency coefficients and low-frequency coefficients using wavelet transform. Second, algorithm selects the rule of coefficients fusion based on the relative image quality of local regions of the image. The algorithm of this paper avoids the interference of low quality image, makes full use of the area of higher information content and achieves the favorable consistency of the fused image. Experiments demonstrate the effectiveness of the algorithm.

2013 ◽  
Author(s):  
Song Yue ◽  
Tingting Ren ◽  
Chengsheng Wang ◽  
Bo Lei ◽  
Zhijie Zhang

Fast track article for IS&T International Symposium on Electronic Imaging 2021: Image Quality and System Performance XVIII proceedings.


2005 ◽  
Author(s):  
Chun-mei Xu ◽  
Gang Li ◽  
Wengang Hu ◽  
Wei Zhang

2014 ◽  
Vol 602-605 ◽  
pp. 1559-1562
Author(s):  
Xin Zheng ◽  
Bo Tian ◽  
Yan Xing

Aiming at the theory of infrared image quality evaluation, current image metrics are concluded and summarized in this paper. Meanwhile, 2 groups of contrast experiments are designed to get the values of 3 kinds of typical metrics (SV, TSSIM and TTSIM). Furthermore, the deficiencies of the current typical image metrics are analyzed in the light of the experimental results. What's more, the bottleneck and challenge of the infrared image quality evaluation are foreseen and the probable solutions are briefly discussed based on the results.


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