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Reconstruction Algorithms with Images Inferred by Self-organizing Maps

机译:自组织映射推断图像的图像重建算法

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For restoring a degraded image, reconstruction algorithms with images inferred by self-organizing maps are presented in this study. Multiple images inferred by self-organizing maps are prepared in the initial stage, which creates a map containing one unit for each pixel. Utilizing pixel values as input, image inference is conducted by self-organizing maps. An updating function with threshold according to the difference between input value and inferred value is introduced, so as not to respond to noisy input sensitively. The inference of an original image proceeds appropriately since any pixel is influenced by neighboring pixels corresponding to the neighboring setting. By using the inferred images, two approaches are presented. The first approach is that a pixel value of a restored image is a median value of inferred images for respective pixels. The second approach is that a pixel value is an average value of them. Experimental results are presented in order to show that our approach is effective in quality for image restoration.
机译:为了还原退化的图像,本研究提出了利用自组织图推断的图像的重建算法。通过自组织图推断出的多个图像在初始阶段就准备好了,这将为每个像素创建一个包含一个单位的图。利用像素值作为输入,通过自组织映射进行图像推断。引入了根据输入值与推断值之差的阈值更新功能,以免敏感地响应嘈杂的输入。由于任何像素都受到与相邻设置相对应的相邻像素的影响,因此可以适当地进行原始图像的推断。通过使用推断的图像,提出了两种方法。第一种方法是恢复图像的像素值是各个像素的推断图像的中值。第二种方法是像素值是它们的平均值。提出实验结果以表明我们的方法在图像恢复质量上是有效的。

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