A New Wavelet Based Image Denoising Method

This paper proposes a new wavelet based image denoising method by using linear elementary parameterized denoising functions in the form of derivatives of Gaussian of a set of estimated wavelet coefficients. These coefficients are derived from an improved context modeling procedure in terms of mean square error estimation combining inter- and intra-sub band data. The denoising method results in a two-step denoising effort which outperforms the state-of-the-art non-redundant methods. This method is also extended to the over complete wavelet expansion by applying cycle spinning, which provides additional denoising performance and yields significantly better results than the orthogonal transform.