Estimation and optimization based ill-posed inverse restoration using fuzzy logic
Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise con...
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| Veröffentlicht in: | Multimedia tools and applications Jg. 69; H. 3; S. 1067 - 1087 |
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| Abstract | Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods. |
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| AbstractList | Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods. Intelligent systems ranging from neural network, evolutionary computations and swarm intelligence to fuzzy systems are extensively exploited by researchers to solve variety of problems. In this paper focus is on deblurring that is considered as an inverse problem. It becomes ill-posed when noise contaminates the blurry image. Hence the problem is very sensitive to small perturbation in data. Conventionally, smoothness constraints are considered as a remedy to cater the sensitivity of the problem. In this paper, fuzzy rule based regularization parameter estimation is proposed with quadratic functional smoothness constraint. For deblurring image in the presence of noise, a constrained least square error function is minimized by the steepest descent algorithm. Visual results and quantitative measurements show the efficiency and robustness of the proposed technique compared to the state of the art and recently proposed methods.[PUBLICATION ABSTRACT] |
| Author | Hussain, Ayyaz Choi, Tae-Sun Mirza, Anwar M. Jaffar, Muhammad Arfan Bilal, Mohsin |
| Author_xml | – sequence: 1 givenname: Mohsin surname: Bilal fullname: Bilal, Mohsin organization: National University of Computer and Emerging Sciences – sequence: 2 givenname: Ayyaz surname: Hussain fullname: Hussain, Ayyaz organization: International Islamic University – sequence: 3 givenname: Muhammad Arfan surname: Jaffar fullname: Jaffar, Muhammad Arfan email: arfanjaffar@gist.ac.kr organization: National University of Computer and Emerging Sciences – sequence: 4 givenname: Tae-Sun surname: Choi fullname: Choi, Tae-Sun organization: Gwangju Institute of Science and Technology – sequence: 5 givenname: Anwar M. surname: Mirza fullname: Mirza, Anwar M. organization: King Saud University |
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| CitedBy_id | crossref_primary_10_1007_s11760_019_01559_5 crossref_primary_10_1007_s11760_017_1106_7 crossref_primary_10_1007_s11042_015_2587_4 crossref_primary_10_1007_s12209_015_2667_6 crossref_primary_10_1007_s12559_015_9339_7 crossref_primary_10_1007_s00158_017_1821_2 crossref_primary_10_1007_s11042_017_4757_z |
| Cites_doi | 10.1109/TIP.2006.873446 10.1016/j.cam.2008.08.013 10.1016/0167-2789(92)90242-F 10.1137/1.9780898718874 10.1002/0471725218 10.1109/29.1641 10.1016/j.ins.2010.02.025 10.1109/83.128030 10.1007/s00500-008-0326-8 |
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| DOI | 10.1007/s11042-012-1172-3 |
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| Keywords | Deblurring Constrained least square error Steepest descent Quadratic functional regularization Blur and noise Fuzzy regularization parameter Parameter estimation Image processing Noise reduction Evolutionary algorithm Steepest descent method Expert system Modeling Optimization Restoration Efficiency Least squares method Swarm intelligence Ill posed problem Robustness System identification Intelligent system Error function Neural network Blurred image Inverse problem Fuzzy logic Artificial intelligence Quadratic functional Signal to noise ratio |
