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Research of multi-focus image fusion based on M-band multi-wavelet transformation

机译:基于M波段多小波变换的多焦点图像融合研究

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Image fusion is one of the important embranchments of data fusion. Its purpose is to synthesis multi-image information in one scene to one image which is more suitable to human vision and computer vision or more adapt to further image processing, such as target identification. This paper mainly discusses the image fusion method based on wavelet transformation. Firstly, the article gives the basic concept of multi-focus image fusion. On top of this, the paper gives the theory of wavelet analyses and its fast arithmetic, hereon gives the image fusion method based on singe wavelet. Getting on with the single wavelet, the paper presents some improved wavelet as multi-wavelet, multi-band multi-wavelet, including their theories and their arithmetic of decomposition and reconstruction. At the same time, the article applies the multi-band multi wavelet in the image fusion with the wavelet fusion thought. In the side of selecting fusion arithmetic operators, the paper compares the methods based on pictures, windows and regions, and adopts the fusion norm based on grads and characteristic measurement of regional energy. Besides it compares images which is based on different fusion norms and different wavelets in the aspects of entropy, peak value Signal-to-Noise, square root error and standard error in the experimentation. By using Matlab as experimental platform, we approved the feasibility and validity of the method mentioned in the article through a lot of experiments. The result indicates that multi-band multi-wavelet is very effective in image fusion. Furthermore, the article does some post processing to the fusion image. The method is based on anisotropic diffusion arithmetic based on partial differential equations. The experiments show that the brim diffusion enhanced the PSNR of image with the selective brim diffusion to the fusion image and depressed the image block domino effects caused by wavelet fusion method.
机译:图像融合是数据融合的重要分支之一。其目的是将一个场景中的多图像信息合成为一个更适合于人类视觉和计算机视觉或更适合于进一步的图像处理(例如目标识别)的图像。本文主要讨论基于小波变换的图像融合方法。首先,本文给出了多焦点图像融合的基本概念。在此基础上,给出了小波分析的理论及其快速算法,并在此基础上提出了基于单小波的图像融合方法。从单小波入手,本文提出了一些改进的小波,即多小波,多频带多小波,包括其理论以及分解和重构的算法。同时,本文以小波融合思想将多波段多小波应用于图像融合。在选择融合算术运算符的方面,比较了基于图片,窗口和区域的方法,并采用了基于梯度和区域能量特征度量的融合准则。此外,还比较了在熵,峰值信噪比,平方根误差和标准误差等方面基于不同融合准则和不同小波的图像。通过使用Matlab作为实验平台,我们通过大量实验验证了本文提到的方法的可行性和有效性。结果表明,多波段多小波在图像融合中非常有效。此外,文章对融合图像进行了一些后期处理。该方法基于基于偏微分方程的各向异性扩散算法。实验表明,边缘扩散通过选择性边缘扩散到融合图像提高了图像的PSNR,抑制了小波融合方法引起的图像块多米诺效应。

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