Image super-resolution based on image adaptive decomposition
Qiwei Xie, Haiyan Wang, Lijun Shen, Xi Chen, Hua Han · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.