Nondecimated Wavelet Image Denoising Based on Context Model

A new nondecimated wavelet transform image denoising method which is based on context model is proposed in this paper.In nondecimated wavelet transform,the wavelet coefficients are not decimated when the image is decomposed,which is different from traditional orthogonal wavelet transform.After the decomposition,each wavelet coefficient is modeled as a random variable of generalized Gaussian distribution.Context model is applied to estimate edge variance of each wavelet coefficient.The construction of soft -threshold function greatly considers the relativity of being threshold coefficient and its neighbor and then,the spatial adaptive threshold is produced.From experiment results,we can see that compared with other traditional denoising methods,our method can not only greatly improve denoising effect and have better reconstruction visual effect,but also enhances the Signal to Noise Ratio(SNR).