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| PublicationTitle | Multimedia tools and applications |
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| References | AnnaduraiSShanmugalakshmiRFundamental of digital image processing2007IndiaPearson Education Chang FC, Huang HC (2010) A refactoring method for cache-efficient swarm intelligence algorithms. Inf Sci. doi:10.1016/j.ins.2010.02.025 HuangHCChenYHGenetic fingerprinting for copyright protection of multicast mediaSoft Comput200913438339110.1007/s00500-008-0326-8 WuYDSunYZhangHYSunSXTwo image restoration algorithms using variational pde based neural networkIntl Conf Wireless Comm Mob Comp200707683688 CastlemanKRDigital image processing1996New JerseyPrentice Hall MignotteMA segmentation-based regularization term for image deconvolutionIEEE Trans Image Process20061571973198410.1109/TIP.2006.873446 HansenPCNagyJGO’LearyDPDeblurring images: matrices, spectra and filtering2006PhiladelphiaSociety of Industria and Applied Mathematics10.1137/1.9780898718874 GutierrezJGuerreroLGSpatially adaptive regularization image restoration using a modified hopfield networkIEEE Cong Elec Robo Auto Mechanics20074229234 LimJSTwo-dimensional signal and image processing1990New JerseyPrentice Hall RipleyBDSpatial statistics1981New YorkWiley10.1002/04717252180583.62087 GonzalezRCWoodsREDigital image processing2002New JerseyAddison-Wesley TokhonovANArseninVYSolution of ill-posed problems1977New YorkWiley PuranikPBajajPAbrahamAPalsodkarPDeshmukhAHuman perception-based color image segmentation using comprehensive learning particle swarm optimizationJ Info Hiding Mult Sig Process201123227235 SinghKMFuzzy rule based median filter for gray-scale imagesJ Info Hiding Mult Sig Process201122108122 ZhuYTChellappaRVaidAJenkinsBKImage restoration using a neural networkIEEE Trans Acoust Speech Signal Process19883671141115110.1109/29.1641 de CastroAPADrummondINda SilvaJDSA multiscale neural network method for image restorationTEMA Tend Mat Apl Comput2008914150 Jensen TK (2006) Stabilization algorithms for large-scale problems. Dissertation, Technical University of Denmark BilalMSharifMJaffarMAHussainAMirzaAMImage restoration using modified hopfield fuzzy regularization methodIEEE Int Conf Future Info Tech2010515 PerrySWAdaptive image restoration: perception based neural network model and algorithm2006University of SydneyDissertation RudinLIOsherSFatemiENonlinear total variation based noise removal algorithmsPhysica D19926025926810.1016/0167-2789(92)90242-F0780.49028 LeeCSGuoSMHsuCYA novel fuzzy filter for impulse noise removalAdv Neur Networks—LNCS20043174375380 PaikJKKatsaggelosAKImage restoration using a modified hopfield networkIEEE Trans Image Process199211496310.1109/83.128030 Sun W, xiang Yuan Y (2006) Optimization theory and methods: nonlinear programming. Springer GuXGoaLA new method for parameter estimation of edge-preserving regularization in image restorationJ Comput Appl Math200922547848610.1016/j.cam.2008.08.0131156.940062494718 PerrySWGuanLWeight assignment for adaptive image restoration by neural networksIEEE Trans Image Process2000111156170 KaganamiHGAliSKZouBOptimal approach for texture analysis and classification based on wavelet transform and neural networkJ Info Hiding Mult Sig Process2011213340 HG Kaganami (1172_CR12) 2011; 2 1172_CR11 SW Perry (1172_CR17) 2006 JK Paik (1172_CR16) 1992; 1 SW Perry (1172_CR18) 2000; 11 KR Castleman (1172_CR3) 1996 LI Rudin (1172_CR21) 1992; 60 M Mignotte (1172_CR15) 2006; 15 1172_CR5 APA Castro de (1172_CR4) 2008; 9 CS Lee (1172_CR13) 2004; 3174 KM Singh (1172_CR22) 2011; 2 1172_CR23 P Puranik (1172_CR19) 2011; 2 X Gu (1172_CR7) 2009; 225 YT Zhu (1172_CR26) 1988; 36 S Annadurai (1172_CR1) 2007 BD Ripley (1172_CR20) 1981 J Gutierrez (1172_CR8) 2007; 4 HC Huang (1172_CR10) 2009; 13 RC Gonzalez (1172_CR6) 2002 JS Lim (1172_CR14) 1990 PC Hansen (1172_CR9) 2006 YD Wu (1172_CR25) 2007; 07 M Bilal (1172_CR2) 2010; 5 AN Tokhonov (1172_CR24) 1977 |
