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Fusion Algorithm of Multi-focus Images with Weighted Ratios and Weighted Gradient Based on Wavelet Transform

机译:基于小波变换的加权比和加权梯度的多焦图像融合算法

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摘要

Multi-focus image fusion means fusing a completely clear image with a set of images of the same scene and under the same imaging conditions with different focus points. In order to get a clear image that contains all relevant objects in an area, the multi-focus image fusion algorithm is proposed based on wavelet transform. Firstly, the multi-focus images were decomposed by wavelet transform. Secondly, the wavelet coefficients of the approximant and detail sub-images are fused respectively based on the fusion rule. Finally, the fused image was obtained by using the inverse wavelet transform. Among them, for the low-frequency and high-frequency coefficients, we present a fusion rule based on the weighted ratios and the weighted gradient with the improved edge detection operator. The experimental results illustrate that the proposed algorithm is effective for retaining the detailed images.
机译:多焦点图像融合意味着融合完全清晰的图像,其具有相同场景的一组图像,在与不同焦点的相同成像条件下。 为了获得包含区域中的所有相关对象的清晰图像,基于小波变换提出了多聚焦图像融合算法。 首先,通过小波变换分解多焦图像。 其次,近似和细节子图像的小波系数分别基于融合规则融合。 最后,通过使用逆小波变换获得融合图像。 其中,对于低频和高频系数,我们基于加权比率和加权梯度与改进的边缘检测操作员一起呈现融合规则。 实验结果表明,所提出的算法对于保留详细图像是有效的。

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