Presentation 2015-03-03
Image Interpolation based on Weighting Function of Gaussian
Takuro YAMAGUCHI, Yasuhiro NAKAJIMA, Masaaki IKEHARA,
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Abstract(in English) In this paper, we propose a new image interpolation method based on a 2-D piecewise stationary autoregressive (PAR) model. Soft-decision adaptive interpolation (SAI) and its improved methods which are based on PAR model are state-of-the-art methods in image interpolation. They produce upconverted images with good quality but tend to have high calculation cost because of solving the inverse matrix problem to estimate the weighting parameters. So we use Gaussian function to estimate parameters without the inverse matrix calculation and reduce the calculation cost. Moreover, parameters are estimated on pixel by pixel, while in SAI they are constant in a local window. Thanks to these, the proposed method outperforms SAI in the quality of upconversion with low calculation cost. Finally we validate the proposed method through some experimental results.
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Keyword(in English) image interpolation / Gaussian / PAR model / image modeling
Paper # EA2014-105,SIP2014-146,SP2014-168
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Conference Information
Committee SIP
Conference Date 2015/2/23(1days)
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Registration To Signal Processing (SIP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Image Interpolation based on Weighting Function of Gaussian
Sub Title (in English)
Keyword(1) image interpolation
Keyword(2) Gaussian
Keyword(3) PAR model
Keyword(4) image modeling
1st Author's Name Takuro YAMAGUCHI
1st Author's Affiliation EEE Dept., Keio Univ.()
2nd Author's Name Yasuhiro NAKAJIMA
2nd Author's Affiliation EEE Dept., Keio Univ.
3rd Author's Name Masaaki IKEHARA
3rd Author's Affiliation EEE Dept., Keio Univ.
Date 2015-03-03
Paper # EA2014-105,SIP2014-146,SP2014-168
Volume (vol) vol.114
Number (no) 474
Page pp.pp.-
#Pages 5
Date of Issue