期刊文献+

基于稀疏分解和背景差分融合方法的图像处理技术 被引量:2

Image processing technology based on sparse decomposition and background difference fusion method
下载PDF
导出
摘要 针对传统融合算法处理聚焦区域能力弱、边缘效果差以及目标轮廓提取存在缺陷等问题,提出了基于稀疏分解和背景差分融合的方法.稀疏分解经过鲁棒主成分分析方式提取多聚焦图像轮廓,从而为源图像的准确分离奠定基础;背景差分融合依照源图像与增强图像的差异图提取轮廓信息以准确定位聚焦区域,从而防止引入人工干扰.结果表明,与传统方法相比,本文提出的方法在很大程度上提升了融合效果,能够很好地加强其对噪声的鲁棒性,同时表现出很好的视觉效果. Aiming at the problems that in the traditional fusion algorithm,the capacity to deal with the focus area is weak,the edge effect is poor,and the defects exist in the target contour extraction,a method based on the sparse decomposition and background difference fusion was proposed. The contours of multi-focus image were extracted with the sparse decomposition method in the robust principal component analysis mode,which could provide the foundation for the exact separation of source image. According to the difference diagram between both source and enhanced images,the contour information was extracted in the background difference fusion method to accurately locate the focus area,and thus the introduction of manual interference could be prevented. The results showthat compared with the traditional method,the proposed method can greatly increase the fusion effect,enhance its robustness to noise,and exhibits good visual effect at the same time.
作者 王金茹 WANG Jin-ru(School of Management and Journalism,Shenyang Sport University,Shenyang 110102,China)
出处 《沈阳工业大学学报》 EI CAS 北大核心 2018年第4期436-440,共5页 Journal of Shenyang University of Technology
基金 辽宁省自然科学基金资助项目(2015020031) 2015年度辽宁省社科联与高校社科联合作课题(lslgslhl-156)
关键词 稀疏分解 背景差分融合 鲁棒主成分分析 图像融合 多尺度变换 剪切波变换 图像处理 融合算法 sparse decomposition background differential fusion robust principal component analysis image fusion multi-scale transform shear wave transform image processing fusion algorithm
  • 相关文献

参考文献6

二级参考文献39

  • 1李红启,鲁光泉.基于构建定律的智能交通网络[J].公路交通科技,2009(S1):107-110. 被引量:2
  • 2李红伦,李勃,阮湘辉,李文兵.基于背景减法的目标检测在Matlab中的实现方法[J].云南大学学报(自然科学版),2009,31(S2):59-61. 被引量:6
  • 3张跃飞,姜玉亭,王建英,尹忠科.基于稀疏分解的图像压缩[J].系统工程与电子技术,2006,28(4):513-515. 被引量:11
  • 4刘富强,李洲晖.基于光照无关图的阴影去除方法[J].中国图象图形学报,2007,12(10):1837-1840. 被引量:5
  • 5Rockinger O. Pixel-level fusion of image sequences using wavelet frames. In: Proceedings of Image Fusion and Shape Variability Techniques. Leeds, UK: Leeds University Press,1996. 149-154
  • 6Gonzalez A M, Saleta J L, Catalan R G, Garcia R. Fusion of multispectral and panchromatic images using improved IHS and PCA mergers based on wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 2004, 42(6): 1291-1299
  • 7Wang Z J, Ziou D, Armenakis C, Li D, Li Q G. A comparative analysis of image fusion methods. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(6): 1391-1402
  • 8Nunez J, Otazu X, Fors O, Prades A, Pala V, Arbiol R. Multiresolution-based image fusion with additive wavelet decomposition. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(3): 1204-1211
  • 9Do M N, Vetterli M. The contourlet transform: an efficient directional multiresolution image representation. IEEE Transactions on Image Processing, 2005, 14(12): 2091-2106
  • 10Da Cunha A L, Zhou J P, Do M N. The nonsubsampled contourlet transform: theory, design and applications. IEEE Transactions on Image Processing, 2006, 15(10): 3089-3101

共引文献37

同被引文献23

引证文献2

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部