Abstract
In this paper, we propose a new image interpolation method based on a 2-D piecewise stationary autoregressive (PAR) model. SAI, which defined PAR model, is a state-of-the-art method in image interpolation. It produces good quality restored images but has high calculation cost because of solving multiple least-square problems. Our method utilizes Gaussian function in estimating parameters instead of solving least-square problems and reduces the calculation cost. Moreover, parameters are estimated at each pixel, while they are estimated in each local window in SAI. By these improvements, the proposed method has equivalent quality to SAI with low calculation cost.
| Original language | English |
|---|---|
| Title of host publication | Conference Record - Asilomar Conference on Signals, Systems and Computers |
| Publisher | IEEE Computer Society |
| Pages | 1193-1197 |
| Number of pages | 5 |
| Volume | 2016-February |
| ISBN (Print) | 9781467385763 |
| DOIs | |
| Publication status | Published - 2016 Feb 26 |
| Event | 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 - Pacific Grove, United States Duration: 2015 Nov 8 → 2015 Nov 11 |
Other
| Other | 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 |
|---|---|
| Country | United States |
| City | Pacific Grove |
| Period | 15/11/8 → 15/11/11 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Signal Processing
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Cite this
Yamaguchi, T., Ikehara, M., & Nakajima, Y. (2016). Image interpolation based on weighting function of Gaussian. In Conference Record - Asilomar Conference on Signals, Systems and Computers (Vol. 2016-February, pp. 1193-1197). [7421329] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2015.7421329