Generalized Extreme Value Distributions, Information Geometry And Sharpness Functions For Microscopy Images:
2014 (English)In: 2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014, 2867-2871 p.Conference paper (Refereed)
We introduce the generalized extreme value distributions asdescriptors of edge-related visual appearance properties. Theoreticallythese distributions are characterized by their limitingand stability properties which gives them a role similarto that of the normal distributions. Empirically we will showthat these distributions provide a good fit for images from alarge database of microscopy images with two visually verydifferent types of images. The generalized extreme value distributionsare transformed exponential distributions for whichanalytical expressions for the Fisher matrix are available. Wewill show how the determinant of the Fisher matrix and thegradient of the determinant of the Fisher matrix can be usedas sharpness functions and a combination of the determinantand the gradient information can be used to improve the qualityof the focus estimation.
Place, publisher, year, edition, pages
2014. 2867-2871 p.
, International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
generalized extreme value distribution, information geometry, edge statistics, auto-focus, imagebased screening
IdentifiersURN: urn:nbn:se:liu:diva-107139ISI: 000343655302177ISBN: 978-1-4799-2893-4OAI: oai:DiVA.org:liu-107139DiVA: diva2:722032
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Florence, Italy, May 4-9, 2014
ProjectsVirtual Photo Set, VPS