Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/299509
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dc.coverage.spatialParallel processing model for efficient remote sensing image based on pipeline
dc.date.accessioned2020-09-16T09:58:32Z-
dc.date.available2020-09-16T09:58:32Z-
dc.identifier.urihttp://hdl.handle.net/10603/299509-
dc.description.abstractUsually image processing is the combination of images in which the input is an image and it generates an output as a set of characteristics of an image This research work goes with three major contributions and as the first contribution this research work implements the basic image processing techniques for satellite image enhancement based on parallel processing The model proposes a pipeline on parallel image processing and it mainly concentrates on the existing effectiveness of remote sensing image processing that is usually not up to the streak Parallel processing in image processing aids in separating a huge image into lesser and it parallely does processing Further the proposed model comprises of four phases termed i Pipeline Processing Model Design ii Implementation of parallel processing of meta algorithm iii Template matching and Document Classification iv Structure of Image Document Inspection In this developed model every task is normally done in a different manner and each of them achieves diverse task in dissimilar way The experimental outcome displays the efficacy of pipeline based parallel processing approach in the progression of remote sensing image along huge data amount The second contribution of this research work is proposing a new parallel classification methodology by a new clustering and classification concept newline
dc.format.extentxvi,147xp.
dc.languageEnglish
dc.relationp.135-145
dc.rightsuniversity
dc.titleParallel processing model for efficient remote sensing image based on pipeline
dc.title.alternative
dc.creator.researcherRamesh P S
dc.subject.keywordParallel processing
dc.subject.keywordRemote sensing
dc.subject.keywordImage processing
dc.description.note
dc.contributor.guideLetitia S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registeredn.d.
dc.date.completed2019
dc.date.awarded09/08/2019
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdf.pdfAttached File22.85 kBAdobe PDFView/Open
02_certificates.pdf.pdf917.85 kBAdobe PDFView/Open
03_abstracts.pdf.pdf5.96 kBAdobe PDFView/Open
04_acknowledgements.pdf.pdf3.91 kBAdobe PDFView/Open
05_contents.pdf.pdf9.8 kBAdobe PDFView/Open
06_list_of_tables.pdf.pdf6.71 kBAdobe PDFView/Open
07_list_of_figures.pdf.pdf4 kBAdobe PDFView/Open
08_chapter1.pdf.pdf93.31 kBAdobe PDFView/Open
09_chapter2.pdf.pdf54.99 kBAdobe PDFView/Open
10_chapter3.pdf.pdf239.65 kBAdobe PDFView/Open
11_chapter4.pdf.pdf1.98 MBAdobe PDFView/Open
12_chapter5.pdf.pdf525.57 kBAdobe PDFView/Open
13_conclusion6.pdf.pdf21.85 kBAdobe PDFView/Open
14_references.pdf.pdf49.19 kBAdobe PDFView/Open
15_publications.pdf.pdf9.96 kBAdobe PDFView/Open
80_recommendation.pdf117.18 kBAdobe PDFView/Open


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