Image fusion method based on multi-scale non-local mean filter and shear direction filter

被引：0
|
作者：
Wang F. [1 ]
Cheng Y.-M. [1 ]
机构：
[1] School of Automation, Northwestern Polytechnical University, Xi'an
来源：
Kongzhi yu Juece/Control and Decision | 2017年 / 32卷 / 12期
关键词：
Fusion rule; Image fusion; Multi-scale transform; Nonlocal means filter; Shear filter;
D O I：
10.13195/j.kzyjc.2016.1590
中图分类号：
学科分类号：
摘要：
For the problem that the non-subsampled pyraimd(NSP) used in non-subsampled shearlet transform(NSST) cannot effectively capture the image structure information, a multi-scale nonlocal means filter(MNMF) combined directional shearinge filter(SF) of new transformation is proposed, which uses the MNMF instead of the NSP decomposition in the NSST transformation. Then, it is used in image fusion, and the input image is decomposed into different subbands.The approximation subbands are fused by applying the regional weighted sum of pixel energy(PE) and gradient energy(GE). For the direction subbands, the fusion rule based on GE combiend with the coefficient of absolute value(CAV) is proposed. The simulation experiments verify that the proposed fusion method has obvious advantages in two aspects of visual perception and objective quality evaluation. © 2017, Editorial Office of Control and Decision. All right reserved.
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页码：2183 / 2189
页数：6
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