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Proceedings Paper

Stationarity testing in 2D image analysis
Author(s): Jaromír Kukal; Iva Nachtigalová; Zuzana Krbcová; Jan Švihlík; Karel Fliegel
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Paper Abstract

Signal and image stationarity is the basic assumption for many methods of their analysis. However this assumption is not true in a lot of real cases. The paper is focused on local stationary testing using a small symmetric neighbourhood. The neighbourhood is split into two parts which should have the same statistical properties when the hypothesis of image stationarity is valid. We apply various testing approaches (two-sampled F-test, t-test, WMW, K-S) to obtain adequate p-values for given pixel, mask position, and test type. Finally, using battery of masks and tests, we obtain the series of p-values for every pixel. Applying False Discovery Rate (FDR) methodology, we localize all the pixels when any hypothesis falls. Resulting binary image is an alternative to traditional edge detection but with strong statistical background.

Paper Details

Date Published: 6 September 2019
PDF: 8 pages
Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372G (6 September 2019);
Show Author Affiliations
Jaromír Kukal, Univ. of Chemistry and Technology Prague (Czech Republic)
Iva Nachtigalová, Univ. of Chemistry and Technology Prague (Czech Republic)
Zuzana Krbcová, Univ. of Chemistry and Technology Prague (Czech Republic)
Jan Švihlík, Univ. of Chemistry and Technology Prague (Czech Republic)
Czech Technical Univ. in Prague (Czech Republic)
Karel Fliegel, Czech Technical Univ. in Prague (Czech Republic)


Published in SPIE Proceedings Vol. 11137:
Applications of Digital Image Processing XLII
Andrew G. Tescher; Touradj Ebrahimi, Editor(s)

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