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Denoising by multiwavelet singularity detection
- Source :
- International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003.
- Publication Year :
- 2003
- Publisher :
- IEEE, 2003.
-
Abstract
- Wavelet denoising by singularity detection was proposed as an algorithm that combines Mallat and Donoho's denoising approaches. With wavelet transform modulus sum, we can avoid the error and ambiguities of tracing the modulus maxima across scales and the complicated and computationally demanding reconstruction process. We can also avoid the visual artifacts produced by shrinkage. In this paper, we investigate a multiwavelet denoising algorithm based on a modified singularity detection approach. Improved signal denoising results are obtained in comparison to the single wavelet case.
- Subjects :
- Computer science
business.industry
Second-generation wavelet transform
MathematicsofComputing_NUMERICALANALYSIS
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Wavelet transform
Pattern recognition
Data_CODINGANDINFORMATIONTHEORY
Total variation denoising
Wavelet packet decomposition
ComputingMethodologies_PATTERNRECOGNITION
Wavelet
Singularity
ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION
Video denoising
Step detection
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003
- Accession number :
- edsair.doi...........bdb8ce4ee7e8c1b4a17b02a2ad0afde7
- Full Text :
- https://doi.org/10.1109/icnnsp.2003.1279349