Recommended resources for noise reduction I know the question What Resources Are Recommended for an Introduction to Signal Processing (DSP)? and I have already read some general DSP books, such as Rick Lyons's "Understanding DSP,"  and also have browsed through Oppenheim's.

More specifically, what (printed) book would you recommend for denoising techniques in general? 

Including techniques adapted for audio, spectral subtraction,  Wiener filtering,  etc. and if possible adapted to discrete signal processing with an algorithm/engineering point of view
  (i.e. rather x[k] than continuous x(t) and integrals...)

I just ordered a used version of Advanced digital signal processing and noise reduction, Vaseghi, but I'm looking for other recommendations.
Signal denosing is a well-studied technique in signal processing. It first began using simple techniques such as filtering. In this approach, the emphasis is laid on designing filters which can perform denosing techniques in a fast and efficient manner.

Later, when wavelet theory was developed, some researchers used wavelets to denosing the signal. Essentially, we can apply thresholding techniques (soft or hard threshold) on the coefficients of the wavelets. On reconstruction using the dominant coefficients, one can denoise the signal.

In the early 2000s, sparsity-based techniques were introduced where the input signal is represented using an over complete dictionary. In the reconstruction step, sparsity inducing norms were used to extract only the dominant columns of the dictionary. Popular approaches include LASSO and total variation denosing.

Reference


Useful reference with MATLAB codes http://www.numerical-tours.com/matlab/