Rather than attempting to separate signal from noise in the spatial domain, it is often advantageous to work in a
transform domain. Building on previous work, a novel denoising method based on local adaptive multi-scale wavelet
least squares support vector regression is proposed. Investigation on real images contaminated by Gaussian noise has
demonstrated that the proposed method can achieve an acceptable trade off between the noise removal and smoothing of
the edges and details.