Share Email Print
cover

Proceedings Paper

Wavelet domain denoising by using the universal hidden Markov tree model
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, a new image denoising method which is based on the uHMT(universal Hidden Markov Tree) model in the wavelet domain is proposed. The MAP (Maximum a Posteriori) estimate is adopted to deal with the ill-conditioned problem (such as image denoising) in the wavelet domain. The uHMT model in the wavelet domain is applied to construct a prior model for the MAP estimate. By using the optimization method Conjugate Gradient, the closest approximation to the true result is achieved. The results show that images restored by our method are much better and sharper than other methods not only visually but also quantitatively.

Paper Details

Date Published: 13 September 2008
PDF: 7 pages
Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707304 (13 September 2008); doi: 10.1117/12.794064
Show Author Affiliations
Feng Li, Australian Defence Force Academy, Univ. of New South Wales (Australia)
Donald Fraser, Australian Defence Force Academy, Univ. of New South Wales (Australia)
Xiuping Jia, Australian Defence Force Academy, Univ. of New South Wales (Australia)
Andrew Lambert, Australian Defence Force Academy, Univ. of New South Wales (Australia)


Published in SPIE Proceedings Vol. 7073:
Applications of Digital Image Processing XXXI
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top