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dc.contributorBiradar, Chandrashekharen_US
dc.contributorRoy, Partha Sarathien_US
dc.creatorJeganathan, C.en_US
dc.date2013-11-28en_US
dc.date.accessioned2017-07-23T23:13:59Z
dc.date.available2017-07-23T23:13:59Z
dc.identifierhttp://www.irosss.org/ojs/index.php/IJARSGG/article/view/39en_US
dc.identifierhttps://www.researchgate.net/profile/Jeganathan_Chockalingam/publication/256082841_INTELLIGENT_OBJECT_BASED_SMOOTHING_AN_ALGORITHM_FOR_REMOVING_NOISES_IN_THE_CLASSIFIED_SATELLITE_IMAGE/links/0deec53194e10c3e65000000/INTELLIGENT-OBJECT-BASED-SMOOTHING-AN-ALGORITHM-FOR-REMOVING-NOISES-IN-THE-CLASSIFIED-SATELLITE-IMAGE.pdfen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/90rPuPTAen_US
dc.identifier.citationC. Jeganathan, Chandrashekhar Biradar, Partha Sarathi Roy. (28/11/2013). INTELLIGENT OBJECT BASED SMOOTHING: AN ALGORITHM FOR REMOVING NOISES IN THE CLASSIFIED SATELLITE IMAGE. International Journal of Advancement in Remote Sensing, GIS and Geography, 1 (1), pp. 32-41.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/7225
dc.description.abstractThe existing smoothing algorithms like mean, median, majority/mode filters are not efficient in smoothing the classified image derived from the satellite data. Mean filter alters original class pattern and also it is influenced by the outliers in the neighbors. Though Median filter does not alter the values it does affect the shape of the class extent. The majority filter also suffers from a big disadvantage that it eliminates linear features and in the common edge between two classes it will blindly follow the majority rule though there is no noise. Also, these smoothing filters, by and large dependent on kernel size, pixel size and the shape of the input classes. Keeping these limitations in view the study attempted a kernel & pixel size-independent smoothing algorithm for smoothing classified satellite data, which must also cognitively, considers the neighbourhood contiguity. In this approach, spatial connectivity functions are utilized to characterize the neighborhood as objects, which are then supplemented with structuring element to selectively incorporate morphological operators like erosion and dilation for smoothing the classified image. This object oriented morphological smoothing algorithm, its effectiveness and efficiency has been studied in this research. It was found that the proposed algorithm efficiently maintained the shape and area than other conventional smoothing algorithms.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherInternational Research Operation in Sciences and Social Sciences (IROSS)en_US
dc.rightsCC-BY-4.0en_US
dc.sourceInternational Journal of Advancement in Remote Sensing, GIS and Geography;1,(2013) Pagination 32,41en_US
dc.subjectobject based smoothingen_US
dc.subjectclassified imageen_US
dc.subjectmean filteren_US
dc.subjectmedian filter and majority filteren_US
dc.titleINTELLIGENT OBJECT BASED SMOOTHING: AN ALGORITHM FOR REMOVING NOISES IN THE CLASSIFIED SATELLITE IMAGEen_US
dc.typeJournal Articleen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.creator.ID-typeORCIDen_US
cg.contributor.centerBirla Institute of Technology - BIT Mesraen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerUniversity of Hyderabad, University Center of Earth and Space Science - UOHYD - UCESSen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.contactjeganathanc@bitmesra.ac.inen_US
dc.identifier.statusOpen accessen_US


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