A K-nearest neighbor-based method for the restoration of damaged images
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摘要
The present paper deals with the problem of restoring a digital image starting from its random sampling or its damaged version. The method is adaptive and uses local evaluation of the kernel parameters. Applications of the method on simulated and real data are presented and its performance on the reconstruction of very sparse images is shown.
论文关键词：Convolution,Filtering,Sparse images,Information theory,Biological image analysis,Image random sampling,Data compression
论文评审过程：Received 17 August 1988, Revised 27 January 1989, Available online 19 May 2003.
论文官网地址：https://doi.org/10.1016/0031-3203(90)90058-S
