Structure-oriented multidirectional wiener filter for denoising of image and video signals

Mohammed Ghazal, Aishy Amer, Ali Ghrayeb

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

In this letter, we propose a structure-oriented multi-directional Wiener filter to reduce additive white Gaussian noise in image and video signals. A local activity profile based on second derivatives is used to restrict filtering to homogeneous directions to combat blurring. The proposed filter improves the Wiener estimate of denoised pixels to reduce the residual blurring of the conventional Wiener filter while achieving higher noise-reduction gains of up to 5.6 dB peak signal-to-noise-ratio (PSNR). The parameters of the proposed filter (block size, shape and coefficients) are adapted to image structure and noise level for optimization with respect to noise-reduction gain and structure preservation. The effectiveness of the proposed method is shown using both the PSNR and the modulation transfer function calculated for a range of spatial frequencies to measure the degradation in contrast due to blurring. Our results show that the proposed method achieves a higher contrast transfer ratio than the conventional Wiener filter indicating improved preservation of high frequency content. We also show the performance of the proposed filter relative to reference anisotropic diffusion and wavelet methods.

Original languageEnglish
Article number4625975
Pages (from-to)1797-1802
Number of pages6
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume18
Issue number12
DOIs
Publication statusPublished - Dec 2008
Externally publishedYes

Fingerprint

Noise abatement
Signal to noise ratio
Optical transfer function
Acoustic noise
Pixels
Derivatives
Degradation

Keywords

  • Directional filter
  • Gaussian noise
  • Structure preservation
  • Wiener filter

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Media Technology

Cite this

Structure-oriented multidirectional wiener filter for denoising of image and video signals. / Ghazal, Mohammed; Amer, Aishy; Ghrayeb, Ali.

In: IEEE Transactions on Circuits and Systems for Video Technology, Vol. 18, No. 12, 4625975, 12.2008, p. 1797-1802.

Research output: Contribution to journalArticle

@article{94e54305117143879180e4aad1b54132,
title = "Structure-oriented multidirectional wiener filter for denoising of image and video signals",
abstract = "In this letter, we propose a structure-oriented multi-directional Wiener filter to reduce additive white Gaussian noise in image and video signals. A local activity profile based on second derivatives is used to restrict filtering to homogeneous directions to combat blurring. The proposed filter improves the Wiener estimate of denoised pixels to reduce the residual blurring of the conventional Wiener filter while achieving higher noise-reduction gains of up to 5.6 dB peak signal-to-noise-ratio (PSNR). The parameters of the proposed filter (block size, shape and coefficients) are adapted to image structure and noise level for optimization with respect to noise-reduction gain and structure preservation. The effectiveness of the proposed method is shown using both the PSNR and the modulation transfer function calculated for a range of spatial frequencies to measure the degradation in contrast due to blurring. Our results show that the proposed method achieves a higher contrast transfer ratio than the conventional Wiener filter indicating improved preservation of high frequency content. We also show the performance of the proposed filter relative to reference anisotropic diffusion and wavelet methods.",
keywords = "Directional filter, Gaussian noise, Structure preservation, Wiener filter",
author = "Mohammed Ghazal and Aishy Amer and Ali Ghrayeb",
year = "2008",
month = "12",
doi = "10.1109/TCSVT.2008.2004925",
language = "English",
volume = "18",
pages = "1797--1802",
journal = "IEEE Transactions on Circuits and Systems for Video Technology",
issn = "1051-8215",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",

}

TY - JOUR

T1 - Structure-oriented multidirectional wiener filter for denoising of image and video signals

AU - Ghazal, Mohammed

AU - Amer, Aishy

AU - Ghrayeb, Ali

PY - 2008/12

Y1 - 2008/12

N2 - In this letter, we propose a structure-oriented multi-directional Wiener filter to reduce additive white Gaussian noise in image and video signals. A local activity profile based on second derivatives is used to restrict filtering to homogeneous directions to combat blurring. The proposed filter improves the Wiener estimate of denoised pixels to reduce the residual blurring of the conventional Wiener filter while achieving higher noise-reduction gains of up to 5.6 dB peak signal-to-noise-ratio (PSNR). The parameters of the proposed filter (block size, shape and coefficients) are adapted to image structure and noise level for optimization with respect to noise-reduction gain and structure preservation. The effectiveness of the proposed method is shown using both the PSNR and the modulation transfer function calculated for a range of spatial frequencies to measure the degradation in contrast due to blurring. Our results show that the proposed method achieves a higher contrast transfer ratio than the conventional Wiener filter indicating improved preservation of high frequency content. We also show the performance of the proposed filter relative to reference anisotropic diffusion and wavelet methods.

AB - In this letter, we propose a structure-oriented multi-directional Wiener filter to reduce additive white Gaussian noise in image and video signals. A local activity profile based on second derivatives is used to restrict filtering to homogeneous directions to combat blurring. The proposed filter improves the Wiener estimate of denoised pixels to reduce the residual blurring of the conventional Wiener filter while achieving higher noise-reduction gains of up to 5.6 dB peak signal-to-noise-ratio (PSNR). The parameters of the proposed filter (block size, shape and coefficients) are adapted to image structure and noise level for optimization with respect to noise-reduction gain and structure preservation. The effectiveness of the proposed method is shown using both the PSNR and the modulation transfer function calculated for a range of spatial frequencies to measure the degradation in contrast due to blurring. Our results show that the proposed method achieves a higher contrast transfer ratio than the conventional Wiener filter indicating improved preservation of high frequency content. We also show the performance of the proposed filter relative to reference anisotropic diffusion and wavelet methods.

KW - Directional filter

KW - Gaussian noise

KW - Structure preservation

KW - Wiener filter

UR - http://www.scopus.com/inward/record.url?scp=56849132299&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=56849132299&partnerID=8YFLogxK

U2 - 10.1109/TCSVT.2008.2004925

DO - 10.1109/TCSVT.2008.2004925

M3 - Article

VL - 18

SP - 1797

EP - 1802

JO - IEEE Transactions on Circuits and Systems for Video Technology

JF - IEEE Transactions on Circuits and Systems for Video Technology

SN - 1051-8215

IS - 12

M1 - 4625975

ER -