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Image Inpainting System Model Based on Evaluation

机译:基于评估的图像修复系统模型

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摘要

Image segmentation algorithm and inpainting algorithm are the key ingredients in the process of inpainting after studying many image-inpainting algorithms. Therefore, analyzing, comparing and verifying the segment algorithms and inpainting algorithms, the system model which owns segment and repair evaluation function is constructed, so it can optimize the segmentation algorithms and the inpainting algorithms; finally make the inpainting result better. There is segmentation module and inpainting module in the system model, the former is to segment damaged area, and the later is to repair image. They adopt expert system, which extract image characteristics and optimize segmentation algorithms and inpainting algorithms by heuristic rules in the knowledge database, evaluate the result of the inpainting which can feedback the heuristic rules for selecting better algorithms, finally adopt the best segmentation and inpainting algorithm. System model synthesizes two key ingredients of segmentation and inpainting, so that it can enhance the inpainting effect, and' that the system will be constructed actuaDy need to further study and to carry out.
机译:在研究了很多图像修复算法之后,图像分割算法和修复算法是修复过程中的关键要素。因此,通过对分割算法和修复算法进行分析,比较和验证,构建了具有分割和修复评估功能的系统模型,从而可以对分割算法和修复算法进行优化。最终使修复效果更好。系统模型中有分割模块和修复模块,前者用于分割受损区域,后者用于修复图像。他们采用专家系统,该系统提取图像特征并通过知识数据库中的启发式规则来优化分割算法和修复算法,评估修复结果以反馈启发式规则以选择更好的算法,最后采用最佳的分割和修复算法。系统模型综合了分割和修复的两个关键要素,从而可以增强修复效果,并且需要进一步研究和实施该系统。

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