BayWave: BAYesian WAVElet-based image estimation Online publication date: Wed, 30-Jun-2010
by Amit Pande, Sparsh Mittal
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 2, No. 4, 2009
Abstract: Image denoising is an important step in image compression and other image processing algorithms. Hard and soft thresholding algorithms are often used to denoise the images. Recently wavelet transform has been used as a tool to denoise the images. However, there are problems associated with the thresholding algorithms. There is no subjective way to determine the threshold. In this work, we implement a simple Bayesian theory to obtain optimal threshold for such algorithms. MATLAB simulations were performed to validate the working of Bayesian thresholding method.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com