文件名称:IJIT-1206_14(2)
- 所属分类：
- 图形图像处理(光照,映射..)
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- [PDF]
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- 2012-11-26
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- 268kb
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- pa***
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In this paper, we propose a novel algorithm for image inpainting based on compactly supported
radial basis functions (CSRBF) interpolation. The algorithm converts 2D image inpainting problem
into implict surface reconstruction problem from 3D points set. Firstly, we construct the implicit
surface for approximating the points set which convert from damaged image by using radial basis
functions (RBF), and then resample from the constructed surface can evaluate the pixels’ value of
damaged or removed portion on the image. Using compactly supported radial basis functions, the
matrix of corresponding system of the linear algebraic equations is spare and bounded. So it can
decrease the computational complexity of RBF algorithm. Experiments show that good results are
obtained by using the proposed algorithm. -In this paper, we propose a novel algorithm for image inpainting based on compactly supported
radial basis functions (CSRBF) interpolation. The algorithm converts 2D image inpainting problem
into implict surface reconstruction problem from 3D points set. Firstly, we construct the implicit
surface for approximating the points set which convert from damaged image by using radial basis
functions (RBF), and then resample from the constructed surface can evaluate the pixels’ value of
damaged or removed portion on the image. Using compactly supported radial basis functions, the
matrix of corresponding system of the linear algebraic equations is spare and bounded. So it can
decrease the computational complexity of RBF algorithm. Experiments show that good results are
obtained by using the proposed algorithm.
radial basis functions (CSRBF) interpolation. The algorithm converts 2D image inpainting problem
into implict surface reconstruction problem from 3D points set. Firstly, we construct the implicit
surface for approximating the points set which convert from damaged image by using radial basis
functions (RBF), and then resample from the constructed surface can evaluate the pixels’ value of
damaged or removed portion on the image. Using compactly supported radial basis functions, the
matrix of corresponding system of the linear algebraic equations is spare and bounded. So it can
decrease the computational complexity of RBF algorithm. Experiments show that good results are
obtained by using the proposed algorithm. -In this paper, we propose a novel algorithm for image inpainting based on compactly supported
radial basis functions (CSRBF) interpolation. The algorithm converts 2D image inpainting problem
into implict surface reconstruction problem from 3D points set. Firstly, we construct the implicit
surface for approximating the points set which convert from damaged image by using radial basis
functions (RBF), and then resample from the constructed surface can evaluate the pixels’ value of
damaged or removed portion on the image. Using compactly supported radial basis functions, the
matrix of corresponding system of the linear algebraic equations is spare and bounded. So it can
decrease the computational complexity of RBF algorithm. Experiments show that good results are
obtained by using the proposed algorithm.
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IJIT-1206_14(2).pdf