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 |
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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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