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Image Inpainting Based on Image Mapping and Object Removal Using Semi-Automatic Method

机译:基于图像映射和对象去除的半自动图像修复

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The image inpainting process selects the object manually. We are dealing with semi-automatic image inpainting algorithm. In semi-automatic image inpainting method user manually gives an outline of an object which we want to remove or the damaged region which we want to recover and an inpainting algorithm will automatically fill that region. In the proposed method, segmentation is used for removing unwanted regions from the image. As the hole in the image to be inpainted is an unendorsed method, we are totaling the pixel in the holes by means of spatial contextual correspondences. The main importance of our approach is to utilize association of a pixel with its neighbors to get precise smoothness over the inpainted image. The region to be inpainted can be chosen initially by performing the segmentation approach. The region growing method is applied thus segmenting the regions. The multiple and single region selection is also applicable. Now the region to be inpainted is termed as a hole in the given image which is removed from the image. The omitted region can be packed using the correlation made by the information supplied by the neighbors and its information.
机译:图像修补过程会手动选择对象。我们正在处理半自动图像修复算法。在半自动图像修复方法中,用户手动给出要删除的对象的轮廓或要恢复的损坏区域的轮廓,修复算法将自动填充该区域。在提出的方法中,分割用于从图像中去除不需要的区域。由于要修复的图像中的孔是未经认可的方法,因此我们将通过空间上下文对应来对孔中的像素进行总计。我们方法的主要重要性是利用像素与其相邻像素的关联,以在修复的图像上获得精确的平滑度。可以首先通过执行分割方法来选择要修复的区域。应用区域生长方法,从而分割区域。多个和单个区域选择也适用。现在,要修复的区域称为给定图像中的孔,该孔已从图像中删除。可以使用由邻居提供的信息及其信息所形成的相关性来打包省略的区域。

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