Information Technology for Medical Data Stream Mining

Perova, Iryna; Brazhnykova, Yelizaveta; Miroshnychenko, Nelia; Bodyanskiy, Yevgeniy

doi:10.1109/tcset49122.2020.235399

Cited by 4 publications

(1 citation statement)

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“…The study showed that the use of the devised procedure reduces identification errors with cataloged (reference) objects by 5-7 times [18]. Statistical modeling [38] has proven that this significantly affects the quality and accuracy of a number of data acquisition and retrieval tasks [39]. This also affects brightness estimation and detection of object trajectories [40,41] using supercomputers [42].…”

Section: Discussion Of Results Of Investigating the Procedures For Br...mentioning

confidence: 99%

Devising a procedure for the brightness alignment of astronomical frames background by a high frequency filtration to improve accuracy of the brightness estimation of objects

Vlasenko,

Khlamov,

Savanevych

2024

EEJET

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The object of this study is the background substrate of astronomical frames. To detect and compare the image of an object in a frame with its real image from astronomical catalogs, it is necessary to uniformly distribute the brightness of the background image substrate. Most often, the background alignment of astronomical frames is performed using the hardware calibration method applying the construction of service frames. However, it does not make it possible to eliminate the background from temporary stray light. Therefore, to solve this problem, a procedure has been proposed for brightness alignment of the background frame using high-pass filtering. For high-pass filtering of images, three high-pass filters were considered – an ideal filter, a Butterworth filter, and a Gaussian filter. To remove coarse-grained image components from the image, a high-pass filter was used, which attenuates low-frequency harmonics of the image spectrum while simultaneously passing high-frequency harmonics. Applying the devised procedure for brightness alignment of the background substrate of the frame has made it possible to increase the signal-to-noise ratio and reduce the dynamic range of the background substrate of the image. The study showed that when assessing brightness and identifying frames, the fitting provides better accuracy of reference to the starry sky. Also, the standard deviation of frame identification errors in this case is 5–7 times less than without using the devised procedure. The devised procedure for brightness alignment of the background frame substrate was tested in practice within the framework of the CoLiTec project. It was implemented at the stage of intra-frame processing in the Lemur software for automated detection of new objects and tracking of known objects

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