Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/260249
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dc.coverage.spatialEnhanced Lossless Encoding and Decoding Scheme for Complex Satellite Images
dc.date.accessioned2019-09-27T11:11:20Z-
dc.date.available2019-09-27T11:11:20Z-
dc.identifier.urihttp://hdl.handle.net/10603/260249-
dc.description.abstractnewline ABSTRACT newlineToday, satellite images have been widely used in a large number of applications, ranging newlinefrom independent land mapping services to government and military activities. However, at newlinethe time of capturing satellite images we gain high resolution spectral information, which newlinegenerates a massively large image data sets. Therefore, storage and transmission of this newlineamount of data has become one of the greatest challenges. The only remedy for this challenging newlineproblem is compression, by which the storage and transmission of data can be increased. newlineSeveral satellite image compression techniques have been introduced aiming to newlinereduce the image size and improve user interaction with the information. newlineThis research is intended to develop a lossless compression mechanism which suits for newlineall types of satellites images. The satellite images are very complex and covers a wide area, newlinewith the combination of several colors and scenes. Based on eliminating these redundancies newlinein image blocks compression can be achieved. newlineIn this research work as an initial step, analysis of different compression techniques newlineis carried out by compressing different satellite images. The Mean Square Error, Signal to newlineNoise Ratio and Peak Signal to Noise Ratio values are calculated. The satellite images are newlinecompressed by applying different bitrates. In order to perform the analysis process, sixteen newlinedifferent satellite images and eight compression techniques were chosen. newlineAlgorithm with both the properties of Discrete Cosine Transform and DiscreteWavelet newlineTransform is developed and the performance of it is measured. A color component based newlinecompression is developed with two phases, the drawback of method 1 is rectified in method newline2 and the compression method yields better results. newlineIn order to overcome the performance of color component based compression a trail newlinewith block similarity had been done with two phases. The second phase of this method newlineconquer a comparatively better result than JPEG. newlineFinally the basic principles of H.264 is optimized t
dc.format.extent160
dc.languageEnglish
dc.relation252
dc.rightsuniversity
dc.titleEnhanced Lossless Encoding and Decoding Scheme for Complex Satellite Images
dc.title.alternative-
dc.creator.researcherSanjith S
dc.subject.keywordEngineering and Technology,Computer Science,Computer Science Software Engineering
dc.description.noteEnhanced Lossless Encoding and Decoding Scheme for Complex Satellite Images
dc.contributor.guideGanesan R
dc.publisher.placeKanyakumari
dc.publisher.universityNoorul Islam Centre for Higher Education
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered12/08/2013
dc.date.completed21/10/2017
dc.date.awarded30/11/2018
dc.format.dimensionsA4
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering

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acknowledgement.pdfAttached File41.78 kBAdobe PDFView/Open
chapter iii.pdf13.57 MBAdobe PDFView/Open
chapter ii.pdf100.97 kBAdobe PDFView/Open
chapter i.pdf586.04 kBAdobe PDFView/Open
chapter iv.pdf779.82 kBAdobe PDFView/Open
chapter viii.pdf44.12 kBAdobe PDFView/Open
chapter vii.pdf1.26 MBAdobe PDFView/Open
chapter vi.pdf817.13 kBAdobe PDFView/Open
chapter v.pdf1.57 MBAdobe PDFView/Open
front page.pdf103.66 kBAdobe PDFView/Open
list of figures.pdf44.02 kBAdobe PDFView/Open
list of publications.pdf52.47 kBAdobe PDFView/Open
references.pdf111.15 kBAdobe PDFView/Open
table of content.pdf44.06 kBAdobe PDFView/Open


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