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Deblurring Image Using Motion Sensor and SOM Neural Network

机译:使用运动传感器和SOM网络的去纹理图像

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As multimedia image related devices are widely used by the general public, multimedia image processing technology is more and more advanced, however there are still some problems that are worth to be explored and improved. How to deblurring an image without the information of speed and direction of moving objects is still a well-known ill-posed problem. In this paper, we proposed a system to deblurring image that can estimate important parameter advance to reduce the complexity of deblurring process. The data of sensor of moving object is collected. The SOM neural network is used to train to classify the speed and direction of the object from the sensor data. After that, we can estimate the speed and direction of objects without other algorithms. With such important parameters, deblurring processing will more efficient.
机译:随着多媒体图像相关设备被广泛的公众广泛使用,多媒体图像处理技术越来越先进,但仍有一些问题值得探索和改进。如何在没有移动物体的速度和方向的信息的情况下去束缚图像仍然是一个众所周知的不良问题。在本文中,我们提出了一种用于去掩缝图像的系统,可以估计重要参数前进以降低去纹理过程的复杂性。收集移动物体传感器的数据。 SOM Neural网络用于训练从传感器数据分类对象的速度和方向。之后,我们可以估计没有其他算法的物体的速度和方向。利用如此重要的参数,防束处理将更有效。

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