基于相位一致性的结构相似度图像融合质量评价方法

doi:10.3969/j.issn.1000-1093.2013.12.005

兵工学报 ›› 2013, Vol. 34 ›› Issue (12): 1514-1520.doi: 10.3969/j.issn.1000-1093.2013.12.005

基于相位一致性的结构相似度图像融合质量评价方法

张玉珍^1，2，3，孙佳嵩^1，2，陈钱^1，2，顾国华^1，2，冯世杰^1，2，

曾祥通^1，2，喻士领^1，2

收稿日期:2013-08-15 修回日期:2013-08-15 上线日期:2014-03-04
通讯作者: 张玉珍 E-mail:olindazh@163.com
作者简介:张玉珍（1973—），女，讲师，硕士生导师

Image Fusion Quality Assessment Method Based on Phase Congruency and Structural Similarity

ZHANG Yu-zhen^1，2，3， SUN Jia-song^1，2， CHEN Qian^1,2, GU Guo-hua^1,2, FENG Shi-jie^1，2，

(1.School of Electronic Engineering and Optoelectronic Technology，Nanjing University of Science and Technology，Nanjing 210094，Jiangsu，China； 2.Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense，Nanjing 210094，Jiangsu，China； 3.Key Laboratory of Photoelectronic Imaging Technology and System，Ministry of Education of China，Beijing Institute of Technology，Beijing 100081，China）

Received:2013-08-15 Revised:2013-08-15 Online:2014-03-04
Contact: ZHANG Yu-zhen E-mail:olindazh@163.com

摘要/Abstract

摘要： 在红外(IR)图像和可见光CCD图像融合效果评价中，结构轮廓对人眼感知的影响非常重要，而相位一致性（PC）模型生成的PC图像很好地在红外(IR)图像和可见光CCD图像融合效果评价中，结构轮廓对人眼感知的影响非常重要，而相位一致性（PC）模型生成的PC图像很好地保留了结构轮廓特征，且不受图像亮度和对比度变化的影响。提出了基于PC的结构相似度（SSIM）图像融合质量评价方法；利用SSIM模型分别产生融合图像相对于IR图像和可见光CCD图像的SSIM图像；根据PC模型产生IR和可见光CCD各自的PC图像；根据人眼对轮廓和非轮廓区域的重视程度的不同，利用各自的PC图像对SSIM图像进行加权；最终利用信息熵加权得到融合图像的评价指标。实验中，在对实验图像进行主观评价和多种客观评价指标计算的基础上，首次计算了非线性相关系数和斯皮尔曼等级相关系数(SROCC)，最后统计分析实验数据。实验结果表明该方法较以往评价方法具有更好的主客观一致性。

关键词: 信息处理技术, 图像融合, 结构相似度, 相位一致性, 图像融合质量评价, 主客观一致性

Abstract: Structure contour is very important to the human visual system in the quality evaluation of infrared (IR) and visible CCD fusion images. The phase congruency (PC) image, produced by the PC model, can preserve the structure contour feature of image very well, even if the image brightness and contrast have changed. Therefore, an assessment method based on PC is proposed for these considerations. Firstly, two images, the structural similarity (SSIM) images of the fused image relative to the IR and visible CCD images, are produced by the SSIM model, respectively. Then, two PC images of the IR and visible CCD images are produced by the PC model. Afterwards, the SSIM images are weighted by their corresponding PC images, considering the different visual sensitive levels of two different regions, contour region and residual region. At last, the information-entropy coefficients of the IR and visible CCD images are used as the weights to predict image quality assessment. The subjective and objective indexes of experimental images are extracted, and the nonlinear correlation coefficients and Spearman’s rank-order coefficients (SROCCs) are calculated for the first time. Finally the experimental data are statistically analyzed. The results indicate that the proposed method can present more subjective evaluation results more than the previous evaluation methods.

Key words: information processing, image fusion, structural similarity, phase congruency, image quality assessment, consistency between subjective as and objective assessments

中图分类号:

TP391.4

张玉珍，孙佳嵩，陈钱，顾国华，冯世杰，. 基于相位一致性的结构相似度图像融合质量评价方法[J]. 兵工学报, 2013, 34(12): 1514-1520.

ZHANG Yu-zhen， SUN Jia-song， CHEN Qian, GU Guo-hua, FENG Shi-jie，. Image Fusion Quality Assessment Method Based on Phase Congruency and Structural Similarity[J]. Acta Armamentarii, 2013, 34(12): 1514-1520.

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基于相位一致性的结构相似度图像融合质量评价方法

Image Fusion Quality Assessment Method Based on Phase Congruency and Structural Similarity

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