Image interpolation based on weighting function of Gaussian
Takuro Yamaguchi, Masaaki Ikehara, Y. Nakajima · 2015
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.