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Muti-focus image fusion using wavelet based contourlet transform and region

机译:基于小波的Contourlet变换和区域的Muti-焦点图像融合

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Utilizing the contourlet's advantages of multiscale, localization, directionality and anisotropy, a New method for multi-focus image fusion using wavelet based contourlet transform and region was proposed. In the contourlet transform, the Laplacian pyramid transform was replaced by the wavelet transform to obtain non-redundant wavelet-based contourlet transform. The source image is decomposed into low-frequency image and high-frequency images by wavelet based contourlet.. The fusion rule of Regional variance is adopted in low-frequency image, and the fusion rule of local energy are adopted in high-frequents subbands. Finally the fused image is obtained through inverse transform. Experimental results show that the proposed method has better subjective visual effect. Compared to traditional gradient pyramid algorithm and wavelet fusion algorithm, the proposed algorithm in paper has smallest mean square error.
机译:利用Contourlet的多尺度,定位,方向和各向异性的优点,提出了一种使用基于小波的Contourlet变换和区域的多聚焦图像融合的新方法。在轮廓型变换中,通过小波变换代替Laplacian金字塔变换以获得基于非冗余小波的Contourlet变换。通过基于小波的Contourlet将源图像分解成低频图像和高频图像。在低频图像中采用区域方差的融合规则,并且在高频率子带中采用局部能量的融合规则。最后,通过逆变换获得熔融图像。实验结果表明,该方法具有更好的主观视觉效果。与传统梯度金字塔算法和小波融合算法相比,所提出的纸张算法具有最小的均方误差。

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