@inproceedings {395,
	title = {A combined Bayesshrink wavelet-ridgelet technique for image denoising},
	booktitle = {2006 IEEE International Conference on Multimedia and Expo},
	year = {2006},
	abstract = {<p>In this paper a combined Bayesshrink wavelet-ridgelet de-noising method is presented. In our previous work we have showed that Bayesshrink ridgelet performs better than Visushrink ridgelet and Visushrink wavelet. Although our Bayesshrink ridgelet technique performs somewhat poorer in comparison with Bayesshrink wavelet, based on SNR, visually it produces smoother results, especially for images with straight lines. In the proposed method Bayesshrink wavelet is combined with Bayesshrink ridgelet denoising method which performs better than each filter individually. The proposed combined denoising method gains the advantage of each filter in its specific domain, i.e., wavelet for natural and ridgelet for straight regions, and produces better and smoother results, both visually and in terms of SNR</p>
},
	keywords = {Bayes methods, Bayesshrink wavelet ridgelet technique, filtering theory, Image Denoising, image denoising method, wavelet transforms},
	doi = {http://dx.doi.org/10.1109/ICME.2006.262931},
	author = {N Nezamoddin Kachouie and P Fieguth}
}
