Boundary effect in a wavelet multi resolution analysis

What are the methods to minimize the effect of boundaries in a wavelet decomposition?

I use R and the package waveslim.

I have found for instance the function



  1. I am not too use how to use it.

  2. I am not sure the best solution is to remove some coefficient. I have read somewhere that it exists some wavelets that are not the same everywhere and their shape change at the boudaries.

Any ideas?


I think this is a good question and I don’t kown much about implementations. Since wavelet is ‘mutli-resolution’ you have two types of solutions (which are somehow connected):

  1. Modify your signal for example extend you signal over the actual boundary to have meaningfull coefficients.
    Exemples of that are :

    • periodic wavelet on the interval
    • Zero padding (extend the signal by zero outside ist domain
    • finer prodecure are extensions of zero padding with smoothness condition at the boundary.
  2. Modify the wavelet (somehow equivalent to threshold or lower wavelet coefficient that are near the boundary). More generally, there are procedures I know there have been many work since that of A Cohen I Daubechies et P Vial 1993. For example, in (Monasse and Perrier, 1995), wavelet that forms a basis adapted to conditions such as Dirichlet or Neumann are constructed. I guess some are implemented ? If you found implementations, I am interested.


Monasse and Perrier : 1995 CRAS Ondelettes sur lintervalle pour la prise en compte de conditions aux limites

A Cohen I Daubechies et P Vial Wavelets on the interval and fast wavelet transforms Appl Comp Harmonic Analysis (1993)

Source : Link , Question Author : RockScience , Answer Author : robin girard

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