Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/299509
Title: Parallel processing model for efficient remote sensing image based on pipeline
Researcher: Ramesh P S
Guide(s): Letitia S
Keywords: Parallel processing
Remote sensing
Image processing
University: Anna University
Completed Date: 2019
Abstract: Usually 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
Pagination: xvi,147xp.
URI: http://hdl.handle.net/10603/299509
Appears in Departments:Faculty of Information and Communication Engineering

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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
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80_recommendation.pdf117.18 kBAdobe PDFView/Open
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