Paper
4 September 2009 Wavelet primal sketch representation using Marr wavelet pyramid and its reconstruction
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Abstract
Based on the class of complex gradient-Laplace operators, we show the design of a non-separable two-dimensional wavelet basis from a single and analytically defined generator wavelet function. The wavelet decomposition is implemented by an efficient FFT-based filterbank. By allowing for slight redundancy, we obtain the Marr wavelet pyramid decomposition that features improved translation-invariance and steerability. The link with Marr's theory of early vision is due to the replication of the essential processing steps (Gaussian smoothing, Laplacian, orientation detection). Finally, we show how to find a compact multiscale primal sketch of the image, and how to reconstruct an image from it.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dimitri Van De Ville and Michael Unser "Wavelet primal sketch representation using Marr wavelet pyramid and its reconstruction", Proc. SPIE 7446, Wavelets XIII, 74460W (4 September 2009); https://doi.org/10.1117/12.825972
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KEYWORDS
Wavelets

Reconstruction algorithms

Projection systems

Transform theory

Wavelet transforms

Image processing

Smoothing

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