Wavelet-based image denoising using nonstationary stochastic geometrical image priors

Sviatoslav V. Voloshynovskiy; Oleksiy Koval; Thierry Pun

doi:10.1117/12.476590

7 May 2003 Wavelet-based image denoising using nonstationary stochastic geometrical image priors

Sviatoslav V. Voloshynovskiy, Oleksiy Koval, Thierry Pun

Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476590
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

In this paper a novel stochastic image model in the transform domain is presented and its superior performance in image denoising applications is demonstrated. The proposed model exploits local subband image statistics and is based on geometrical priors. Contrarily to complex models based on local correlations, or to mixture models, the proposed model performs a partition of the image into non-overlapping regions with distinctive statistics. A close form analytical solution of the image denoising problem for AWGN is derived and its performance bounds are analyzed. Despite being very simple, the proposed stochastic image model provides a number of advantages in comparison to the existing approaches: (a) simplicity of stochastic image modeling; (b) completeness of the model, taking into account multiresolution, non-stationary image behavior, geometrical priors and providing an excellent fit to the global image statistics; (c) very low complexity of the algorithm; (d) tractabiity of the model and of the obtained results due to the closed-form solution and to the existence of analytical performance bounds; (e) extensibility to different transform domains, such as orthogonal, biorthogonal and overcomplete data representations. The results of benchmarking with the state-of-the-art image denoising methods demonstrate the superior performance of the proposed approach.

Citation Download Citation

Sviatoslav V. Voloshynovskiy, Oleksiy Koval, and Thierry Pun "Wavelet-based image denoising using nonstationary stochastic geometrical image priors", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476590

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available