IPOL Journal · Image Processing On Line
- published
- 2014-04-03
- reference
- Boshra Rajaei, An Analysis and Improvement of the BLS-GSM Denoising Method, Image Processing On Line, 4 (2014), pp. 44–70. https://doi.org/10.5201/ipol.2014.86
Communicated by Pablo Musé
Demo edited by Miguel Colom
Abstract
Modeling image properties using Gaussian scale mixture (GSM) model in a multiresolution transform space is the basic idea of a denoising algorithm proposed by Portilla et al. Under this model and using the correlations between pyramid coefficients, the Bayesian least squares (BLS) of each coefficient is used to estimate its original value. In this article, we analyze and discuss the BLS-GSM algorithm, its drawbacks and benefits in more detail. An analytical parameter study of this denoising approach is provided as well. Additionally, we propose a localized version of this algorithm and experimentally show that it outperforms the original method both numerically and visually. We also show that the resulting method is state-of-the-art in terms of PSNR.
Download
- full text manuscript: PDF low-res. (2.3M) PDF (12.8M) [?]
- source code: TAR/GZ
History
- the original source code was modified on 2020-11-25 to include the possibility to denoise with the given STD parameter without re-noising the input image. The original version of the code is available here
- the README file of the source code was updated on 2021-02-20. The previous version of the code is available here
- Note from the editor: the manuscript of the article was modified on 2022-01-01 to include information about its editors. The original version of the manuscript is available here.
