Wavelet Shrinkage Denoising

Three iterations of the discrete wavelet transform are computed using the Daubechies six-term filter. The wavelet transform splits the data into lowpass (approximation) portions and highpass (detail) portions. Wavelet shrinkage reduces the magnitude of terms in the highpass portions. Finally, the wavelet transform is inverted to get the denoised version of the data. The blue and purple curves are the plots of the clean and denoised data (points joined) and the tan points are the plot of the noisy data. The amount of shrinkage is controlled by the tolerance, .