| References_xml | – reference: BilalMSharifMJaffarMAHussainAMirzaAMImage restoration using modified hopfield fuzzy regularization methodIEEE Int Conf Future Info Tech2010515 – reference: RudinLIOsherSFatemiENonlinear total variation based noise removal algorithmsPhysica D19926025926810.1016/0167-2789(92)90242-F0780.49028 – reference: Jensen TK (2006) Stabilization algorithms for large-scale problems. Dissertation, Technical University of Denmark – reference: CastlemanKRDigital image processing1996New JerseyPrentice Hall – reference: LimJSTwo-dimensional signal and image processing1990New JerseyPrentice Hall – reference: AnnaduraiSShanmugalakshmiRFundamental of digital image processing2007IndiaPearson Education – reference: GuXGoaLA new method for parameter estimation of edge-preserving regularization in image restorationJ Comput Appl Math200922547848610.1016/j.cam.2008.08.0131156.940062494718 – reference: TokhonovANArseninVYSolution of ill-posed problems1977New YorkWiley – reference: PerrySWAdaptive image restoration: perception based neural network model and algorithm2006University of SydneyDissertation – reference: WuYDSunYZhangHYSunSXTwo image restoration algorithms using variational pde based neural networkIntl Conf Wireless Comm Mob Comp200707683688 – reference: GutierrezJGuerreroLGSpatially adaptive regularization image restoration using a modified hopfield networkIEEE Cong Elec Robo Auto Mechanics20074229234 – reference: ZhuYTChellappaRVaidAJenkinsBKImage restoration using a neural networkIEEE Trans Acoust Speech Signal Process19883671141115110.1109/29.1641 – reference: HuangHCChenYHGenetic fingerprinting for copyright protection of multicast mediaSoft Comput200913438339110.1007/s00500-008-0326-8 – reference: HansenPCNagyJGO’LearyDPDeblurring images: matrices, spectra and filtering2006PhiladelphiaSociety of Industria and Applied Mathematics10.1137/1.9780898718874 – reference: MignotteMA segmentation-based regularization term for image deconvolutionIEEE Trans Image Process20061571973198410.1109/TIP.2006.873446 – reference: GonzalezRCWoodsREDigital image processing2002New JerseyAddison-Wesley – reference: Sun W, xiang Yuan Y (2006) Optimization theory and methods: nonlinear programming. Springer – reference: Chang FC, Huang HC (2010) A refactoring method for cache-efficient swarm intelligence algorithms. Inf Sci. doi:10.1016/j.ins.2010.02.025 – reference: LeeCSGuoSMHsuCYA novel fuzzy filter for impulse noise removalAdv Neur Networks—LNCS20043174375380 – reference: PerrySWGuanLWeight assignment for adaptive image restoration by neural networksIEEE Trans Image Process2000111156170 – reference: PaikJKKatsaggelosAKImage restoration using a modified hopfield networkIEEE Trans Image Process199211496310.1109/83.128030 – reference: PuranikPBajajPAbrahamAPalsodkarPDeshmukhAHuman perception-based color image segmentation using comprehensive learning particle swarm optimizationJ Info Hiding Mult Sig Process201123227235 – reference: RipleyBDSpatial statistics1981New YorkWiley10.1002/04717252180583.62087 – reference: SinghKMFuzzy rule based median filter for gray-scale imagesJ Info Hiding Mult Sig Process201122108122 – reference: de CastroAPADrummondINda SilvaJDSA multiscale neural network method for image restorationTEMA Tend Mat Apl Comput2008914150 – reference: