Piella像素级多分辨率图像融合框架的扩展及其算法

李光鑫; 徐抒岩; 吴伟平; 孙天宇; 郝伟

doi:10.3788/OPE.20122012.2773

您当前的位置：

首页 >

文章列表页 >

Piella像素级多分辨率图像融合框架的扩展及其算法

信息科学 | 更新时间：2020-08-13

- Piella像素级多分辨率图像融合框架的扩展及其算法
- Extension of Piella pixel-level multiresolution image fusion framework and its algorithm
- 光学精密工程 2012年20卷第12期页码：2773-2780
- 作者机构：
  
  中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目(No.60507003)();科技部国际合作项目(No.2011DFA50590)()
- DOI：10.3788/OPE.20122012.2773
  中图分类号： TP751
- 收稿日期：2012-08-21，
  
  修回日期：2012-09-15，
  
  纸质出版日期：2012-12-10
- 稿件说明：
移动端阅览
李光鑫, 徐抒岩, 吴伟平, 孙天宇, 郝伟. Piella像素级多分辨率图像融合框架的扩展及其算法[J]. 光学精密工程, 2012,20(12): 2773-2780

LI Guang-xin, XU Shu-yan, WU Wei-ping, SUN Tian-yu, HAO Wei. Extension of Piella pixel-level multiresolution image fusion framework and its algorithm[J]. Editorial Office of Optics and Precision Engineering, 2012,20(12): 2773-2780
李光鑫, 徐抒岩, 吴伟平, 孙天宇, 郝伟. Piella像素级多分辨率图像融合框架的扩展及其算法[J]. 光学精密工程, 2012,20(12): 2773-2780 DOI： 10.3788/OPE.20122012.2773.

LI Guang-xin, XU Shu-yan, WU Wei-ping, SUN Tian-yu, HAO Wei. Extension of Piella pixel-level multiresolution image fusion framework and its algorithm[J]. Editorial Office of Optics and Precision Engineering, 2012,20(12): 2773-2780 DOI： 10.3788/OPE.20122012.2773.

摘要

为了优化加权多分辨率图像融合的算法结构

在Piella像素级多分辨率图像融合框架基础上

提出一种只用匹配测度控制决策模块的加权多分辨率图像融合扩展模式

改变了传统加权多分辨率图像融合模式必须由活性测度和匹配测度共同决定决策因子的格局。相对于传统模式

提出的扩展模式去除了活性测度

相应的算法结构更为简单。以相关信号强度比作为匹配测度

给出了一种基于扩展模式的加权多分辨率图像融合算法。对红外和可见光图像的融合实验表明

该算法融合性能优于传统加权多分辨率图像融合算法

其边缘融合质量指标(EFQI)和加权融合质量指标(WFQI)分别提高了2.9%和1.8%;而且计算复杂度更低

计算决策因子所需的乘法和加法运算次数分别减少了66.7%和33.3%。

Abstract

To optimize the architecture of weighted average multiresolution image fusion algorithm

an extended weighted average multiresolution image fusion model to control the decision map only with the match measure is presented based on the Piella pixel-level multiresolution image fusion framework. The extended model changes the fusion pattern that the decision factor must be decided by both activity measure and match measure in the conventional weighted average multiresolution image fusion model. Since the activity measure is removed in the extended model

the corresponding algorithm architecture is rather simpler. By taking the correlated signal intensity ratio as the match measure

a weighted average multiresolution image fusion method based on the extended model is proposed. The experiment on fusing infrared and visible images shows that the proposed method is able to produce better fusion results than the conventional ones and its Edge Fusion Quality Index(EFQI) and Weight Fusion Quality Index(WFQI)has increased by 2.9% and 1.8%

respectively.Moreover

it achieves much lower computational complexity for the decision factor with decreased multiplication and addition times of 66.7% and 33.3%

respectively.

关键词

Keywords

references

PIELLA G. A general framework for multiresolution image fusion: From pixels to regions [J]. Information Fusion, 2003, 4(4):259-280.[2] ZHANG Z, BLUM R S. A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application [J]. IEEE, 1999, 87(8):1315-1326.[3] BURT P J, KOLCZYNSKI R J. Enhanced image capture through fusion. The 4th International Conference on Computer Vision, Berlin, Germany: 1993:173-182.[4] GOOITZEN V D W. Technical overview of the sarnoff acadia II vision processor [J]. SPIE, 2010, 7710: 77100O-1-77100O-12.[5] DAVID B, GOOITZEN V D W. Implementing real-time imaging systems using the sarnoff acadia II vision processor [J]. SPIE, 2010, 7710: 77100T-1-77100T-12.[6] 李光鑫, 徐抒岩. 适于图像融合的快速颜色传递方法 [J]. 光学精密工程, 2009, 17(9):2301-2310. LI G X, XU S Y. Fast color transfer method for image fusion [J]. Opt. Precision Eng., 2009, 17(9): 2301-2310. (in Chinese)[7] 李光鑫, 王珂, 张立保. 加权多分辨率图像融合的快速算法 [J]. 中国图象图形学报, 2005, 10(12):1529-1536. LI G X, WANG K, ZHANG L B. Computationally efficient algorithm of multiresolution image fusion with weighted average fusion rule [J]. Journal of Image and Graphics, 2005,10(12):1529-1536. (in Chinese)[8] PU T, NI G. Contrast-based image fusion using the discrete wavelet transform [J]. Optical Engineering, 2000, 39(8): 2075-2082.[9] LI H, MANJUNATH B S, MITRA S K. Multisensor image fusion using the wavelet transform [J]. Graphical Models and Image Processing, 1995,57(3):235-245.[10] DAUBECHIES I. Ten Lectures on Wavelets [M]. Philadelphia, PA: SIAM, 1992.[11] PIELLA G, HEIJMANS H. A new quality metric for image fusion. Proceedings of IEEE International Conference on Image Processing, Barcelona, Spain,2003: III-173-III-176.[12] CANGA E F, NIKOLOV S G, CANAGARAJAH C N, et al.. Characterisation of image fusion quality metrics for surveillance applications over bandlimited channels. The 8th International Conference on Information Fusion, Philadelphia, USA,2005:483-490.[13] SMITH M I, HEATHER J P. Review of image fusion technology in 2005 [J]. SPIE, 2005, 5782: 29-45.

浏览量

390

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据