[1]贺国旗[],陈向奎[],韩泉叶[],等. 一种自动提高图像信噪比的方法[J].计算机技术与发展,2015,25(12):60-63.
　HE Guo-qi[],CHEN Xiang-kui[],HAN Quan-ye[],et al. A Method of Automatically Improving SNR of Image[J].,2015,25(12):60-63.
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 一种自动提高图像信噪比的方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年12期
页码:
60-63
栏目:
智能、算法、系统工程
出版日期:
2015-12-10

文章信息/Info

Title:
 A Method of Automatically Improving SNR of Image
文章编号:
1673-629X（2015)12-0060-04
作者:
 贺国旗[1] ; 陈向奎[2] ; 韩泉叶[1] ; 兰新哲[1]
1. 陕西广播电视大学 资源建设与现代教育技术中心；2.洛阳师范学院 信息技术学院
Author(s):
 HE Guo-qi[1] ; CHEN Xiang-kui[2];  HAN Quan-ye[1];  LAN Xin-zhe[1]
关键词:
 ; 信噪比; 图像处理; 视觉效果; 失真; 振幅
Keywords:
 ; signal to noise ratio; image processing; visual effect; distortion; amplitude
分类号:
TP301
文献标志码:
A
摘要:
 信噪比是衡量图像处理效果的一种客观有效的方法,是图像识别的重要依据之一,但是信噪比衡量的结果往往存在与人的视觉效果不一致的现象. 文中针对原有的信噪比计算公式存在使有的图像与原图像非常相像而得到信噪比却非常低的问题,通过对原图像和结果图像进行统计分析,根据原图像和结果图像的内容自动地得到一个比例系数. 如果对结果图像的每一个像素乘以该系数,就可以得到信噪比比较高的图像;也可以通过改变传统的信噪比计算公式,对结果图像使用新的信噪比计算公式进行计算,从而得到一个比较高的信噪比,且对任意图像使用新的信噪比计算公式得到绝不低于原有公式计算的结果. 文中通过理论分析和实验结果说明提高了所提算法的有效性.
Abstract:
 The signal-to-noise ratio is an effective way of measuring the effect of image processing and one of significant foundation of image identification. However,the SNR measure result often leads to inconsistent phenomenon with the visual effect. Aiming at the issue which the original calculation formula of the SNR makes high similarity between some images and original image that results in low SNR,a proportional coefficient is obtained automatically through analyzing the original and the results image. Each pixel of the results im-age multiplied by the coefficient,can get an image with high SNR,also can change the traditional SNR calculation formula which calcu-lates to results image by using new calculation formula of the SNR to get a higher signal-to-noise ratio and will get a higher calculation result by using new calculation formula of the SNR than original’s. The theory analysis and experiment results demonstrate that the effec-tiveness of algorithm proposed in this paper is improved.

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更新日期/Last Update: 2016-01-28