Wavelet-based image denoising in (digital) particle image velocimetry

Abstract

Mallat algorithm, which analyzes the evolution of the wavelet transform maxima across scales based on wavelet transform, is applied in image denoising in particle image velocimetry (PIV) in this paper. An improved interrogation method for PIV images based on cross-correlation with discrete window offset, which makes use of a translation of the second interrogation window and rebuilds it considering rotation and shear is also presented. The displacement extracted from PIV images is predicted and corrected by means of an iterative procedure. In addition, the displacement vectors are validated at each intermediate of the iteration process. The method of image denoising in PIV based on wavelet transform is compared with averaging filter, Wiener filter and median filter by interrogation of synthetic and real PIV images and the results are discussed.