A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
A family of polynomial spline wavelet transforms
Signal Processing
Adapted wavelet analysis from theory to software
Adapted wavelet analysis from theory to software
The lifting scheme: a construction of second generation wavelets
SIAM Journal on Mathematical Analysis
CREW: Compression with Reversible Embedded Wavelets
DCC '95 Proceedings of the Conference on Data Compression
Watermarking Based on the Density Coefficients of Faber-Schauder Wavelets
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
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The Faber-Schauder wavelet transform is a simple multiscale transformation with many interesting properties in image processing. Some of these properties are: preservation of pixel ranges, arithmetic operations, non requirement of boundary processing, multiscale edge detection, elimination of the constant and the linear correlation, and the use of close neighboring information. In this study we describe this transformation and we propose a mixed scale visualization of the wavelet transform which makes it possible to show the transform result as an image. This visualization is used, with orientation information, to refine edge detection and image characterization by selecting regions with a high density of extrema wavelet coefficients.