IEICE TRANSACTIONS on Fundamentals
Properties and Effective Extensions of Local Similarity-Based Pixel Value Restoration for Impulse Noise Removal
Summary :
In this paper, impulse noise removal for digital images is handled. It is well-known that switching-type processing is effective for the impulse noise removal. In the process, noise-corrupted pixels are first detected, and then, filtering is applied to the detected pixels. This switching process prevents distorting original signals. A noise detector is of course important in the process, a filter for pixel value restoration is also important to obtain excellent results. The authors have proposed a local similarity-based filter (LSF). It utilizes local similarity in a digital image and its capability against restoration of orderly regions has shown in the previous paper. In this paper, first, further experiments are carried out and properties of the LSF are revealed. Although LSF is inferior to an existing filter when disorderly regions are processed and evaluated by the peak signal-to-noise ratio, its outputs are subjectively adequate even in the case. If noise positions are correctly detected, capability of the LSF is guaranteed. On the other hand, some errors may occur in actual noise detection. In that case, LSF sometimes fails to restoration. After properties are examined, we propose two effective extensions to the LSF. First one is for computational cost reduction and another is for color image processing. The original LSF is very time consuming, and in this paper, computational cost reduction is realized introducing a search area. Second proposal is the vector LSF (VLSF) for color images. Although color images can be processed using a filter, which is for monochrome images, to each color component, it sometimes causes color drift. Hence vector processing has been investigated so far. However, existing vector filters do not excel in preservation of orderly pattern although color drift is suppressed. Our proposed VLSF is superior both in orderly pattern preservation and color drift suppression. Effectiveness of the proposed extensions to LSF is verified through experiments.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E95-A No.11 pp.2023-2031
- Publication Date
- 2012/11/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E95.A.2023
- Type of Manuscript
- Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)
- Category
- Image Processing
Authors
Keyword
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Go TANAKA, Noriaki SUETAKE, Eiji UCHINO, "Properties and Effective Extensions of Local Similarity-Based Pixel Value Restoration for Impulse Noise Removal" in IEICE TRANSACTIONS on Fundamentals,
vol. E95-A, no. 11, pp. 2023-2031, November 2012, doi: 10.1587/transfun.E95.A.2023.
Abstract: In this paper, impulse noise removal for digital images is handled. It is well-known that switching-type processing is effective for the impulse noise removal. In the process, noise-corrupted pixels are first detected, and then, filtering is applied to the detected pixels. This switching process prevents distorting original signals. A noise detector is of course important in the process, a filter for pixel value restoration is also important to obtain excellent results. The authors have proposed a local similarity-based filter (LSF). It utilizes local similarity in a digital image and its capability against restoration of orderly regions has shown in the previous paper. In this paper, first, further experiments are carried out and properties of the LSF are revealed. Although LSF is inferior to an existing filter when disorderly regions are processed and evaluated by the peak signal-to-noise ratio, its outputs are subjectively adequate even in the case. If noise positions are correctly detected, capability of the LSF is guaranteed. On the other hand, some errors may occur in actual noise detection. In that case, LSF sometimes fails to restoration. After properties are examined, we propose two effective extensions to the LSF. First one is for computational cost reduction and another is for color image processing. The original LSF is very time consuming, and in this paper, computational cost reduction is realized introducing a search area. Second proposal is the vector LSF (VLSF) for color images. Although color images can be processed using a filter, which is for monochrome images, to each color component, it sometimes causes color drift. Hence vector processing has been investigated so far. However, existing vector filters do not excel in preservation of orderly pattern although color drift is suppressed. Our proposed VLSF is superior both in orderly pattern preservation and color drift suppression. Effectiveness of the proposed extensions to LSF is verified through experiments.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E95.A.2023/_p
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@ARTICLE{e95-a_11_2023,
author={Go TANAKA, Noriaki SUETAKE, Eiji UCHINO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Properties and Effective Extensions of Local Similarity-Based Pixel Value Restoration for Impulse Noise Removal},
year={2012},
volume={E95-A},
number={11},
pages={2023-2031},
abstract={In this paper, impulse noise removal for digital images is handled. It is well-known that switching-type processing is effective for the impulse noise removal. In the process, noise-corrupted pixels are first detected, and then, filtering is applied to the detected pixels. This switching process prevents distorting original signals. A noise detector is of course important in the process, a filter for pixel value restoration is also important to obtain excellent results. The authors have proposed a local similarity-based filter (LSF). It utilizes local similarity in a digital image and its capability against restoration of orderly regions has shown in the previous paper. In this paper, first, further experiments are carried out and properties of the LSF are revealed. Although LSF is inferior to an existing filter when disorderly regions are processed and evaluated by the peak signal-to-noise ratio, its outputs are subjectively adequate even in the case. If noise positions are correctly detected, capability of the LSF is guaranteed. On the other hand, some errors may occur in actual noise detection. In that case, LSF sometimes fails to restoration. After properties are examined, we propose two effective extensions to the LSF. First one is for computational cost reduction and another is for color image processing. The original LSF is very time consuming, and in this paper, computational cost reduction is realized introducing a search area. Second proposal is the vector LSF (VLSF) for color images. Although color images can be processed using a filter, which is for monochrome images, to each color component, it sometimes causes color drift. Hence vector processing has been investigated so far. However, existing vector filters do not excel in preservation of orderly pattern although color drift is suppressed. Our proposed VLSF is superior both in orderly pattern preservation and color drift suppression. Effectiveness of the proposed extensions to LSF is verified through experiments.},
keywords={},
doi={10.1587/transfun.E95.A.2023},
ISSN={1745-1337},
month={November},}
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TY - JOUR
TI - Properties and Effective Extensions of Local Similarity-Based Pixel Value Restoration for Impulse Noise Removal
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2023
EP - 2031
AU - Go TANAKA
AU - Noriaki SUETAKE
AU - Eiji UCHINO
PY - 2012
DO - 10.1587/transfun.E95.A.2023
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E95-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2012
AB - In this paper, impulse noise removal for digital images is handled. It is well-known that switching-type processing is effective for the impulse noise removal. In the process, noise-corrupted pixels are first detected, and then, filtering is applied to the detected pixels. This switching process prevents distorting original signals. A noise detector is of course important in the process, a filter for pixel value restoration is also important to obtain excellent results. The authors have proposed a local similarity-based filter (LSF). It utilizes local similarity in a digital image and its capability against restoration of orderly regions has shown in the previous paper. In this paper, first, further experiments are carried out and properties of the LSF are revealed. Although LSF is inferior to an existing filter when disorderly regions are processed and evaluated by the peak signal-to-noise ratio, its outputs are subjectively adequate even in the case. If noise positions are correctly detected, capability of the LSF is guaranteed. On the other hand, some errors may occur in actual noise detection. In that case, LSF sometimes fails to restoration. After properties are examined, we propose two effective extensions to the LSF. First one is for computational cost reduction and another is for color image processing. The original LSF is very time consuming, and in this paper, computational cost reduction is realized introducing a search area. Second proposal is the vector LSF (VLSF) for color images. Although color images can be processed using a filter, which is for monochrome images, to each color component, it sometimes causes color drift. Hence vector processing has been investigated so far. However, existing vector filters do not excel in preservation of orderly pattern although color drift is suppressed. Our proposed VLSF is superior both in orderly pattern preservation and color drift suppression. Effectiveness of the proposed extensions to LSF is verified through experiments.
ER -
English
