Paper Info
Title
Interpolation-based image inpainting in color images using high dimensional model representation.
Abstract
Image inpainting is the process of filling missing or fixing corrupted regions in a given image. The intensity values of the pixels in missing area are expected to be associated with the pixels in the surrounding area. Interpolation-based methods that can solve the problem with a high accuracy may become inefficient when the dimension of the data increases. We solve this problem by representing images with lower dimensions using High Dimensional Model Representation method. We then perform Lagrange interpolation on the lower dimensional data to find the intensity values of the missing pixels. In order to use High Dimensional Model Representation method and to improve the accuracy of Lagrange interpolation, we also propose a procedure that decompose missing regions into smaller ones and perform inpainting hierarchically starting from the smallest region. Experimental results demonstrate that the proposed method produces better results than the variational and exemplar-based inpainting approaches in most of the test images.
Year
Venue
Field
2016
European Signal Processing Conference
Computer vision,Nearest-neighbor interpolation,Multivariate interpolation,Bicubic interpolation,Interpolation,Algorithm,Stairstep interpolation,Inpainting,Artificial intelligence,High-dimensional model representation,Image scaling,Mathematics
DocType
ISSN
Citations 
Conference
2076-1465
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Efsun Karaca100.34
M. Alper Tunga2405.44