A modified form of different applied median filter for removal of salt & pepper noise
An algorithm is presented for removal of Salt & pepper noise. Proposed algorithm uses two phased approach where noise is first detected and then removed using window sizes extending up to 7 × 7. Window size changes depending upon noise density. In any processing window, we have some pre-processe...
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| Published in | Multimedia tools and applications Vol. 82; no. 5; pp. 7479 - 7490 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.02.2023
Springer Nature B.V |
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| Online Access | Get full text |
| ISSN | 1380-7501 1573-7721 |
| DOI | 10.1007/s11042-022-13289-x |
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| Abstract | An algorithm is presented for removal of Salt & pepper noise. Proposed algorithm uses two phased approach where noise is first detected and then removed using window sizes extending up to 7 × 7. Window size changes depending upon noise density. In any processing window, we have some pre-processed pixels and some unprocessed pixels. If a pixel under consideration is a noise pixel then we consider all processed and unprocessed pixels for noise pixel replacement, if we find one or more noise-free pixels in window then we replace median of these pixels with corrupted pixel. If we do not find any original pixel in window then we increase window size and repeat retrospective process. The proposed algorithm shows improved results as compared to existing methods. Proposed algorithm is tested and compared for Structural Similarity (SSIM) and Peak-Signal-to-Noise Ratio (PSNR) with existing methods. |
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| AbstractList | An algorithm is presented for removal of Salt & pepper noise. Proposed algorithm uses two phased approach where noise is first detected and then removed using window sizes extending up to 7 × 7. Window size changes depending upon noise density. In any processing window, we have some pre-processed pixels and some unprocessed pixels. If a pixel under consideration is a noise pixel then we consider all processed and unprocessed pixels for noise pixel replacement, if we find one or more noise-free pixels in window then we replace median of these pixels with corrupted pixel. If we do not find any original pixel in window then we increase window size and repeat retrospective process. The proposed algorithm shows improved results as compared to existing methods. Proposed algorithm is tested and compared for Structural Similarity (SSIM) and Peak-Signal-to-Noise Ratio (PSNR) with existing methods. |
| Author | Rehman, Zia Ul Mustafa, Ghulam Hanif, Muhammad Aslam, Numan Ehsan, Muhammad Khurram |
| Author_xml | – sequence: 1 givenname: Numan surname: Aslam fullname: Aslam, Numan organization: Department of Computer Science, Bahria University Lahore Campus (BULC) – sequence: 2 givenname: Muhammad Khurram surname: Ehsan fullname: Ehsan, Muhammad Khurram organization: Faculty of Engineering Sciences, Bahria University Lahore Campus (BULC) – sequence: 3 givenname: Zia Ul surname: Rehman fullname: Rehman, Zia Ul organization: Department of Computer Science, Kinnaird College for Women Lahore – sequence: 4 givenname: Muhammad surname: Hanif fullname: Hanif, Muhammad email: muhammad.hanif@riphah.edu.pk organization: Riphah Institute of Informatics, Riphah International University, Malakand Campus – sequence: 5 givenname: Ghulam surname: Mustafa fullname: Mustafa, Ghulam organization: Department of Computer Science, Bahria University Lahore Campus (BULC) |
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| CitedBy_id | crossref_primary_10_1038_s41699_024_00458_9 crossref_primary_10_3390_app13084861 crossref_primary_10_3390_s25010210 crossref_primary_10_1007_s11760_024_03271_5 crossref_primary_10_7717_peerj_cs_1160 crossref_primary_10_1038_s41598_025_92283_3 |
| Cites_doi | 10.1016/j.compeleceng.2018.05.026 10.1109/ICSIPR.2013.6498000 10.1007/978-3-642-38466-0_41 10.1109/LSP.2011.2122333 10.1109/LSP.2020.3016868 10.5566/ias.2418 10.1016/j.engappai.2012.10.012 10.1007/s12652-020-01737-1 10.3390/sym12121990 10.1109/82.749102 10.1109/LSP.2006.884014 10.1109/83.806630 10.1016/j.aeue.2013.03.006 10.1109/ISMS.2012.93 10.29137/umagd.495904 10.1109/83.370679 10.1109/LSP.2006.884018 10.1016/j.patrec.2012.03.025 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Impulse noise Random noise Median filter Salt & pepper noise |
