Random-Valued Impulse Noise Removal Using Non-Local Search for Similar Structures and Sparse Representation

Kengo TSUDA; Takanori FUJISAWA; Masaaki IKEHARA

doi:10.1587/transfun.E100.A.2146

Random-Valued Impulse Noise Removal Using Non-Local Search for Similar Structures and Sparse Representation

Kengo TSUDA, Takanori FUJISAWA, Masaaki IKEHARA

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In this paper, we introduce a new method to remove random-valued impulse noise in an image. Random-valued impulse noise replaces the pixel value at a random position by a random value. Due to the randomness of the noisy pixel values, it is difficult to detect them by comparison with neighboring pixels, which is used in many conventional methods. Then we improve the recent noise detector which uses a non-local search of similar structure. Next we propose a new noise removal algorithm by sparse representation using DCT basis. Furthermore, the sparse representation can remove impulse noise by using the neighboring similar image patch. This method has much more superior noise removal performance than conventional methods at images. We confirm the effectiveness of the proposed method quantitatively and qualitatively.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.10 pp.2146-2153

Publication Date: 2017/10/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.2146

Type of Manuscript: PAPER

Category: Image

Authors

Kengo TSUDA
  Keio University
Takanori FUJISAWA
  Keio University
Masaaki IKEHARA
  Keio University

Keyword

image denoising, random-valued impulse noise, sparse representation, DCT basis

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Kengo TSUDA, Takanori FUJISAWA, Masaaki IKEHARA, "Random-Valued Impulse Noise Removal Using Non-Local Search for Similar Structures and Sparse Representation" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 10, pp. 2146-2153, October 2017, doi: 10.1587/transfun.E100.A.2146.
Abstract: In this paper, we introduce a new method to remove random-valued impulse noise in an image. Random-valued impulse noise replaces the pixel value at a random position by a random value. Due to the randomness of the noisy pixel values, it is difficult to detect them by comparison with neighboring pixels, which is used in many conventional methods. Then we improve the recent noise detector which uses a non-local search of similar structure. Next we propose a new noise removal algorithm by sparse representation using DCT basis. Furthermore, the sparse representation can remove impulse noise by using the neighboring similar image patch. This method has much more superior noise removal performance than conventional methods at images. We confirm the effectiveness of the proposed method quantitatively and qualitatively.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2146/_p

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@ARTICLE{e100-a_10_2146,
author={Kengo TSUDA, Takanori FUJISAWA, Masaaki IKEHARA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Random-Valued Impulse Noise Removal Using Non-Local Search for Similar Structures and Sparse Representation},
year={2017},
volume={E100-A},
number={10},
pages={2146-2153},
abstract={In this paper, we introduce a new method to remove random-valued impulse noise in an image. Random-valued impulse noise replaces the pixel value at a random position by a random value. Due to the randomness of the noisy pixel values, it is difficult to detect them by comparison with neighboring pixels, which is used in many conventional methods. Then we improve the recent noise detector which uses a non-local search of similar structure. Next we propose a new noise removal algorithm by sparse representation using DCT basis. Furthermore, the sparse representation can remove impulse noise by using the neighboring similar image patch. This method has much more superior noise removal performance than conventional methods at images. We confirm the effectiveness of the proposed method quantitatively and qualitatively.},
keywords={},
doi={10.1587/transfun.E100.A.2146},
ISSN={1745-1337},
month={October},}

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TY - JOUR
TI - Random-Valued Impulse Noise Removal Using Non-Local Search for Similar Structures and Sparse Representation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2146
EP - 2153
AU - Kengo TSUDA
AU - Takanori FUJISAWA
AU - Masaaki IKEHARA
PY - 2017
DO - 10.1587/transfun.E100.A.2146
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2017
AB - In this paper, we introduce a new method to remove random-valued impulse noise in an image. Random-valued impulse noise replaces the pixel value at a random position by a random value. Due to the randomness of the noisy pixel values, it is difficult to detect them by comparison with neighboring pixels, which is used in many conventional methods. Then we improve the recent noise detector which uses a non-local search of similar structure. Next we propose a new noise removal algorithm by sparse representation using DCT basis. Furthermore, the sparse representation can remove impulse noise by using the neighboring similar image patch. This method has much more superior noise removal performance than conventional methods at images. We confirm the effectiveness of the proposed method quantitatively and qualitatively.
ER -