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

Marchant, Ross, and Jackway, Paul (2013) Local feature analysis using a sinusoidal signal model derived from higher-order Riesz transforms. In: Proceedings of the 20th IEEE International Conference on Image Processing. pp. 3489-3493. From: ICIP 2013: 20th IEEE International Conference on Image Processing, 15-18 September 2013, Melbourne, VIC, Australia.

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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 sig- nal model using higher-order Riesz transforms, such that am- plitude, 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.

Item ID: 33304
Item Type: Conference Item (Research - E1)
ISBN: 978-1-4799-2341-0
Keywords: Riesz transform, image processing, feature analysis
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Funders: Australian Postgraduate Award, CSIRO, School of Engineering and Physical Sciences
Date Deposited: 23 May 2014 04:42
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 50%
97 EXPANDING KNOWLEDGE > 970109 Expanding Knowledge in Engineering @ 50%
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