Hetzheim, Hartwig and Dooley, Laurence S.
PDF (Not Set)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
|DOI (Digital Object Identifier) Link:||https://doi.org/10.1109/ICSIGP.1996.566319|
|Google Scholar:||Look up in Google Scholar|
This paper discusses the application of three different nonparametric methods for decomposing images into regions which exhibit special stochastic properties, together with the constituent components of the stochastic. These are: (1) order statistics in connection with steps in the empirical estimated distribution functions; (2) detection of stochastic information within an image by hypothesis testing; and (3) rank order statistics to decompose the different types of stochastic within an image. The decomposition is used to isolate different image regions and to estimate the processes which are the constituent stochastic components. In order to achieve this, decisions based upon membership relations are employed and adapted thresholds used. The thresholds are obtained by the ordering of terms calculated by stochastic estimation methods together with one of the aforementioned techniques
|Item Type:||Conference Item|
|Academic Unit/School:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Laurence Dooley|
|Date Deposited:||08 Jun 2009 09:57|
|Last Modified:||26 Mar 2017 06:15|
|Share this page:|
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.