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A survey on image processing in noisy environment by fuzzy logic, image fusion, neural network, and non-local means

机译:利用模糊逻辑,图像融合,神经网络和非局部手段对嘈杂环境中的图像处理进行调查

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As time goes by, our technology gets improve day by day. We can know that it gets better in robotic technology. Robots try to social with human beings immediately. For the input, image processing becomes more important because it can make sure the human's actions and reactions. It is unavoidable that get some noise when the camera takes photo as input. Thus, noise removal is a key technology for image processing. We choose four kinds of noise removal's methods to introduce. There are fuzzy logical, image fusion, artificial neural network, non-local means. We find papers which were published during 2015 to 2017 and introduce what's different between them and traditional method. At the end of this paper, we use PSNR as the compared standard to check their advantages and disadvantages.
机译:随着时间的流逝,我们的技术日趋完善。我们可以知道,它在机器人技术方面越来越好。机器人试图立即与人类交往。对于输入,图像处理变得更加重要,因为它可以确保人的动作和反应。当相机拍摄照片作为输入时,不可避免地会产生一些噪点。因此,噪声去除是图像处理的关键技术。我们选择四种噪声消除的方法进行介绍。有模糊逻辑,图像融合,人工神经网络,非局部手段。我们查找2015年至2017年期间发表的论文,并介绍它们与传统方法之间的区别。在本文的最后,我们使用PSNR作为比较标准来检查它们的优缺点。

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