POD-based Background Removal for Particle Image Velocimetry

M A Mendez, M. Raiola, Alessandro Masullo, S. Discetti, A. Ianiro, Raf Theunissen, J.-M. Buchlin

Research output: Contribution to journalArticle (Academic Journal)peer-review

68 Citations (Scopus)
352 Downloads (Pure)


State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time-dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based on the Proper Orthogonal Decomposition (POD) of the image recording sequence and exploits the different spatial and temporal coherence of background and particles. After describing the theoretical framework, the method is tested on synthetic and experimental images, and compared with well-known pre-processing techniques in terms of image quality enhancement, improvements in the PIV interrogation and computational cost. The results show that, unlike existing techniques, the proposed method is robust in the presence of significant background noise intensity, gradients, and temporal oscillations. Moreover, the computational cost is one to two orders of magnitude lower than conventional image normalization methods. A downloadable version of the preprocessing toolbox has been made available at http://seis.bris.ac.uk/aexrt/PIVPODPreprocessing/.
Original languageEnglish
Pages (from-to)181-192
Number of pages12
JournalExperimental Thermal and Fluid Science
Early online date20 Aug 2016
Publication statusPublished - Jan 2017


  • PIV Image Pre-Processing
  • POD Decomposition of Video Sequences
  • Reduced Order Modeling (ROM)


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