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| References | Erkan U, Gokrem L, Enginoglu S (2019) Adaptive right median filter for salt-and-pepper noise removal. International Journal of Engineering Research and Development, 542–550 HwangHHaddadRAAdaptive median filters: new algorithms and resultsIEEE Trans Image Process1995449950210.1109/83.370679 Turkmen I (2013) A new method to remove random-valued impulse noise in images. International Journal of Electronics and Communications (AEÜ), 771–779 Xu YQ, Dong SF (2007) A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Processing Letters, 31–34 Javier MM, Galván CG, López RL, Debayle J (2021) On the properties of some adaptive morphological filters for salt and pepper noise removal. Image Analysis and Stereology, International Society for Stereology, 29 Umbaugh S (2005) Computer imaging: digital image analysis and processing: Taylor & Fransis Sheebha SP, Adhinarayanan VS (2012) A Modified algorithm for Removal of Salt and Pepper Noise in Color Images, in International Conference on Intelligent Systems Modelling and Simulation, 356–367 SattiPSharmaNGargBMin-max average pooling based filter for impulse noise removalIEEE Signal Processing Letters2020271475147910.1109/LSP.2020.3016868 VeerakumarTSubramanyamANPremChandCHEsakkirajanSRemoval of high density salt and pepper noise through modified decision based Unsymmetric trimmed median filterIEEE Signal Processing Letters20111828729010.1109/LSP.2011.2122333 Imran BM, Benazir TM (2013) Removal of high and low density impulse noise from digital images using non linear filter. International Conference on Signal Processing, Image Processing and Pattern Recognition Cheng FC, Shie MC, Ruan SJ, Hsieh MH (2013) Fast and efficient median filter for removing 1–99% levels of salt-and-pepper, Engineering Applications of Artificial Intelligence, 1333–1338 KarthikBKrishna KumarTVijayaragavanSPSriramMRemoval of high density salt and pepper noise in color image through modified cascaded filterJ Ambient Intell Human Comput2021123901390810.1007/s12652-020-01737-1 ErkanUGokremLEnginogluSDifferent applied median fillter in salt-and-pepper noiseInt J Comput Electr Eng201870110 RevathyKMadhuRTNairSRemoval of Salt-and Pepper Noise in Images: A New Decision-Based AlgorithmProceedings of the International MultiConference of Engineers and Computer Scientists IMECS2008I1921 Wang Z, Wang DZ (2013) A novel decision-based algorithm for removal of highly corrupted images. Chinese Intelligent Automation Conference, Heidelberg, 367–375 Ma T, Chen KK, Chen H (1999) Tri-state median filter for image denoising. IEEE Transactions on Image Processing, 1834–1838 ChouTCLuCTDenoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filterPattern Recogn Lett2012331287129510.1016/j.patrec.2012.03.025 WangZZhangDProgressive switching median filter for the removal of impulse noise from highly corrupted imagesIEEE Transactions on Circuits and Systems—II: Analog and Digital Signal Processing199946788010.1109/82.749102 Chen F, Huang M, Ma Z, Li Y, Huang Q (2020) An iterative weighted-mean filter for removal of high-density salt-and-pepper noise. Symmetry 12(12) EbenezerDSrinivasanKSA new fast and efficient decision-based algorithm for removal of high-density impulse noisesIEEE Signal Processing Letters20071418919210.1109/LSP.2006.884018 Z Wang (13289_CR19) 1999; 46 U Erkan (13289_CR5) 2018; 70 13289_CR18 K Revathy (13289_CR12) 2008; I 13289_CR16 13289_CR15 13289_CR14 B Karthik (13289_CR10) 2021; 12 T Veerakumar (13289_CR17) 2011; 18 TC Chou (13289_CR3) 2012; 33 13289_CR8 13289_CR6 P Satti (13289_CR13) 2020; 27 D Ebenezer (13289_CR4) 2007; 14 H Hwang (13289_CR7) 1995; 4 13289_CR9 13289_CR11 13289_CR20 13289_CR2 13289_CR1 |
| References_xml | – reference: KarthikBKrishna KumarTVijayaragavanSPSriramMRemoval of high density salt and pepper noise in color image through modified cascaded filterJ Ambient Intell Human Comput2021123901390810.1007/s12652-020-01737-1 – reference: Umbaugh S (2005) Computer imaging: digital image analysis and processing: Taylor & Fransis – reference: Imran BM, Benazir TM (2013) Removal of high and low density impulse noise from digital images using non linear filter. International Conference on Signal Processing, Image Processing and Pattern Recognition – reference: Javier MM, Galván CG, López RL, Debayle J (2021) On the properties of some adaptive morphological filters for salt and pepper noise removal. Image Analysis and Stereology, International Society for Stereology, 29 – reference: Chen F, Huang M, Ma Z, Li Y, Huang Q (2020) An iterative weighted-mean filter for removal of high-density salt-and-pepper noise. Symmetry 12(12) – reference: RevathyKMadhuRTNairSRemoval of Salt-and