• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2015, Vol. 37 ›› Issue (06): 1203-1207.

• 论文 • 上一篇    下一篇

结合Curvelet变换和LSWT的多聚焦图像融合算法

王丽1,苗凤娟1,陶佰睿2   

  1. (1. 齐齐哈尔大学通信与电子工程学院,黑龙江 齐齐哈尔 161005;2.齐齐哈尔大学计算中心,黑龙江 齐齐哈尔 161005)
  • 收稿日期:2014-01-14 修回日期:2014-07-04 出版日期:2015-06-25 发布日期:2015-06-25
  • 基金资助:

    黑龙江省教育厅科学技术研究项目(12531774);黑龙江省自然科学基金资助项目(F201438)

A multi-focus image fusion algorithm based on
Curvelet transform and LSWT    

WANG Li1,MIAO Fengjuan1,TAO Bairui2   

  1. (1.Communication and Electronic Engineering Institute,Qiqihar University,Qiqihar 161005;
    2.Computer Center,Qiqihar University,Qiqihar 161005,China)
  • Received:2014-01-14 Revised:2014-07-04 Online:2015-06-25 Published:2015-06-25

摘要:

针对多聚焦图像,提出了一种结合二代Curvelet变换和提升静态小波变换LSWT的图像融合算法。首先将待融合的图像分别进行离散Curvelet分解变换,得到不同分解级数和方向下的细节尺度系数和粗尺度系数;其次对粗尺度系数分别进行LSWT变换,对变换得到的低频分量和高频分量分别采用不同的方法融合后进行LSWT逆变换,得到的系数作为Curvelet变换的粗尺度系数;对于Curvelet变换后得到的细节尺度系数采用局部平均能量方差的方法进行融合;最后进行Curvelet逆变换得到融合后的图像。实验结果显示,该方法融合效果较好,优于传统方法。

关键词: Curvelet变换, LSWT, 图像融合

Abstract:

Focusing on multi-focus images,in this paper we present an image fusion method based on the second generation Curvelet transform and the lifting stationary wavelet transform (LSWT).Firstly,the images to be fused are decomposed by discrete Curvelet transform, thus the fine-scale and coarse-scale coefficients are obtained in different scales and directions.Secondly,the coarse scale coefficients are decomposed by the LSWT.The low-frequency coefficients and the high-frequency coefficients are separately fused by different methods.Subsequently the coefficients obtained by the lifting stationary wavelet inverse transform are the coarse-scale coefficients of the Curvelet inverse transform.The fine-scale coefficients are fused by the local average energy and variance method.Finally,the fused image is obtained by the Curvelet inverse transform.Experimental results show that the proposed method is superior to the traditional methods.

Key words: Curvelet transform;LSWT;image fusion