Image quality evaluation method based on structural similarity

2007 ◽  
Author(s):  
Li Zhu ◽  
Guoyou Wang ◽  
Ying Liu
Keyword(s):  
Image Quality ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Structural Similarity ◽  
Image Quality Evaluation

Quantitative image quality evaluation method for UDC (Under Display Camera)

2021 ◽  
Keyword(s):  
Image Quality ◽  
International Symposium ◽  
System Performance ◽  
Quality Evaluation ◽  
Fast Track ◽  
Evaluation Method ◽  
Image Quality Evaluation ◽  
Electronic Imaging ◽  
Quantitative Image

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

Image Quality Evaluation of Panoramic Camera Steropair based on Structural Similarity

2014 ◽  
Vol 51 (7) ◽  
pp. 071004
Author(s):  
高露露 Gao Lulu ◽  
刘建军 Liu Jianjun ◽  
任鑫 Ren Xin ◽  
李春来 Li Chunlai
Keyword(s):  
Image Quality ◽  
Quality Evaluation ◽  
Structural Similarity ◽  
Image Quality Evaluation

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
Keyword(s):  
Image Quality ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Infrared Image ◽  
Low Frequency ◽  
Fusion Rule ◽  
Source Image ◽  
Fusion Algorithm ◽  
Information Quantity ◽  
Image Quality Evaluation

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.

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