Parameters optimization of the novel probabilistic algorithm for improving spatial resolution of multispectral satellite images
A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel brightness in different channels of an improved multispectral image based on the probabilistic characte...
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| Published in: | Journal of computer & systems sciences international Vol. 56; no. 6; pp. 1008 - 1020 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Moscow
Pleiades Publishing
01.11.2017
Springer Nature B.V |
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| ISSN: | 1064-2307, 1555-6530 |
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| Abstract | A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel brightness in different channels of an improved multispectral image based on the probabilistic characteristics of the pixel neighborhood on the multispectral image and the overall brightness intensity of the panchromatic image at that point. The applicability of different metrics for evaluating the quality of the spatial resolution of satellite images is analyzed. A set of the most adequate quality evaluation metrics is used. An optimization procedure is developed to adjust the parameters of the proposed probabilistic resolution improvement method. The results of testing the method on the multi-spectral images obtained from different satellites in different spatial resolutions are presented. The efficiency of the algorithm is tested at different magnification scales. A comparative analysis of the results of the proposed method with similar approaches is conducted. |
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| AbstractList | A probabilistic method for improving the spatial resolution of multispectral space images using a reference image is proposed. The developed method calculates the mathematical expectation of pixel brightness in different channels of an improved multispectral image based on the probabilistic characteristics of the pixel neighborhood on the multispectral image and the overall brightness intensity of the panchromatic image at that point. The applicability of different metrics for evaluating the quality of the spatial resolution of satellite images is analyzed. A set of the most adequate quality evaluation metrics is used. An optimization procedure is developed to adjust the parameters of the proposed probabilistic resolution improvement method. The results of testing the method on the multi-spectral images obtained from different satellites in different spatial resolutions are presented. The efficiency of the algorithm is tested at different magnification scales. A comparative analysis of the results of the proposed method with similar approaches is conducted. |
| Author | Ignatiev, V. Yu Murynin, A. B. Gorokhovskiy, K. Yu Rakova, K. O. |
| Author_xml | – sequence: 1 givenname: K. Yu surname: Gorokhovskiy fullname: Gorokhovskiy, K. Yu organization: Institute for Scientific Research of Aerospace Monitoring AEROCOSMOS – sequence: 2 givenname: V. Yu surname: Ignatiev fullname: Ignatiev, V. Yu email: vladimir.ignatiev.mipt@gmail.com organization: Institute for Scientific Research of Aerospace Monitoring AEROCOSMOS, Dorodnicyn Computing Centre, FRC CSC RAS – sequence: 3 givenname: A. B. surname: Murynin fullname: Murynin, A. B. organization: Institute for Scientific Research of Aerospace Monitoring AEROCOSMOS, Dorodnicyn Computing Centre, FRC CSC RAS – sequence: 4 givenname: K. O. surname: Rakova fullname: Rakova, K. O. organization: Institute for Scientific Research of Aerospace Monitoring AEROCOSMOS, Moscow Institute of Physics and Technology |
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| Cites_doi | 10.1109/TGRS.2010.2051674 10.1134/S1064230715060027 10.1134/S1064230716020052 10.14358/PERS.72.5.591 10.1134/S1064230709020129 10.1134/S1064230716040122 10.1109/LGRS.2004.834804 10.1016/j.cageo.2006.06.008 10.1134/S0001433816060049 10.1134/S1064230715040085 10.1109/TGRS.2007.901007 10.1109/TGRS.2007.912448 |
