Translator Disclaimer
Paper
6 September 2019 Stationarity testing in 2D image analysis
Author Affiliations +
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jaromír Kukal, Iva Nachtigalová, Zuzana Krbcová, Jan Švihlík, and Karel Fliegel "Stationarity testing in 2D image analysis", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372G (6 September 2019); https://doi.org/10.1117/12.2529346
PROCEEDINGS
8 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT


Back to Top