Detail Preserving Mixed Noise Removal by DWM Filter and BM3D

Takuro YAMAGUCHI; Aiko SUZUKI; Masaaki IKEHARA

doi:10.1587/transfun.E100.A.2451

Detail Preserving Mixed Noise Removal by DWM Filter and BM3D

Takuro YAMAGUCHI, Aiko SUZUKI, Masaaki IKEHARA

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Mixed noise removal is a major problem in image processing. Different noises have different properties and it is required to use an appropriate removal method for each noise. Therefore, removal of mixed noise needs the combination of removal algorithms for each contained noise. We aim at the removal of the mixed noise composed of Additive White Gaussian Noise (AWGN) and Random-Valued Impulse Noise (RVIN). Many conventional methods cannot remove the mixed noise effectively and may lose image details. In this paper, we propose a new mixed noise removal method utilizing Direction Weighted Median filter (DWM filter) and Block Matching and 3D filtering method (BM3D). Although the combination of the DWM filter for RVIN and BM3D for AWGN removes almost all the mixed noise, it still loses some image details. We find the cause in the miss-detection of the image details as RVIN and solve the problem by re-detection with the difference of an input noisy image and the output by the combination. The re-detection process removes only salient noise which BM3D cannot remove and therefore preserves image details. These processes lead to the high performance removal of the mixed noise while preserving image details. Experimental results show our method obtains denoised images with clearer edges and textures than conventional methods.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.11 pp.2451-2457

Publication Date: 2017/11/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.2451

Type of Manuscript: PAPER

Category: Image

Authors

Takuro YAMAGUCHI
  Keio University
Aiko SUZUKI
  Keio University
Masaaki IKEHARA
  Keio University

Keyword

image denoising, mixed noise, DWM filter, BM3D

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Takuro YAMAGUCHI, Aiko SUZUKI, Masaaki IKEHARA, "Detail Preserving Mixed Noise Removal by DWM Filter and BM3D" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 11, pp. 2451-2457, November 2017, doi: 10.1587/transfun.E100.A.2451.
Abstract: Mixed noise removal is a major problem in image processing. Different noises have different properties and it is required to use an appropriate removal method for each noise. Therefore, removal of mixed noise needs the combination of removal algorithms for each contained noise. We aim at the removal of the mixed noise composed of Additive White Gaussian Noise (AWGN) and Random-Valued Impulse Noise (RVIN). Many conventional methods cannot remove the mixed noise effectively and may lose image details. In this paper, we propose a new mixed noise removal method utilizing Direction Weighted Median filter (DWM filter) and Block Matching and 3D filtering method (BM3D). Although the combination of the DWM filter for RVIN and BM3D for AWGN removes almost all the mixed noise, it still loses some image details. We find the cause in the miss-detection of the image details as RVIN and solve the problem by re-detection with the difference of an input noisy image and the output by the combination. The re-detection process removes only salient noise which BM3D cannot remove and therefore preserves image details. These processes lead to the high performance removal of the mixed noise while preserving image details. Experimental results show our method obtains denoised images with clearer edges and textures than conventional methods.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2451/_p

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@ARTICLE{e100-a_11_2451,
author={Takuro YAMAGUCHI, Aiko SUZUKI, Masaaki IKEHARA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Detail Preserving Mixed Noise Removal by DWM Filter and BM3D},
year={2017},
volume={E100-A},
number={11},
pages={2451-2457},
abstract={Mixed noise removal is a major problem in image processing. Different noises have different properties and it is required to use an appropriate removal method for each noise. Therefore, removal of mixed noise needs the combination of removal algorithms for each contained noise. We aim at the removal of the mixed noise composed of Additive White Gaussian Noise (AWGN) and Random-Valued Impulse Noise (RVIN). Many conventional methods cannot remove the mixed noise effectively and may lose image details. In this paper, we propose a new mixed noise removal method utilizing Direction Weighted Median filter (DWM filter) and Block Matching and 3D filtering method (BM3D). Although the combination of the DWM filter for RVIN and BM3D for AWGN removes almost all the mixed noise, it still loses some image details. We find the cause in the miss-detection of the image details as RVIN and solve the problem by re-detection with the difference of an input noisy image and the output by the combination. The re-detection process removes only salient noise which BM3D cannot remove and therefore preserves image details. These processes lead to the high performance removal of the mixed noise while preserving image details. Experimental results show our method obtains denoised images with clearer edges and textures than conventional methods.},
keywords={},
doi={10.1587/transfun.E100.A.2451},
ISSN={1745-1337},
month={November},}

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TY - JOUR
TI - Detail Preserving Mixed Noise Removal by DWM Filter and BM3D
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2451
EP - 2457
AU - Takuro YAMAGUCHI
AU - Aiko SUZUKI
AU - Masaaki IKEHARA
PY - 2017
DO - 10.1587/transfun.E100.A.2451
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2017
AB - Mixed noise removal is a major problem in image processing. Different noises have different properties and it is required to use an appropriate removal method for each noise. Therefore, removal of mixed noise needs the combination of removal algorithms for each contained noise. We aim at the removal of the mixed noise composed of Additive White Gaussian Noise (AWGN) and Random-Valued Impulse Noise (RVIN). Many conventional methods cannot remove the mixed noise effectively and may lose image details. In this paper, we propose a new mixed noise removal method utilizing Direction Weighted Median filter (DWM filter) and Block Matching and 3D filtering method (BM3D). Although the combination of the DWM filter for RVIN and BM3D for AWGN removes almost all the mixed noise, it still loses some image details. We find the cause in the miss-detection of the image details as RVIN and solve the problem by re-detection with the difference of an input noisy image and the output by the combination. The re-detection process removes only salient noise which BM3D cannot remove and therefore preserves image details. These processes lead to the high performance removal of the mixed noise while preserving image details. Experimental results show our method obtains denoised images with clearer edges and textures than conventional methods.
ER -