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| Copyright | Pleiades Publishing, Ltd. 2017 Journal of Computer and Systems Sciences International is a copyright of Springer, (2017). All Rights Reserved. |
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| References | MuryninA.GorokhovskiyK.BondurV.IgnatievV.Analysis of large long-term remote sensing image sequence for agricultural yield forecastingProceedings of the 4th International Workshop on Image Mining, Theory and Applications IMTA-4 2013, with VISIGRAPP 2013, Barcelona, Spain2013PortugalSCITERGRASS4855 VizilterYu. V.VygolovO. V.ZheltovS. Yu.RubisA. Yu.A way to interconnect the multispectral images for improved vision systems by using the methods of diffusive morphologyJ. Comput. Syst. Sci. Int.20165559810.1134/S10642307160401223643040 Aerospace Monitoring of Objects of Oil and Gas Facilities, Ed. by V. G. Bondur (Nauchnyi Mir, Moscow, 2012) [in Russian]. EvdokimenkovV. N.KimR. V.Krasil’shchikovM. N.SebryakovG. G.The use of the neural network model of pilot control actions for their individually-adapted supportJ. Comput. Syst. Sci. Int.20155460910.1134/S10642307150400851338.932633376961 TuT.-M.HuangP. S.HungC.-L.ChangC.-P.A fast intensity hue saturation fusion technique with spectral adjustment for IKONOS imageryIEEE Geosci. Remote Sens. Lett.2004130931210.1109/LGRS.2004.834804 B. Owen Art, Monte Carlo Theory, Methods and Examples. http://statweb.stanford.edu/~owen/mc/Ch-varis.pdf. IshutinA. A.KikinI. S.SebryakovG. G.SoshnikovV. N.Algorithms for the detection, localization, and recognition of electro-optical images of the group of isolated ground locations for inertial-sighting systems of navigation and guidance of aircraftJ. Comput. Syst. Sci. Int.20165524210.1134/S1064230716020052 AiazziB.AlparoneL.BarontiS.GarzelliA.SelvaM.MTF–tailore multiscale fusion of high-resolution MS and pan imageryPhotogramm. Eng. Remote Sens.20067259159610.14358/PERS.72.5.591 ChoiJ.YuK.KimY.A new adaptive component-substitution based satellite image fusion by using partial replacementIEEE Trans. Geosci. Remote Sens.20114929530910.1109/TGRS.2010.2051674 VizilterYu. V.ZheltovS. Yu.The use of projective morphologies for object detection and identification in imagesJ. Comput. Syst. Sci. Int.20094828210.1134/S10642307090201291176.682292555361 DouW.ChenY.LiX.SuiD.A general framework for component substitution image fusion: an implementation using fast image fusion methodComput. Geosci.20073321922810.1016/j.cageo.2006.06.008 ChavezP. S.SidesJr.,_S. C.AndersonA. J.Comparison of three different methods to merge multiresolution and multispectral data: landsat TM and SPOT panchromaticPhotogramm. Eng. Remote Sens.199157295303 BondurV. G.DulovV. A.MuryninA. B.Ignat’evV. Yu.Retrieving sea-wave spectra using satelliteimagery spectra in a wide range of frequenciesIzv., Atmos. Ocean. Phys.20165263710.1134/S0001433816060049 GurchenkovA. A.BochkarevaV. G.MuryninA. B.TrekinA. N.Image quality improvement by method of spatial spectrum extrapolationVestn. MGTU Baumana, Ser.: Estestv. Nauki201626591102 BondurV. G.MuryninA. B.Ignat’evV. Yu.Parameters optimization in the problem of sea-wave spectra recovery by airspace imagesMashin. Obuchen. Anal. Dannykh20162218230 MilanfarP.Super-Resolution Imaging2011Boca Raton, London, New YorkCRC473 BochkarevaV. G.MatveevI. A.MuryninA. B.TsurkovV. I.Methods for improving image quality using spatial spectral analysisJ. Comput. Syst. Sci. Int.20155489710.1134/S10642307150600273432990 ThomasC.RanchinT.WaldL.ChanussotJ.Synthesis of multispectral images to high spatial resolution: a critical review of fusion methods based on remote sensing physicsIEEE Trans. Geosci. Remote Sens.2008461301131210.1109/TGRS.2007.912448 VivoneG.AlparoneL.ChanussotJ.dalla MuraM.GarzelliA.LicciardiG.RestainoR.WaldL.A critical comparison among pansharpening algorithmsIEEE Trans. Geosci. Remote Sens.2015 AiazziB.BarontiS.SelvaM.Improving component substitution pansharpening through multivariate regression of MS+Pan dataIEEE Trans. Geosci. Remote Sens.2007453230323910.1109/TGRS.2007.901007 V. G. Bondur (6721_CR7) 2016; 2 6721_CR1 V. G. Bondur (6721_CR6) 2016; 52 Yu. V. Vizilter (6721_CR13) 2016; 55 G. Vivone (6721_CR11) 2015 W. Dou (6721_CR17) 2007; 33 T.