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.