Improved Criminisi Algorithm Based on a New Priority Function with the Gray Entropy

Xiang-yan Xi, F. Wang, Yefei Liu
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引用次数: 14

Abstract

In the image inpainting process, the data term of the Criminisi algorithm depends on the shape of the manually selected target region and the confidence drops to zero rapidly, resulting in in painting sequence deviation which finally influence the in paint effect. Then we introduce the entropy to improve the data term, in this way another priority function will be defined. Experiments confirm that the improved algorithm can eliminate the dependence on the shape of the target region and the confidence will not drop to zero rapidly again. Experiments show that the algorithm will repair the image with pure texture, strong edges and purely synthetic images better.
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基于新的灰色熵优先级函数的改进犯罪识别算法
在图像补绘过程中,Criminisi算法的数据项依赖于人工选择的目标区域的形状,置信度迅速降至零,导致补绘序列偏差,最终影响补绘效果。然后我们引入熵来改进数据项,这样就定义了另一个优先级函数。实验证明,改进后的算法能够消除对目标区域形状的依赖,置信度不会再次快速降为零。实验表明,该算法对纯纹理、强边缘和纯合成图像的修复效果较好。
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