Image inpainting based on image segmentation and segment classification

Eman T. Hassan, Hazem M. Abbas, H. K. Mohamed
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引用次数: 7

Abstract

We present a new inpainting algorithm that is based on image segmentation and segment classification. First, we employ the mean shift algorithm to segment the input image. Then, we divide the original inpainting problem to be either one of the two problems: Large Segment Inpainting problem or Non-uniform Segments inpainting problem. The reason we do that is that human eye is more discerning to the errors in the structure and texture propagation of a large-uniform regions with less details while it is less discerning to errors in non-uniform regions with more details. We propose a novel algorithm for each one of the problems- Large Segment Inpainting and Non-uniform Segments inpainting- according to the main features of each one. The experimental results show the advantage of our technique which produces output images with better perceived visual quality.
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基于图像分割和分段分类的图像绘制
提出了一种新的基于图像分割和分割分类的图像绘制算法。首先,采用均值移位算法对输入图像进行分割。然后,我们将原补漆问题划分为两个问题之一:大线段补漆问题或非均匀线段补漆问题。我们这样做的原因是人眼对大均匀区域的结构和纹理传播中的错误具有较强的识别能力,而对非均匀区域的错误具有较强的识别能力。针对这两种问题的主要特点,我们分别提出了一种新的算法来解决这两种问题——大线段绘制和非均匀线段绘制。实验结果表明了该方法的优越性,输出的图像具有较好的感知视觉质量。
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