基于小波域隐马尔可夫模型的图像降噪，性能最好的图像降噪程序。 -Based on wavelet-domain Hidden Markov Model of image noise, the performance of the best image noise reduction procedures.

Decompose image into subbands, denoise, and recompose again. fh = decomp_reconst(im,Nsc,Nor,block,noise,parent,covariance,optim,sig) covariance: are we considering covariance or just variance? optim: for choosing between BLS-GSM (opti

Decompose image into subbands, denoise using BLS-GSM method, and recompose again. fh = decomp_reconst(im,Nsc,filter,block,noise,parent,covariance,optim,sig) im: image Nsc: number of scales filter: type of filter used (see namedFilt

Decompose image into subbands (undecimated wavelet), denoise, and recompose again. fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig) im : image Nsc: Number of scales daub_order: Order of the daubec