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Local feature analysis using a sinusoidal signal model derived from higher-order Riesz transforms | IEEE Conference Publication | IEEE Xplore

Local feature analysis using a sinusoidal signal model derived from higher-order Riesz transforms


Abstract:

The monogenic signal consists of an image and its first-order Riesz transform. It describes signal structure as a sinusoid with a particular amplitude, phase and orientat...Show More

Abstract:

The monogenic signal consists of an image and its first-order Riesz transform. It describes signal structure as a sinusoid with a particular amplitude, phase and orientation; however, the orientation estimate is poor around certain phase values. We describe a novel method of estimating this sinusoidal signal model using higher-order Riesz transforms, such that amplitude, phase and orientation estimates are improved under noise conditions. Furthermore, the method leads to novel intrinsically-1D (line and edge) and intrinsically-2D (corner and junction) detectors.
Date of Conference: 15-18 September 2013
Date Added to IEEE Xplore: 13 February 2014
Electronic ISBN:978-1-4799-2341-0

ISSN Information:

Conference Location: Melbourne, VIC, Australia

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