Abstract
A novel error correction scheme for image interpolation algorithms based on support vector machines (SVMs) is proposed. SVMs are trained with the interpolation error distribution of down-sampled interpolated image to estimate interpolation error of the source image. Interpolation correction is employed to the interpolated result of source image with SVMs regression to obtain more accuracy result image. Error correction results of linear, cubic and warped distance adaptive interpolation algorithms demonstrate the effectiveness of the scheme.
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© 2006 Springer-Verlag Berlin Heidelberg
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Ma, L., Ma, J., Shen, Y. (2006). Support Vector Machines Based Image Interpolation Correction Scheme. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_99
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DOI: https://doi.org/10.1007/11795131_99
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36297-5
Online ISBN: 978-3-540-36299-9
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