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

Konferenzbeitrag

Links:
Autoren:

Tan-Toan Le
Mathias Ziebarth
Thomas Greiner
Michael Heizmann

Quelle:

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

Seiten:

1672-1676

Konferenz:

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