Estimation of Errors in the Transverse Velocity Vectors Determined from HINODE/SOT Magnetograms Using the NAVE Technique

Details Estimation of Errors in the Transverse Velocity Vectors Determined from HINODE/SOT Magnetograms Using the NAVE Technique Estimation of Errors in the Transverse Velocity Vectors Determined from HINODE/SOT Magnetograms Using the NAVE Technique

Jun 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009jkas...42...61c&link_type=abstract

Journal of the Korean Astronomical Society, vol. 42, no. 3, pp. 61-69

Computer Science

Performance

2

Methods: Data Analysis, Sun: Atmospheric Motions, Techniques: Image Processing

Scientific paper

Transverse velocity vectors can be determined from a pair of images successively taken with a time interval using an optical flow technique. We have tested the performance of the new technique called NAVE (non-linear affine velocity estimator) recently implemented by Chae & Sakurai using real image data taken by the Narrowband Filter Imager (NFI) of the Solar Optical Telescope (SOT) aboard the Hinode satellite. We have developed two methods of estimating the errors in the determination of velocity vectors, one resulting from the non-linear fitting σ_v and the other ɛ_u resulting from the statistics of the determined velocity vectors. The real error is expected to be somewhere between σ_v and ɛ_u. We have investigated the dependence of the determined velocity vectors and their errors on the different parameters such as the critical speed for the subsonic filtering, the width of the localizing window, the time interval between two successive images, and the signal-to-noise ratio of the feature. With the choice of v_{crit}=2 pixel/step for the subsonic filtering, and the window FWHM of 16 pixels, and the time interval of one step (2 minutes), we find that the errors of velocity vectors determined using the NAVE range from around 0.04 pixel/step in high signal-to-noise ratio features (S/N ˜ 10), to 0.1 pixel/step in low signa-to-noise ratio features (S/N ˜ 3) with the mean of about 0.06 pixel/step where 1 pixel/step corresponds roughly to 1 km/s in our case.

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