Translation invariant combined denoising algorithm

Birgir Bjorn Saevarsson; Johannes R. Sveinsson; Jon Atli Benediktsson

doi:10.1109/ISCAS.2005.1465567

Translation invariant combined denoising algorithm

Birgir Bjorn Saevarsson, Johannes R. Sveinsson, Jon Atli Benediktsson

Research output: Contribution to journal › Conference article › peer-review

5 Citations (Scopus)

Abstract

The purpose of this paper is to develop a method for denoising images corrupted with additive white Gaussian noise (AWGN). The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. The discrete curvelet transform is a new image representation approach that codes image edges more efficiently than the wavelet transform. On the other hand the wavelet transform codes homogeneous areas better than the curvelet transform. In this paper the translation invariant combined denoising algorithm (TICDA) is proposed. The algorithm is implemented by combining the undecimated discrete wavelet transform (UDWT) and the translation invariant discrete curvelet transform (TIDCT). The AWGN image is then denoised by letting the TICDA solve an l1 optimization problem.

Original language	English
Article number	1465567
Pages (from-to)	4241-4244
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
DOIs	https://doi.org/10.1109/ISCAS.2005.1465567
Publication status	Published - 2005
Event	IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan Duration: 23 May 2005 → 26 May 2005

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title = "Translation invariant combined denoising algorithm",

abstract = "The purpose of this paper is to develop a method for denoising images corrupted with additive white Gaussian noise (AWGN). The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. The discrete curvelet transform is a new image representation approach that codes image edges more efficiently than the wavelet transform. On the other hand the wavelet transform codes homogeneous areas better than the curvelet transform. In this paper the translation invariant combined denoising algorithm (TICDA) is proposed. The algorithm is implemented by combining the undecimated discrete wavelet transform (UDWT) and the translation invariant discrete curvelet transform (TIDCT). The AWGN image is then denoised by letting the TICDA solve an l1 optimization problem.",

author = "Saevarsson, {Birgir Bjorn} and Sveinsson, {Johannes R.} and Benediktsson, {Jon Atli}",

year = "2005",

doi = "10.1109/ISCAS.2005.1465567",

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pages = "4241--4244",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 ; Conference date: 23-05-2005 Through 26-05-2005",

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T1 - Translation invariant combined denoising algorithm

AU - Saevarsson, Birgir Bjorn

AU - Sveinsson, Johannes R.

AU - Benediktsson, Jon Atli

PY - 2005

Y1 - 2005

N2 - The purpose of this paper is to develop a method for denoising images corrupted with additive white Gaussian noise (AWGN). The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. The discrete curvelet transform is a new image representation approach that codes image edges more efficiently than the wavelet transform. On the other hand the wavelet transform codes homogeneous areas better than the curvelet transform. In this paper the translation invariant combined denoising algorithm (TICDA) is proposed. The algorithm is implemented by combining the undecimated discrete wavelet transform (UDWT) and the translation invariant discrete curvelet transform (TIDCT). The AWGN image is then denoised by letting the TICDA solve an l1 optimization problem.

AB - The purpose of this paper is to develop a method for denoising images corrupted with additive white Gaussian noise (AWGN). The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. The discrete curvelet transform is a new image representation approach that codes image edges more efficiently than the wavelet transform. On the other hand the wavelet transform codes homogeneous areas better than the curvelet transform. In this paper the translation invariant combined denoising algorithm (TICDA) is proposed. The algorithm is implemented by combining the undecimated discrete wavelet transform (UDWT) and the translation invariant discrete curvelet transform (TIDCT). The AWGN image is then denoised by letting the TICDA solve an l1 optimization problem.

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DO - 10.1109/ISCAS.2005.1465567

M3 - Conference article

AN - SCOPUS:50649102405

SN - 0271-4310

SP - 4241

EP - 4244

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

M1 - 1465567

T2 - IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005

Y2 - 23 May 2005 through 26 May 2005

ER -

Translation invariant combined denoising algorithm

Abstract

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