Pepper Noise in Images: A New Decision-Based AlgorithmProceedings of the International MultiConference of Engineers and Computer Scientists IMECS2008I1921 – reference: Sheebha SP, Adhinarayanan VS (2012) A Modified algorithm for Removal of Salt and Pepper Noise in Color Images, in International Conference on Intelligent Systems Modelling and Simulation, 356–367 – reference: HwangHHaddadRAAdaptive median filters: new algorithms and resultsIEEE Trans Image Process1995449950210.1109/83.370679 – reference: EbenezerDSrinivasanKSA new fast and efficient decision-based algorithm for removal of high-density impulse noisesIEEE Signal Processing Letters20071418919210.1109/LSP.2006.884018 – reference: Turkmen I (2013) A new method to remove random-valued impulse noise in images. International Journal of Electronics and Communications (AEÜ), 771–779 – reference: Cheng FC, Shie MC, Ruan SJ, Hsieh MH (2013) Fast and efficient median filter for removing 1–99% levels of salt-and-pepper, Engineering Applications of Artificial Intelligence, 1333–1338 – reference: ChouTCLuCTDenoising of salt-and-pepper noise corrupted image using modified directional-weighted-median filterPattern Recogn Lett2012331287129510.1016/j.patrec.2012.03.025 – reference: Erkan U, Gokrem L, Enginoglu S (2019) Adaptive right median filter for salt-and-pepper noise removal. International Journal of Engineering Research and Development, 542–550 – reference: VeerakumarTSubramanyamANPremChandCHEsakkirajanSRemoval of high density salt and pepper noise through modified decision based Unsymmetric trimmed median filterIEEE Signal Processing Letters20111828729010.1109/LSP.2011.2122333 – reference: Xu YQ, Dong SF (2007) A new directional weighted median filter for removal of random-valued impulse noise. IEEE Signal Processing Letters, 31–34 – reference: Ma T, Chen KK, Chen H (1999) Tri-state median filter for image denoising. IEEE Transactions on Image Processing, 1834–1838 – reference: SattiPSharmaNGargBMin-max average pooling based filter for impulse noise removalIEEE Signal Processing Letters2020271475147910.1109/LSP.2020.3016868 – reference: Wang Z, Wang DZ (2013) A novel decision-based algorithm for removal of highly corrupted images. Chinese Intelligent Automation Conference, Heidelberg, 367–375 – reference: ErkanUGokremLEnginogluSDifferent applied median fillter in salt-and-pepper noiseInt J Comput Electr Eng201870110 – reference: WangZZhangDProgressive switching median filter for the removal of impulse noise from highly corrupted imagesIEEE Transactions on Circuits and Systems—II: Analog and Digital Signal Processing199946788010.1109/82.749102 – volume: 70 start-page: 1 year: 2018 ident: 13289_CR5 publication-title: Int J Comput Electr Eng doi: 10.1016/j.compeleceng.2018.05.026 – ident: 13289_CR8 doi: 10.1109/ICSIPR.2013.6498000 – ident: 13289_CR18 doi: 10.1007/978-3-642-38466-0_41 – volume: 18 start-page: 287 year: 2011 ident: 13289_CR17 publication-title: IEEE Signal Processing Letters doi: 10.1109/LSP.2011.2122333 – volume: 27 start-page: 1475 year: 2020 ident: 13289_CR13 publication-title: IEEE Signal Processing Letters doi: 10.1109/LSP.2020.3016868 – ident: 13289_CR9 doi: 10.5566/ias.2418 – ident: 13289_CR2 doi: 10.1016/j.engappai.2012.10.012 – volume: 12 start-page: 3901 year: 2021 ident: 13289_CR10 publication-title: J Ambient Intell Human Comput doi: 10.1007/s12652-020-01737-1 – ident: 13289_CR1 doi: 10.3390/sym12121990 – volume: 46 start-page: 78 year: 1999 ident: 13289_CR19 publication-title: IEEE Transactions on Circuits and Systems—II: Analog and Digital Signal Processing doi: 10.1109/82.749102 – ident: 13289_CR20 doi: 10.1109/LSP.2006.884014 – ident: 13289_CR11 doi: 10.1109/83.806630 – ident: 13289_CR15 doi: 10.1016/j.aeue.2013.03.006 – ident: 13289_CR14 doi: 10.1109/ISMS.2012.93 – ident: 13289_CR16 – ident: 13289_CR6 doi: 10.29137/umagd.495904 – volume: 4 start-page: 499 year: 1995 ident: 13289_CR7 publication-title: IEEE Trans Image Process doi: 10.1109/83.370679 – volume: I start-page: 19 year: 2008 ident: 13289_CR12 publication-title: Proceedings of the International MultiConference of Engineers and Computer Scientists IMECS – volume: 14 start-page: 189 year: 2007 ident: 13289_CR4 publication-title: IEEE Signal Processing Letters doi: 10.1109/LSP.2006.884018 – volume: 33 start-page: 1287 year: 2012 ident: 13289_CR3 publication-title: Pattern Recogn Lett doi: 10.1016/j.patrec.2012.03.025 |
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| Title | A modified form of different applied median filter for removal of salt & pepper noise |
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