Synopsis
Complete Signal Representation With Multiscale Edges offers a practical vision of how multiscale edges capture a signal’s structure and texture, with stable, complete descriptions you can use in real-world imaging tasks.
This book centers on wavelet-based ideas that describe signals at multiple scales. It shows how adaptive sampling of the wavelet transform, guided by local maxima, creates edge descriptors that translate with the image and help distinguish edge types and textures. The result is a framework that not only detects edges but also supports reconstruction and compact coding, with a focus on image processing and computer vision.
- How multiscale edges provide a complete, stable description of signals and images
- Algorithms for edge detection, edge-type descriptors, and texture discrimination
- Reconstruction of signals from their multiscale edges and implications for coding
- Applications to image processing, enhancement, and pattern recognition
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About the Author
St?phane Mallat is a Professor in the Computer Science Department of the Courant Institute of Mathematical Sciences at New York University, and a Professor in the Applied Mathematics Department at ccole Polytechnique, Paris, France. He has been a visiting professor in the ElectricalEngineering Department at Massachusetts Institute of Technology and in the Applied Mathematics Department at the University of Tel Aviv. Dr. Mallat received the 1990 IEEE Signal Processing Society's paper award, the 1993 Alfred Sloan fellowship in Mathematics, the 1997Outstanding Achievement Award from the SPIE Optical Engineering Society, and the 1997 Blaise Pascal Prize in applied mathematics, from theFrench Academy of Sciences.
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