计算机应用 ›› 2019, Vol. 39 ›› Issue (2): 564-570.DOI: 10.11772/j.issn.1001-9081.2018061346

• 虚拟现实与多媒体计算 • 上一篇    下一篇

不可分拉普拉斯金字塔构造及其在多光谱图像融合中的应用

刘斌, 辛迦楠, 谌文江, 肖惠勇   

  1. 湖北大学 计算机与信息工程学院, 武汉 430062
  • 收稿日期:2018-06-27 修回日期:2018-08-30 出版日期:2019-02-10 发布日期:2019-02-15
  • 通讯作者: 辛迦楠
  • 作者简介:刘斌(1963-),男,湖北武汉人,教授,博士,主要研究方向:图像处理、小波分析、模式识别;辛迦楠(1992-),女,河南洛阳人,硕士研究生,主要研究方向:图像处理、小波分析、遥感图像融合、机器学习;谌文江(1994-),女,湖北武汉人,硕士研究生,主要研究方向:图像处理、小波分析、多聚焦图像融合;肖惠勇(1992-),男,湖北孝感人,硕士,主要研究方向:图像处理、小波分析、遥感图像融合。
  • 基金资助:
    国家自然科学基金面上项目(61471160)。

Construction of non-separable Laplacian pyramid and its application in multi-spectral image fusion

LIU Bin, XIN Jianan, CHEN Wenjiang, XIAO Huiyong   

  1. School of Computer Science and Information Engineering, Hubei University, Wuhan Hubei 430062, China
  • Received:2018-06-27 Revised:2018-08-30 Online:2019-02-10 Published:2019-02-15
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61471160).

摘要: 针对拉普拉斯塔形(LP)变换在图像融合中具有高频信息损失严重且缺乏平移不变性的问题,利用不可分小波具有平移不变性和能够准确描述图像细节信息的特点,提出一种新的非采样不可分拉普拉斯金字塔构造方法,并将该构造方法应用于多光谱图像融合中。首先,构造六通道不可分低通滤波器,利用该滤波器构造多光谱图像和全色图像的非采样不可分小波塔形分解,进而对图像进行非采样不可分拉普拉斯塔形分解;然后,针对不同的分解层采用不同的融合规则进行融合;最后,根据不可分拉普拉斯重构算法进行重构,即可得到融合后的图像。实验结果表明,与离散小波变换(DWT)的融合方法、基于Contourlet变换(CT)的融合方法以及基于直方图中轴化(MHE)的融合方法对比,所提方法在保持原全色图像空间分辨率的评价指标空间相关系数上分别提高了1.84%、1.56%和11.06%,在光谱信息保持程度的评价指标相对整体维数综合误差上分别降低了49.26%、48.15%和89.19%。该方法所得图像在获得好的光谱信息的同时有效地提高了空间分辨率,较好地保留了图像的边缘信息与结构信息。

关键词: 多光谱图像融合, 不可分小波, 低通滤波器, 不可分拉普拉斯金字塔, 平移不变性

Abstract: In order to solve the problem that classical Laplacian Pyramid (LP) transformin image fusion losses high frequency information of the fused image seriously and has no translation invariance, with the use of non-separable wavelet which has translation invariance and accurate description of image details, a new construction method of non-sampling non-separable LP was proposed and applied to the multi-spectral image fusion. Firstly, a six-channel non-separable low-pass filter was constructed and used to construct non-sampling non-separable wavelet pyramid for multi-spectral image and panchromatic image, and then the image was processed by non-sampling non-separable LP decomposition. Then, different fusion rules were used for the fusion of different decomposition layers. Finally, the fused image was obtained by using non-separable LP reconstruction algorithm. The experimental results show that compared with the algorithms based on Discrete Wavelet Transformation (DWT), Contourlet Transformation (CT), and Midway Histogram Equalization (MHE), the spatial correlation coefficient of the proposed method was increased by 1.84%, 1.56%, and 11.06% respectively, and the relative global dimensional synthesis error of the proposed method was reduced by 49.26%, 48.15%, and 89.19% respectively. The proposed method can effectively improve the spatial resolution while obtaining good spectral information of image, well preserve the edge information and structure information of the image.

Key words: multi-spectral image fusion, non-separable wavelet, low-pass filter, non-separable Laplacian Pyramid (LP), translation invariance

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