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Research on ELM-based Image Restoration Algorithm

机译:基于ELM的图像恢复算法研究

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As the rapid development of the multi-media technology, more and more digital devices are used to take pictures. However, sometimes the images may be degraded due to disoperation, the environment, and system and so on. The main task for image recovery is combining the degraded images and some priori information to acquire the best estimation of the original image by using some kind of restoration algorithm. In this paper, a new image restoration algorithm based on ELM Neural Network and some edge information was proposed, aiming at the fuzzy motion images. As the experiment shows that comparing traditional BP Neural Network, the new restoration algorithm based on ELM Neural Network is simpler, faster, easier to implement, what's more, it's more suitable for real-time processing.
机译:随着多媒体技术的飞速发展,越来越多的数字设备被用于拍照。但是,有时图像可能会由于故障,环境和系统等原因而降级。图像恢复的主要任务是结合退化图像和一些先验信息,以使用某种恢复算法获得对原始图像的最佳估计。针对模糊运动图像,提出了一种基于ELM神经网络和边缘信息的图像复原算法。实验表明,与传统的BP神经网络相比,基于ELM神经网络的新恢复算法更简单,更快,更容易实现,而且更适合实时处理。

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