BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)

Non-Euclidean Pyramids

A. Muñoz Barrutia, T. Blu, M. Unser

Proceedings of the SPIE Conference on Mathematical Imaging: Wavelet Applications in Signal and Image Processing VIII, San Diego CA, USA, July 31-August 4, 2000, vol. 4119, pp. 710–720.

We propose to design the reduction operator of an image pyramid so as to minimize the approximation error in the lp sense (not restricted to the usual p = 2), where p can take non-integer values. The underlying image model is specified using arbitrary shift-invariant basis functions such as splines. The solution is determined by an iterative optimization algorithm, based on digital filtering. Its convergence is accelerated by the use of first and second derivatives. For p = 1, our modified pyramid is robust to outliers; edges are preserved better than in the standard case where p = 2. For 1 < p < 2, the pyramid decomposition combines the qualities of l1 and l2 approximations. The method is applied to edge detection and its improved performance over the standard formulation is determined. 

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AUTHOR="Mu{\~{n}}oz Barrutia, A. and Blu, T. and Unser, M.",
TITLE="Non-{E}uclidean Pyramids",
BOOKTITLE="Proceedings of the {SPIE} Conference on Mathematical
	Imaging: {W}avelet Applications in Signal and Image Processing
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