Wavelet-Based Image Interpolation Using a Three-Component Exponential Mixture Model
Jing Tian, Weiyu Yu, Shengli Xie · 2008
Wavelet-based image interpolation typically treats the input image as the low-pass filtered subbands of an unknown wavelet-transformed high-resolution image, and then produces the unknown high-resolution image by estimating the wavelet coefficients of the high-pass filtered subbands. The major challenge is to exploit the inter-scale correlation among the wavelet coefficients. In contrast to that the conventional Gaussian mixture (GM) model only exploits the magnitude information of the wavelet coefficients, a three-component exponential mixture (TCEM) model is proposed in this paper to investigate both the magnitude information and the sign information of the wavelet coefficients. The proposed TCEM model consists of a Gaussian component, a positive exponential component and a negative exponential component. Furthermore, the proposed TCEM model is exploited to develop an image interpolation approach. Experiments are conducted to demonstrate the superior performance of the proposed approach.