-M. Tu (6721_CR16) 2004; 1 V. G. Bochkareva (6721_CR9) 2015; 54 A. A. Ishutin (6721_CR5) 2016; 55 C. Thomas (6721_CR12) 2008; 46 A. Murynin (6721_CR2) 2013 P. Milanfar (6721_CR10) 2011 Yu. V. Vizilter (6721_CR4) 2009; 48 V. N. Evdokimenkov (6721_CR3) 2015; 54 P. S. Chavez (6721_CR14) 1991; 57 6721_CR20 A. A. Gurchenkov (6721_CR8) 2016; 2 B. Aiazzi (6721_CR15) 2007; 45 J. Choi (6721_CR18) 2011; 49 B. Aiazzi (6721_CR19) 2006; 72 |
| References_xml | – reference: AiazziB.AlparoneL.BarontiS.GarzelliA.SelvaM.MTF–tailore multiscale fusion of high-resolution MS and pan imageryPhotogramm. Eng. Remote Sens.20067259159610.14358/PERS.72.5.591 – reference: B. Owen Art, Monte Carlo Theory, Methods and Examples. http://statweb.stanford.edu/~owen/mc/Ch-varis.pdf. – reference: BondurV. G.MuryninA. B.Ignat’evV. Yu.Parameters optimization in the problem of sea-wave spectra recovery by airspace imagesMashin. Obuchen. Anal. Dannykh20162218230 – reference: IshutinA. A.KikinI. S.SebryakovG. G.SoshnikovV. N.Algorithms for the detection, localization, and recognition of electro-optical images of the group of isolated ground locations for inertial-sighting systems of navigation and guidance of aircraftJ. Comput. Syst. Sci. Int.20165524210.1134/S1064230716020052 – reference: TuT.-M.HuangP. S.HungC.-L.ChangC.-P.A fast intensity hue saturation fusion technique with spectral adjustment for IKONOS imageryIEEE Geosci. Remote Sens. Lett.2004130931210.1109/LGRS.2004.834804 – reference: DouW.ChenY.LiX.SuiD.A general framework for component substitution image fusion: an implementation using fast image fusion methodComput. Geosci.20073321922810.1016/j.cageo.2006.06.008 – reference: ThomasC.RanchinT.WaldL.ChanussotJ.Synthesis of multispectral images to high spatial resolution: a critical review of fusion methods based on remote sensing physicsIEEE Trans. Geosci. Remote Sens.2008461301131210.1109/TGRS.2007.912448 – reference: AiazziB.BarontiS.SelvaM.Improving component substitution pansharpening through multivariate regression of MS+Pan dataIEEE Trans. Geosci. Remote Sens.2007453230323910.1109/TGRS.2007.901007 – reference: MuryninA.GorokhovskiyK.BondurV.IgnatievV.Analysis of large long-term remote sensing image sequence for agricultural yield forecastingProceedings of the 4th International Workshop on Image Mining, Theory and Applications IMTA-4 2013, with VISIGRAPP 2013, Barcelona, Spain2013PortugalSCITERGRASS4855 – reference: BondurV. G.DulovV. A.MuryninA. B.Ignat’evV. Yu.Retrieving sea-wave spectra using satelliteimagery spectra in a wide range of frequenciesIzv., Atmos. Ocean. Phys.20165263710.1134/S0001433816060049 – reference: EvdokimenkovV. N.KimR. V.Krasil’shchikovM. N.SebryakovG. G.The use of the neural network model of pilot control actions for their individually-adapted supportJ. Comput. Syst. Sci. Int.20155460910.1134/S10642307150400851338.932633376961 – reference: VizilterYu. V.ZheltovS. Yu.The use of projective morphologies for object detection and identification in imagesJ. Comput. Syst. Sci. Int.20094828210.1134/S10642307090201291176.682292555361 – reference: GurchenkovA. A.BochkarevaV. G.MuryninA. B.TrekinA. N.Image quality improvement by method of spatial spectrum extrapolationVestn. MGTU Baumana, Ser.: Estestv. Nauki201626591102 – reference: VivoneG.AlparoneL.ChanussotJ.dalla MuraM.GarzelliA.LicciardiG.RestainoR.WaldL.A critical comparison among pansharpening algorithmsIEEE Trans. Geosci. Remote Sens.2015 – reference: ChavezP. S.SidesJr.,_S. C.AndersonA. J.Comparison of three different methods to merge multiresolution and multispectral data: landsat TM and SPOT panchromaticPhotogramm. Eng. Remote Sens.199157295303 – reference: MilanfarP.Super-Resolution Imaging2011Boca Raton, London, New YorkCRC473 – reference: BochkarevaV. G.MatveevI. A.MuryninA. B.TsurkovV. I.Methods for improving image quality using spatial spectral analysisJ. Comput. Syst. Sci. Int.20155489710.1134/S10642307150600273432990 – reference: ChoiJ.YuK.KimY.A new adaptive component-substitution based satellite image fusion by using partial replacementIEEE Trans. Geosci. Remote Sens.20114929530910.1109/TGRS.2010.2051674 – reference: Aerospace Monitoring of Objects of Oil and Gas Facilities, Ed. by V. G. Bondur (Nauchnyi Mir, Moscow, 2012) [in Russian]. – reference: VizilterYu. V.VygolovO. V.ZheltovS. Yu.RubisA. Yu.A way to interconnect the multispectral images for improved vision systems by using the methods of diffusive morphologyJ. Comput. Syst. Sci. Int.20165559810.1134/S10642307160401223643040 – start-page: 48 volume-title: Proceedings of the 4th International Workshop on Image Mining, Theory and Applications IMTA-4 2013, with VISIGRAPP 2013, Barcelona, Spain year: 2013 ident: 6721_CR2 – volume: 2 start-page: 218 year: 2016 ident: 6721_CR7 publication-title: Mashin. Obuchen. Anal. Dannykh – volume: 49 start-page: 295 year: 2011 ident: 6721_CR18 publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2010.2051674 – volume: 54 start-page: 897 year: 2015 ident: 6721_CR9 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230715060027 – volume: 55 start-page: 242 year: 2016 ident: 6721_CR5 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230716020052 – volume-title: IEEE Trans. Geosci. Remote Sens. year: 2015 ident: 6721_CR11 – ident: 6721_CR20 – ident: 6721_CR1 – volume: 72 start-page: 591 year: 2006 ident: 6721_CR19 publication-title: Photogramm. Eng. Remote Sens. doi: 10.14358/PERS.72.5.591 – volume: 48 start-page: 282 year: 2009 ident: 6721_CR4 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230709020129 – volume: 55 start-page: 598 year: 2016 ident: 6721_CR13 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230716040122 – volume: 1 start-page: 309 year: 2004 ident: 6721_CR16 publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2004.834804 – volume: 33 start-page: 219 year: 2007 ident: 6721_CR17 publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2006.06.008 – volume: 2 start-page: 91 issue: 65 year: 2016 ident: 6721_CR8 publication-title: Vestn. MGTU Baumana, Ser.: Estestv. Nauki – volume: 52 start-page: 637 year: 2016 ident: 6721_CR6 publication-title: Izv., Atmos. Ocean. Phys. doi: 10.1134/S0001433816060049 – volume: 54 start-page: 609 year: 2015 ident: 6721_CR3 publication-title: J. Comput. Syst. Sci. Int. doi: 10.1134/S1064230715040085 – volume: 45 start-page: 3230 year: 2007 ident: 6721_CR15 publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2007.901007 – volume: 46 start-page: 1301 year: 2008 ident: 6721_CR12 publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2007.912448 – start-page: 473 volume-title: Super-Resolution Imaging year: 2011 ident: 6721_CR10 – volume: 57 start-page: 295 year: 1991 ident: 6721_CR14 publication-title: Photogramm. Eng. Remote Sens. |
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| SubjectTerms | Brightness Control Engineering Mechatronics Optimization Pattern Recognition and Image Processing Pixels Probabilistic methods Quality assessment Robotics Satellite imagery Satellites Spatial resolution Test procedures |
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| Title | Parameters optimization of the novel probabilistic algorithm for improving spatial resolution of multispectral satellite images |
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| Volume | 56 |
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