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An Improved Multi-Focus Image Fusion Method Based on Wavelet Transform

机译:一种基于小波变换的改进的多焦点图像融合方法

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An improved multi-focus image fusion method based on wavelet transform is proposed. Firstly, multi-scale decomposition is performed on source images using wavelet transform to get high-frequency and low-frequency sub-images. And then, a method based on neighboring region variance weighted-average is applied to high-frequency sub-image to get the high-frequency fusion coefficient; and a method based on local region gradient information is applied to low-frequency sub-image to get the low-frequency fusion coefficient. Finally, the inverse wavelet transform is utilized to obtain fused image. The fused image by the proposed method is evaluated with some parameters such as root mean square error, peak signal noise rate and entropy, in comparison with traditional fusion methods. The experiment results show that the proposed method is effective on improving the effect and quality of fused image.
机译:提出了一种改进的基于小波变换的多焦点图像融合方法。首先,利用小波变换对源图像进行多尺度分解,得到高频和低频子图像。然后,将基于邻域方差加权平均的方法应用于高频子图像,得到高频融合系数。将基于局部梯度信息的方法应用于低频子图像,得到低频融合系数。最后,利用逆小波变换获得融合图像。与传统的融合方法相比,该方法对融合后的图像进行了诸如均方根误差,峰值信号噪声率和熵之类的参数评估。实验结果表明,该方法对提高融合图像的效果和质量是有效的。

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