JISP  >> Vol. 4 No. 2 (April 2015)

    基于提升小波变换的图像融合改进算法的研究
    Study on the Improvement of Image Fusion Algorithm Based on Lifting Wavelet Transform

  • 全文下载: PDF(697KB) HTML   XML   PP.11-19   DOI: 10.12677/JISP.2015.42002  
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作者:  

江泽涛:桂林电子科技大学计算机科学与工程学院,广西 桂林;
杨 阳,郭 川:南昌航空大学信息工程学院,江西 南昌

关键词:
图像融合融合规则小波变换提升小波变换Image Fusion Fusion Rule Wavelet Transform Lifting Wavelet Transform

摘要:

提出了一种基于提升小波变换的图像融合改进算法。针对提升小波分解后的低频和高频分量各自的特点,选用不同的规则进行融合,即低频系数采用选择法和加权平均相结合的策略,高频系数时,把小波系数的方差与绝对值综合起来考虑决定融合小波系数。实验结果表明,当采用平均梯度、信息熵、标准差、均方根误差和峰值信噪比作为客观评价准则,该算法的融合图像比拉普拉斯金字塔融合图像和传统的小波变换的融合图像具有更好的融合效果,较好地提高了图像融合精确度。

An improved algorithm is Proposed for image fusion based on lifting wavelet transform in the paper. According to the characteristics of lifting wavelet decomposition of the low and high frequency components of the respective, different fusion rules are adopted, namely low frequency coefficient selection method and the weighted average method, choosing the high frequency coefficient, the variance of wavelet coefficients and the absolute value of the wavelet coefficients are considered synthetically decision fusion. The experimental results show that, when we take the average gradient, the information entropy, the standard deviation, root mean square error and peak signal to noise ratio as the objective evaluation criteria of image fusion, image fusion algorithm has better fusion effect than Laplasse Pyramid fusion image and the traditional wavelet transform; it improves the accuracy of image fusion effectly.

文章引用:
江泽涛, 杨阳, 郭川. 基于提升小波变换的图像融合改进算法的研究[J]. 图像与信号处理, 2015, 4(2): 11-19. http://dx.doi.org/10.12677/JISP.2015.42002

参考文献

[1] Daubechies, I. and Sweldens, W. (1998) Factoring wavelet transforms into lifting steps. Journal of Fourier Analysis and Applications, 4, 245-267.
[2] Daubechies, I. and Sweldens, W. (1998) Factoring wavelet transforms into lifting steps. Journal of Fourier Analysis and Applications, 4, 305-327.
[3] Li, H.G., Wang, Q. and Wu, L.N. (2001) A novel design of lifting scheme from general wavelets. IEEE Transactions on Signal Processing, 49, 1714-1717.
[4] 孙延奎 (2005) 小波分析及其应用. 机械工业出版社, 北京.
[5] 王卫卫, 水鹏朗, 宋国乡 (2004) 小波域多聚集图像融合算法. 系统工程与电子技术, 5, 668-671.
[6] 李伟, 朱学峰 (2007) 基于第二代小波变换的图像融合方法及性能评价. 自动化学报, 8, 817-822.
[7] 杨静, 王岩飞, 刘波 (2004) 一种新的非抽取提升结构小波变换图像融合方法. 光子学报, 6, 728-731.
[8] 刘军伟, 饶妮妮 (2005) 提升小波变换的FPGA 设计与实现. 微计算机信息, 11Z, 132-134.
[9] Dong, H.X., Yi, Z.J. and Ye, X.B. (2012) Multifocus image fusion scheme based on features contrast of lifting stationary wavelet. Application Research of Computers, 2, 096.
[10] Liao, C.Z., Liu, Y.S. and Jiang, M.Y. (2013) Multifocus image fusion using Laplacian pyramid and Gabor filters. Applied Mechanics and Materials, 373, 530-535.
[11] 陈浩, 王延杰 (2014) 基于小波变换的图像融合技术研究. 微电子学与计算机, 5, 39-41.
[12] 邵国峰, 林锦顺, 张卫国 (2014) 一种基于提升小波的快速图像融合算法. 光电技术应用, 4, 39-44.
[13] 徐萌萌 (2014) 基于小波变换的图像融合算法研究. 哈尔滨理工大学, 哈尔滨.
[14] 余汪洋, 陈祥光, 董守龙, 吴磊 (2014) 基于小波变换的图像融合算法研究. 北京理工大学学报, 12, 1262-1266.
[15] 王娟 (2010) 基于第二代小波变换的图像融合算法研究. 西华大学, 成都.
[16] 李俊峰, 姜晓丽, 戴文战 (2014) 基于提升小波变换的医学图像融合. 中国图象图形学报, 11, 1639-1648.