The Analysis and Discussion of Infrared Image Metrics

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.1559 ◽

2014 ◽

Vol 602-605 ◽

pp. 1559-1562

Author(s):

Xin Zheng ◽

Bo Tian ◽

Yan Xing

Keyword(s):

Image Quality ◽

Quality Evaluation ◽

Infrared Image ◽

Experimental Results ◽

Current Image ◽

Image Quality Evaluation ◽

Image Metrics

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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A Multi-Criteria Image Quality Evaluation Scheme

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.284-287.2975 ◽

2013 ◽

Vol 284-287 ◽

pp. 2975-2979

Author(s):

Yen Ching Chang ◽

Chun Ming Chang ◽

Liang Hwa Chen ◽

Tung Jung Chan

Keyword(s):

Image Quality ◽

Contrast Enhancement ◽

Quality Evaluation ◽

Experimental Results ◽

Human Vision ◽

Effective Mechanism ◽

Image Quality Evaluation ◽

Evaluation Scheme ◽

Grey Relational Grade ◽

Grey Relational

It is difficult to objectively and quantitatively judge image quality by a single criterion, such as contrast. In general, excessive contrast enhancement easily leads to a loss of image quality. Thus, it easily gives a wrong evaluation to rank image quality according to contrast values. In order to achieve a consistent result with human vision perception, balancing multi-criteria will be a feasible approach. Therefore, we propose a multi-criteria image quality evaluation scheme for ranking seven existing contrast enhancement methods. The scheme applies four criteria to a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd). Experimental results show that our proposed CGRGd do provides a very effective mechanism to choose the best method for a specific purpose.

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Image quality evaluation of infrared image

10.1117/12.576795 ◽

2005 ◽

Author(s):

Chun-mei Xu ◽

Gang Li ◽

Wengang Hu ◽

Wei Zhang

Keyword(s):

Image Quality ◽

Quality Evaluation ◽

Infrared Image ◽

Image Quality Evaluation

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

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.570 ◽

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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