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A New Wavelet-based Multifocus Image Fusion Technique using Method Noise-Median Filtering

机译:一种新的基于小波的多焦点图像融合技术,使用方法噪声中值滤波

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Multifocus Image fusion is a technique to combine two or more different multi-focused images to generate an all-in-one focus image. In this paper, a new wavelet-based multi focus hybrid technique using method noise is proposed. Firstly SWT is applied to both the images to decompose the images in respective four subbands (LL, LH, HL, and HH). LL (low) is the approximation coefficient and others are LH, HL and HH are detailed coefficients for the source image. Then after that with the help of Inverse SWT we reconstruct the enhanced decomposed coefficients. When we compare the fused image with source image we get some residual part known as method noise. After processing i.e. filtering the method noise part, the enhance fused image is produced which is better than previous without method noise and other previous mentioned available literature. The proposed hybrid approach is used to generate a better enhanced and less distorted image that contains the full information of both degraded input images. The experimental results show that the proposed approach is better than the previous literature related to wavelet in terms of qualitative and quantitative results.
机译:多聚焦图像融合是组合两个或更多个不同的多聚焦图像以产生一体化焦点图像的技术。本文提出了一种使用方法噪声的新小波的多重聚焦混合技术。首先,SWT应用于图像,以将图像中的图像分解为各个四个子带(LL,LH,HL和HH)中的图像。 LL(低)是近似系数,其他是LH,HL和HH是源图像的详细系数。然后在逆向SWT的帮助下,我们重建增强的分解系数。当我们将熔融图像与源图像进行比较时,我们得到一些称为方法噪声的残余部分。在处理后,I.过滤方法噪声部分,产生增强融合图像,其优于前一个没有方法噪声和其他先前提到的可用文献。所提出的混合方法用于生成更好的增强且较少的扭曲图像,该图像包含两个劣化的输入图像的完整信息。实验结果表明,在定性和定量结果方面,该方法比以前与小波相关的文献更好。

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