In this paper, a Bayesian wavelet denoising procedure for multicomponent images is proposed. The procedure makes use of a noise-free single component image as prior information. T...
In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
In this paper, we propose the complex Gaussian scale mixture (CGSM) to model the complex wavelet coefficients as an extension of the Gaussian scale mixture (GSM), which is for real...
Yothin Rakvongthai, An P. N. Vo, Soontorn Oraintar...
In this paper we propose a novel order-recursive training algorithm for kernel-based discriminants which is computationally efficient. We integrate this method in a hybrid HMM-bas...
A method for removing additive Gaussian noise from digital images is described. It is based on statistical modeling of the coefficients of a redundant, oriented, complex multiscale...