New Approaches Based on Real and Complex Forms of Ripplet-I Transform for Image Analysis

dc.contributor.author	YAŞAR, Hüseyin
dc.contributor.author	CEYLAN, Murat
dc.date.accessioned	2020-08-07T12:56:46Z
dc.date.available	2020-08-07T12:56:46Z
dc.date.issued	2016
dc.identifier	10.1109/SIU.2016.7495847
dc.identifier.issn	9781509016792 (ISBN)
dc.identifier.uri	http://hdl.handle.net/20.500.12498/3017
dc.description.abstract	The multi resolution analysis are important parts of image processing. Curvelet transform is analysis method which have been using wide variety of applications in multi resolution analysis. Ripplet-I transform is defined by recently generalising of the curvelet transform by adding parameters support (c) and degree (d). Even though this transform has been found out recently, it has been using wide variety of applications. Fast discrete and complex fast discrete versions of ripplet-I transform were examined by this study. In denoising application, better results were obtained with fast discrete and complex fast discrete versions of ripplet-I transform by discrete ripplet-I transform. © 2016 IEEE.
dc.language.iso	Turkish
dc.publisher	Institute of Electrical and Electronics Engineers Inc.
dc.source	24th Signal Processing and Communication Application Conference, SIU 2016
dc.title	New Approaches Based on Real and Complex Forms of Ripplet-I Transform for Image Analysis
dc.type	Konferans Bildirisi