Block Based Deconvolution Algorithm Using Spline Wavelet Packets
Abstract
This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the algorithm and an explicit representation of the solutions. The presented algorithms provide stable solutions that accurately approximate the original objects.
Main Authors
Format
Articles
Research article
Published
2010
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201901171233Use this for linking
Review status
Peer reviewed
ISSN
0924-9907
DOI
https://doi.org/10.1007/s10851-010-0224-4
Language
English
Published in
Journal of Mathematical Imaging and Vision
Citation
- Averbuch, A., Zheludev, V., Neittaanmäki, P., & Koren, J. (2010). Block Based Deconvolution Algorithm Using Spline Wavelet Packets. Journal of Mathematical Imaging and Vision, 38(3), 197-225. https://doi.org/10.1007/s10851-010-0224-4
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The material is available for reading at the archive workstation of the University of Jyväskylä Library.
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