Image interpolation based on inter-scale dependency in wavelet domain
Image interpolation based on inter-scale dependency in wavelet domain
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DOI：
10.1109/icip.2004.1421396
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发表时间：
2004-10
期刊：
影响因子：
--
通讯作者：
D. Woo;I. Eom;Y. Kim
中科院分区：
文献类型：
--
作者：
D. Woo;I. Eom;Y. Kim
小波域图像插值可以看作是对最高频率子带小波系数的估计。提出了一种基于小波域尺度间相关性的图像插值方法。在我们的方法中，高斯混合模型（GMM）被用来估计的小波系数的幅度，和GMM的参数来自子带未经训练。利用小波子带的尺度间相关性，得到了估计小波系数的符号。仿真结果表明，与传统的双三次方法和统计方法（K。Kinebuchi等人，2001年5月），利用隐马尔可夫树（HMT）模型与训练。
Image interpolation in the wavelet domain can be considered as the estimation of wavelet coefficients in the highest frequency subband. In this paper, a novel image interpolation method based on inter-scale dependency in the wavelet domain is proposed. In our method, the Gaussian mixture model (GMM) is used to estimate the magnitude of the wavelet coefficient, and the parameters of the GMM are derived from subbands with no training. The sign of the estimated wavelet coefficient is also obtained by using the inter-scale dependency of wavelet subbands. In the simulation results, the proposed method shows an improved PSNR and subjective quality compared with conventional bicubic method and the statistical method (K. Kinebuchi et al., May, 2001) that exploits the hidden Markov tree (HMT) model with training.