Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99347
Title: 2D finite rate of innovation reconstruction method for step edge and polygon signals in the presence of noise
Authors: Kot, Alex Chichung
Chen, Changsheng
Marziliano, Pina
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2012
Source: Chen, C., Marziliano, P., & Kot, A. C. (2012). 2D finite rate of innovation reconstruction method for step edge and polygon signals in the presence of noise. IEEE transactions on signal processing, 60(6), 2851-2859.
Series/Report no.: IEEE transactions on signal processing
Abstract: The finite rate of innovation (FRI) principle is developed for sampling a class of non-bandlimited signals that have a finite number of degrees of freedom per unit of time, i.e., signals with FRI. This sampling scheme is later extended to three classes of sampling kernels with compact support and applied to the step edge reconstruction problem by treating the image row by row. In this paper, we regard step edges as 2D FRI signals and reconstruct them block by block. The step edge parameters are obtained from the 2D moments of a given image block. Experimentally, our technique can reconstruct the edge more precisely and track the Cramér-Rao bounds (CRBs) closely with a signal-to-noise ratio (SNR) larger than 4 dB on synthetic step edge images. Experiments on real images show that our proposed method can reconstruct the step edges under practical conditions, i.e., in the presence of various types of noise and using a real sampling kernel. The results on locating the corners of data matrix barcodes using our method also outperform some state-of-the-art barcode decoders.
URI: https://hdl.handle.net/10356/99347
http://hdl.handle.net/10220/13534
ISSN: 1053-587X
DOI: http://dx.doi.org/10.1109/TSP.2012.2189391
Rights: © 2012 IEEE
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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