Image Denoising Using Local Contextual Hidden Markov Model Based on Complex Wavelet
Licheng Jiao · Dianzi xuebao · 2005
Multiresolution signal and image models aim to capture the statistical structure of smooth and singular regions.Unfortunately,models based on orthogonal wavelet transform suffer from shift-variance,which makes them be less accurate and real-time.In this paper,we extend the local contextual hidden markov model(LCHMM)modeling framework to the complex wavelet transform and proposed a new model,called local contextual markov model based on complex wavelet(C-LCHMM),which features near shift-invariance and improved angular resolution and can exploit the local statistics of wavelet coefficients at a low computational complexity.