Spatial anisotropic interpolation approach for text removal from an image

dc.contributor.author Raghava, Morusupalli
dc.contributor.author Agarwal, Arun
dc.contributor.author Rao, Ch Raghavendra
dc.date.accessioned 2022-03-27T05:52:13Z
dc.date.available 2022-03-27T05:52:13Z
dc.date.issued 2013-12-01
dc.description.abstract We propose a Spatial Anisotropic Interpolation (SAI) based, Design and Analysis of Computer Experiment (DACE) model for inpainting the gaps that are induced by the removal of text from images. The spatial correlation among the design data points is exploited, leading to a model which produces estimates with zero variance at all design points. Incorporating such a feature turns the model to serve as a surrogate for predicting the response at desired points where experiment is not carried out. This property has been tuned for the purpose of gap filling in images also called as Image Inpainting, while treating the pixel values as responses. The proposed methodology restores the structural as well as textural characteristics of input image. Experiments are carried out with this methodology and results are demonstrated using quality metrics such as SSIM and PSNR. © 2013 Springer-Verlag.
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.8271 LNAI
dc.identifier.issn 03029743
dc.identifier.uri 10.1007/978-3-642-44949-9_15
dc.identifier.uri http://link.springer.com/10.1007/978-3-642-44949-9_15
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8499
dc.subject Anisotropic Interpolation
dc.subject Kriging
dc.subject Random Field
dc.subject Spatial Correlation
dc.title Spatial anisotropic interpolation approach for text removal from an image
dc.type Book Series. Conference Paper
dspace.entity.type
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