计算机应用 ›› 2021, Vol. 41 ›› Issue (1): 220-224.DOI: 10.11772/j.issn.1001-9081.2020081456

所属专题: 第八届中国数据挖掘会议(CCDM 2020)

• 第八届中国数据挖掘会议(CCDM 2020) • 上一篇    下一篇

基于引导滤波和差分图像的多聚焦图像融合方法

成亚玲1,2, 柏智2, 谭爱平1   

  1. 1. 湖南工业职业技术学院 信息工程学院, 长沙 410208;
    2. 湖南城市学院 机械与电气工程学院, 湖南 益阳 413000
  • 收稿日期:2020-09-30 修回日期:2020-10-19 出版日期:2021-01-10 发布日期:2020-12-18
  • 通讯作者: 成亚玲
  • 作者简介:成亚玲(1981-),女,上海人,副教授,硕士,主要研究方向:图像处理、数据挖掘;柏智(1975-),男,湖南邵阳人,副教授,博士,软件设计与开发、图像处理;谭爱平(1979-),男,湖南株洲人,副教授,硕士,主要研究方向:数据挖掘。
  • 基金资助:
    湖南省教育厅科学研究基金资助项目(17B079)。

Multi-focus image fusion method based on guided filtering and difference image

CHENG Yaling1,2, BAI Zhi2, TAN Aiping1   

  1. 1. College of Information Engineering, Hunan Industry Polytechnic, Changsha Hunan 410208, China;
    2. College of Mechanical and Electrical Engineering, Hunan City University, Yiyang Hunan 413000, China
  • Received:2020-09-30 Revised:2020-10-19 Online:2021-01-10 Published:2020-12-18
  • Supported by:
    This work is partially supported by the Scientific Research Fund of Hunan Provincial Department of Education (17B079).

摘要: 针对传统的多聚焦图像的空间域融合容易出现边缘模糊的问题,提出了一种基于引导滤波(GF)和差分图像的多聚焦图像融合方法。首先,将源图像进行不同水平的GF,并对滤波后图像进行差分,从而获得聚焦特征图像;随后,利用聚焦特征图像的梯度能量(EOG)信息获得初始决策图,对初始决策图进行空间一致性检查以及形态学操作以消除因EOG相近而造成的噪点;然后,对初始决策图进行GF以得到优化后决策图,从而避免融合后的图像存在边缘骤变的问题;最后,基于优化后决策图对源图像进行加权融合,以得到融合图像。选取3组经典的多聚焦图像作为实验图像,将所提方法与其他9种多聚焦图像融合方法得到的结果进行比较。主观视觉效果显示,所提方法能更好地将多聚焦图像的细节信息保存下来,另外,经该方法处理后的图像的4项客观评价指标均显著优于对比方法。结果表明,所提方法能够获得高质量的融合图像,较好地保留原始图像信息,有效解决传统多聚焦图像融合出现的边缘模糊问题。

关键词: 多聚焦图像融合, 引导滤波, 差分图像, 决策图, 空间一致性

Abstract: To address the problem of edge blurring in traditional space domain fusion of multi-focus images, a multi-focus image fusion method based on Guided Filtering (GF) and difference image was proposed. Firstly, the source images were filtered by GF in different levels, and the difference was performed to the filtered images, so as to obtain the focused feature map. Secondly, the Energy of Gradient (EOG) of the focused feature map was used to obtain initial decision map. And to remove the noisy pixels caused by similar HOG, the spatial consistency verification and morphological operation were performed to initial decision map. Thirdly, to avoid sudden change of image feature, the initial decision map was optimized by GF. Finally, weighted fusion was performed to source images based on the optimized decision map, so as to obtain the fusion image. Three sets of classic multi-focus images were selected as experimental images, and the results obtained by the proposed method and other 9 multi-focus image fusion methods were compared. The subjective visual effects showed that the proposed method was able to better preserve the detailed information of multi-focus images, and four objective evaluation indicators of images processed by the proposed method were significantly better than those of the images processed by comparison methods. Experimental results show that the proposed method can achieve high-quality fusion image, well preserve information in source images, effectively solve edge blurring problem of traditional multi-focus image fusion.

Key words: multi-focus image fusion, Guided Filter (GF), difference image, decision map, spatial consistency

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