Fractal-wavelet image denoising revisited

TitleFractal-wavelet image denoising revisited
Publication TypeJournal Article
Year of Publication2006
AuthorsGhazel, M., G. H. Freeman, and E. R. Vrscay
JournalIEEE Transactions on Image Processing
Volume15
Pagination2669–2675
ISSN1057-7149
Abstract

The essence of fractal image denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estimate of the original image. We show how well fractal-wavelet denoising predicts parent wavelet subtress of the noiseless image. The performance of various fractal-wavelet denoising schemes (e.g., fixed partitioning, quadtree partitioning) is compared to that of some standard wavelet thresholding methods. We also examine the use of cycle spinning in fractal-based image denoising for the purpose enhancing the denoised estimates. Our experimental results show that these fractal-based image denoising methods are quite competitive with standard wavelet thresholding methods for image denoising. Finally, we compare the performance of the pixel- and wavelet-based fractal denoising schemes.

URLhttp://dx.doi.org/10.1109/TIP.2006.877377
DOI10.1109/TIP.2006.877377

a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949
Email:

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia