Image interpolation for high-resolution display based on the complex dual-tree wavelet transform and hidden Markov model

This paper presents a new method for the interpolation of a full high-definition (HD) image based on the dual-tree complex wavelet transform (DT-CWT) and hidden markov model (HMM). In the proposed method, the DT-CWT is used to decompose the low-resolution image into different subbands. In wavelet domain interpolation, given image is assumed as the low frequency LL subband of the wavelet coefficients of a high-resolution image. The proposed method estimates the higher band coefficients by learning the correlation between the coefficients across the scale. In this paper, the relationship between the wavelet coefficients across the scale is described by HMM, and each wavelet coefficient is modeled by a Gaussian mixture having multiple means and variances. Experimental results show that the proposed algorithm yields images that are sharper compared to several other methods that we have considered in this paper.