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  • Research Article
  • Open Access

Image Informative Maps for Estimating Noise Standard Deviation and Texture Parameters

EURASIP Journal on Advances in Signal Processing20112011:806516

https://doi.org/10.1155/2011/806516

  • Received: 7 December 2010
  • Accepted: 21 February 2011
  • Published:

Abstract

The problem of automatic detection of image areas appropriate for accurate estimation of additive noise standard deviation (STD) irrespectively to processed image properties is considered in this paper. For accurate estimation of either image texture or noise STD, we distinguish two complementary informative maps: noise- (NI-) and texture- (TI-) informative ones. The NI map is determined and iteratively upgraded based on the Fisher information on noise STD calculated in scanning window (SW) fashion. Fractional Brownian motion (fBm) model for image texture is used to derive the required Fisher information. To extract final noise STD from NI map, fBm- and DCT-based estimators are implemented. The performance of these two estimators is comparatively assessed on large image database for different noise levels. It is also compared with performance of two competitive state-of-the-art estimators recently published. Utilizing NI map along with DCT-based noise STD estimator has proved to be significantly more efficient.

Keywords

  • Additive Noise
  • Fisher Information
  • Image Database
  • Image Texture
  • Automatic Detection

Publisher note

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Authors’ Affiliations

(1)
TSI2M Laboratory, University of Rennes 1, BP 80518, 22305 Lannion cedex, France
(2)
Department of Design of Aircraft Radio-Electronic Systems, National Aerospace University (Kharkov Aviation Institute), 17 Chkalova Street, 61070 Kharkov, Ukraine
(3)
Department of Receivers, Transmitters and Signal Processing, National Aerospace University (Kharkov Aviation Institute), 17 Chkalova Street, 61070 Kharkov, Ukraine

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