Particle image velocimetry (PIV) vector image data of a uniform flow and of arbitrary length is decomposed using a new modal wavelet transform with both Dirichlet and Neumann boundary conditions. The Neumann boundary condition is found to be most suitable for PIV vector image data of a uniform flow. It is also found that when the summation of multi-resolution data is performed for more than 10 levels, the number and severity of error vector increases.

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