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一种快速的基于稀疏表示和非下采样轮廓波变换的图像融合算法

赵春晖 郭蕴霆

赵春晖, 郭蕴霆. 一种快速的基于稀疏表示和非下采样轮廓波变换的图像融合算法[J]. 电子与信息学报, 2016, 38(7): 1773-1780. doi: 10.11999/JEIT150933
引用本文: 赵春晖, 郭蕴霆. 一种快速的基于稀疏表示和非下采样轮廓波变换的图像融合算法[J]. 电子与信息学报, 2016, 38(7): 1773-1780. doi: 10.11999/JEIT150933
ZHAO Chunhui, GUO Yunting. Fast Image Fusion Algorithm Based on Sparse Representation and Non-subsampled Contourlet Transform[J]. Journal of Electronics and Information Technology, 2016, 38(7): 1773-1780. doi: 10.11999/JEIT150933
Citation: ZHAO Chunhui, GUO Yunting. Fast Image Fusion Algorithm Based on Sparse Representation and Non-subsampled Contourlet Transform[J]. Journal of Electronics and Information Technology, 2016, 38(7): 1773-1780. doi: 10.11999/JEIT150933

一种快速的基于稀疏表示和非下采样轮廓波变换的图像融合算法

doi: 10.11999/JEIT150933
基金项目: 

国家自然科学基金(61571145, 61405041),黑龙江省自然科学基金重点资助项目(ZD201216),哈尔滨市优秀学科带头人资金(RC2013XK009003)

Fast Image Fusion Algorithm Based on Sparse Representation and Non-subsampled Contourlet Transform

Funds: 

The National Natural Science Foundation of China (61571145, 61405041), The Key Program of Heilongjiang Province Natural Science Foundation (ZD201216), Excellent Academic Leaders Program of Harbin (RC2013XK009003)

  • 摘要: 为了提高图像融合的效率和质量,该文提出一种基于快速非下采样轮廓波变换(NSCT)和4方向稀疏表示的图像融合算法。该方法首先对源图像进行快速NSCT分解,生成一系列低通和高通子带。对于低频子带,利用自适应生成的DCT过完备字典进行快速的4方向稀疏表示和系数融合;对于高频子带,则利用高斯加权区域能量最大的融合规则进行系数融合。快速NSCT将传统NSCT的树形滤波结构转变为多通道滤波结构,能成倍提高分解效率;快速的稀疏融合则抛弃了传统的滑动窗口方法,以水平、垂直、对角线4个方向进行稀疏表示和稀疏融合,进一步提高算法效率。实验结果表明,提出的快速算法能在不影响融合质量的条件下将算法效率提高近20倍。
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出版历程
  • 收稿日期:  2015-08-13
  • 修回日期:  2016-04-07
  • 刊出日期:  2016-07-19

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