Main Features:
* userfriendly and GUI based PIV tool
* multi-pass, multi-grid window deformation technique
* import bmp/ tiff/ jpeg image pairs/ series
* multiple image sequencing styles
* individual image masking and region of interest
* image pre-processing
* two different sub-pixel estimators
* multiple vector validation methods
* magnitude/ vorticity/ divergence/ shear / ...
* data smoothing, vector field highpass
* multiple colormaps
* streamlines
* extensive data extraction tools
* statistics
* synthetic PIV image generator
* Many data export features
* main features accessible via comand line scripting

Saturday, February 13, 2016

PIVlab 1.41 - now 10x faster processing!

Recently, Sergey, a Junior Researcher at the ISSP RAS contacted me and told me that he found a way to make PIVlab (specifically the DFT window deformation part) much faster. He rewrote PIV_FFTmulti.m in a way that doesn't use 'for loops' anymore. The result is a heavily improved processing speed of PIVlab. I tested MATLAB versions 2011a, 2014b and 2015a. The speed was improved by a factor between 7.9 and 10.6 for a 'standard analysis' with three passes. Improvements up to a factor of 30 seem possible.

Thanks a lot Sergey, this will save a lot of people a lot of time!!

Download: http://www.mathworks.com/matlabcentral/fileexchange/27659-pivlab-time-resolved-particle-image-velocimetry--piv--tool

7 comments:

  1. Congrats to you two. I can only agree to significant speed gain. I quickly ran my standard settings (DFT) on a stack of 15.000 images with the commandline script:
    MATLAB2013b with PIVlab4.0 - 4:28
    MATLAB2015a with PIVlab4.0 - 4:47

    MATLAB2013b with PIVlab4.1 - 1:10 h
    MATLAB2015a with PIVlab4.1 - 1:21 h

    Pretty nice. Thanks!
    Tobi

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  2. Nice!!! Congrats both of you.

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  3. Have you considered optimizing this for GPU-computing? I imagine this could further improve performance.

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  4. This MATLAB software is really fast my brother used this and found it max speed for processing which saves a lot of time.

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  5. I really appreciate that you shared this information :)
    I definitely want to learn more about this!

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  6. Really helpful and informative post. You are doing great work. Thanks for sharing and do keep us posted.

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  7. Dear all,

    I have contributed a parallel version of PIVlab in FileExchange.

    https://www.mathworks.com/matlabcentral/fileexchange/63358-parapivlab--pivlab-in-parallel

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