邢素霞. 多光谱图像融合中小波分解层数研究[J]. 微电子学与计算机, 2011, 28(1): 176-179.
引用本文: 邢素霞. 多光谱图像融合中小波分解层数研究[J]. 微电子学与计算机, 2011, 28(1): 176-179.
XING Su-xia. Study on Optimal Wavelet Decomposition Level in Multi-spectrual Image Fusion[J]. Microelectronics & Computer, 2011, 28(1): 176-179.
Citation: XING Su-xia. Study on Optimal Wavelet Decomposition Level in Multi-spectrual Image Fusion[J]. Microelectronics & Computer, 2011, 28(1): 176-179.

多光谱图像融合中小波分解层数研究

Study on Optimal Wavelet Decomposition Level in Multi-spectrual Image Fusion

  • 摘要: 首先根据小波变换原理,采用Db9小波基函数,对多组多光谱图像分别进行1~5层小波分解,然后根据小波逆变换原理对系数融合后的图像进行逆变换,得到不同小波分解层的融合图像.最后,利用图像质量评价方法信息熵、标准差、互信息、以及图像融合质量综合评价方法等,对不同分解层下的融合图像进行了评价.实验结果表明:小波变换在一层小波分解时,图像融合效果最佳.

     

    Abstract: According to the wavelet transform theory, several groups of multi-spectral images were decomposed 1~5 layers respectively by using Db9 wavelet function;and then under the principle of inverse wavelet transform, fused images were obtained.Finally, the image quality evaluation methods such as information entropy, standard deviation, mutual information, and image fusion quality assessment were used to evaluate the fused images under different decomposition layers.Experimental results show that one layer of wavelet decomposition owns the best results in image fusion.

     

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