Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Particle image velocimetry (PIV) is a method used to measure the velocity field of a fluid flow. Traditionally, cross correlation algorithms are used to retrieve the flow velocity. Recently, a new method for PIV based on the L$^2$ optimal mass transportation problem (OT-PIV) was introduced and analyzed in [L. P. Saumier, B. Khouider, and M. Agueh, Comm. Math. Sci., 13 (2015), pp. 269--296] for the case of synthetically generated data and for particles of equal mass or brightness. Here,  extend the work of Saumier et al. to the case of particles with different masses and randomly seeded particles. More importantly,  compare the OT-PIV method with a typical cross-correlation algorithm for the case of real data. Using a combination of theory and numerical experiments,  demonstrate that in the presence of particles with different ights/brightness, the OT method is more accurate for the largest/brightest particles, and it is more faithful when the particles are far enough from each other. This makes it...
['Louis-Philippe Saumier', 'Boualem Khouider', 'Martial Agueh']
I am writing a research paper on a idea Optimal Transport for Particle Image Velocimetry: Real Data and Postprocessing Algorithms
[{"from": "human", "value": "I am writing a research paper on a idea Optimal Transport for Particle Image Velocimetry: Real Data and Postprocessing Algorithms"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Particle image velocimetry (PIV) is a method used to measure the velocity field of a fluid flow. Traditionally, cross correlation algorithms are used to retrieve the flow velocity. Recently, a new method for PIV based on the L$^2$ optimal mass transportation problem (OT-PIV) was introduced and analyzed in [L. P. Saumier, B. Khouider, and M. Agueh, Comm. Math. Sci., 13 (2015), pp. 269--296] for the case of synthetically generated data and for particles of equal mass or brightness. Here,  extend the work of Saumier et al. to the case of particles with different masses and randomly seeded particles. More importantly,  compare the OT-PIV method with a typical cross-correlation algorithm for the case of real data. Using a combination of theory and numerical experiments,  demonstrate that in the presence of particles with different ights/brightness, the OT method is more accurate for the largest/brightest particles, and it is more faithful when the particles are far enough from each other. This makes it..."}]