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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:模糊逻辑,图像融合,神经网络和非本地手段对嘈杂环境的图像处理调查

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摘要

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:随着时间的推移,我们的技术日益增加。我们可以知道它在机器人技术中变得更好。机器人立即尝试与人类社交。对于输入,图像处理变得更加重要,因为它可以确保人类的行为和反应。它是不可避免的,当相机作为输入拍摄照片时会产生一些噪音。因此,噪声去除是用于图像处理的关键技术。我们选择四种噪音拆除方法来介绍。有模糊逻辑,图像融合,人工神经网络,非本地手段。我们发现2015年至2017年发表的论文,并介绍了它们与传统方法之间的不同。在本文末尾,我们使用PSNR作为比较标准来检查其优缺点。

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