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Optimized size-adaptive feature extraction based on content-matched rational wavelet filters

Conference paper


Tan-Toan Le
Mathias Ziebarth
Thomas Greiner
Michael Heizmann


Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), IEEE , 2014.




Signal Processing Conference (EUSIPCO) 2014, Lisbon, Portugal, September 1 - 5, 2014

One of the challenges of feature extraction in image processing is caused by the fact that objects originating from a feature class don't always appear in a unique size, and the feature sizes are diverse. Hence, a multiresolution analysis using wavelets should be suitable. Because of their integer scaling factors classical dyadic or M-channel wavelet filter banks often don't match very well the corresponding feature sizes occurring within the image. This paper presents a new method to optimally extract features in different sizes by ...