KaganamiHGAliSKZouBOptimal approach for texture analysis and classification based on wavelet transform and neural networkJ Info Hiding Mult Sig Process2011213340 – volume: 5 start-page: 1 year: 2010 ident: 1172_CR2 publication-title: IEEE Int Conf Future Info Tech – volume: 4 start-page: 229 year: 2007 ident: 1172_CR8 publication-title: IEEE Cong Elec Robo Auto Mechanics – ident: 1172_CR23 – volume: 3174 start-page: 375 year: 2004 ident: 1172_CR13 publication-title: Adv Neur Networks—LNCS – volume: 15 start-page: 1973 issue: 7 year: 2006 ident: 1172_CR15 publication-title: IEEE Trans Image Process doi: 10.1109/TIP.2006.873446 – volume-title: Solution of ill-posed problems year: 1977 ident: 1172_CR24 – volume: 225 start-page: 478 year: 2009 ident: 1172_CR7 publication-title: J Comput Appl Math doi: 10.1016/j.cam.2008.08.013 – volume: 60 start-page: 259 year: 1992 ident: 1172_CR21 publication-title: Physica D doi: 10.1016/0167-2789(92)90242-F – volume: 11 start-page: 156 issue: 1 year: 2000 ident: 1172_CR18 publication-title: IEEE Trans Image Process – volume-title: Deblurring images: matrices, spectra and filtering year: 2006 ident: 1172_CR9 doi: 10.1137/1.9780898718874 – volume-title: Spatial statistics year: 1981 ident: 1172_CR20 doi: 10.1002/0471725218 – volume: 2 start-page: 108 issue: 2 year: 2011 ident: 1172_CR22 publication-title: J Info Hiding Mult Sig Process – volume: 36 start-page: 1141 issue: 7 year: 1988 ident: 1172_CR26 publication-title: IEEE Trans Acoust Speech Signal Process doi: 10.1109/29.1641 – volume-title: Digital image processing year: 1996 ident: 1172_CR3 – volume-title: Two-dimensional signal and image processing year: 1990 ident: 1172_CR14 – ident: 1172_CR5 doi: 10.1016/j.ins.2010.02.025 – volume-title: Fundamental of digital image processing year: 2007 ident: 1172_CR1 – volume: 1 start-page: 49 issue: 1 year: 1992 ident: 1172_CR16 publication-title: IEEE Trans Image Process doi: 10.1109/83.128030 – volume: 2 start-page: 33 issue: 1 year: 2011 ident: 1172_CR12 publication-title: J Info Hiding Mult Sig Process – volume: 9 start-page: 41 issue: 1 year: 2008 ident: 1172_CR4 publication-title: TEMA Tend Mat Apl Comput – volume-title: Digital image processing year: 2002 ident: 1172_CR6 – volume: 2 start-page: 227 issue: 3 year: 2011 ident: 1172_CR19 publication-title: J Info Hiding Mult Sig Process – volume: 07 start-page: 683 year: 2007 ident: 1172_CR25 publication-title: Intl Conf Wireless Comm Mob Comp – volume-title: Adaptive image restoration: perception based neural network model and algorithm year: 2006 ident: 1172_CR17 – ident: 1172_CR11 – volume: 13 start-page: 383 issue: 4 year: 2009 ident: 1172_CR10 publication-title: Soft Comput doi: 10.1007/s00500-008-0326-8 |
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| SubjectTerms | Algebra Algorithms Analysis Applied sciences Artificial intelligence Computer Communication Networks Computer Science Computer science; control theory; systems Connectionism. Neural networks Data Structures and Information Theory Digitization Estimating techniques Exact sciences and technology Fuzzy logic Ill posed problems Inverse problems Methods Multimedia computer applications Multimedia Information Systems Neural networks Noise Optimization Parameter estimation Pattern recognition. Digital image processing. Computational geometry Regularization methods Remedies Smoothness Special Purpose and Application-Based Systems Studies |
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| Title | Estimation and optimization based ill-posed inverse restoration using fuzzy logic |
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