Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84494
Title: Additive white gaussian noise level estimation in SVD domain for images
Authors: Wei Liu.
Weisi Lin.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2013
Source: Liu, W., & Lin, W. (2013). Additive white gaussian noise level estimation in SVD domain for images. IEEE transactions on image processing, 22(3), 872-883.
Series/Report no.: IEEE transactions on image processing
Abstract: Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of vision and image processing applications as it is critical to the processing techniques that follow. In this paper, a new effective noise level estimation method is proposed on the basis of the study of singular values of noise-corrupted images. Two novel aspects of this paper address the major challenges in noise estimation: 1) the use of the tail of singular values for noise estimation to alleviate the influence of the signal on the data basis for the noise estimation process and 2) the addition of known noise to estimate the content-dependent parameter, so that the proposed scheme is adaptive to visual signals, thereby enabling a wider application scope of the proposed scheme. The analysis and experiment results demonstrate that the proposed algorithm can reliably infer noise levels and show robust behavior over a wide range of visual content and noise conditions, and that is outperforms relevant existing methods.
URI: https://hdl.handle.net/10356/84494
http://hdl.handle.net/10220/18109
ISSN: 1057-7149
DOI: 10.1109/TIP.2012.2219544
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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