Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas
Uncompressed multimedia data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density, processor speeds, and digital communication system performance, demand for data storage capacity and data-transmission bandwidth continues to outstrip the c...
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2004
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Online Access: | http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2004~D_20040525_170905-97621/DS.005.0.02.ETD |
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ndltd-LABT_ETD-oai-elaba.lt-LT-eLABa-0001-E.02~2004~D_20040525_170905-976212013-11-16T03:57:37Z2004-05-25litInformaticsDusevičius, VytautasEfektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimasAnalysis and Development of Efficient Image Compression AlgorithmLithuanian Academic Libraries Network (LABT)Uncompressed multimedia data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density, processor speeds, and digital communication system performance, demand for data storage capacity and data-transmission bandwidth continues to outstrip the capabilities of available technologies. The recent growth of data intensive multimedia-based web applications even more sustained the need for more efficient ways to encode such data. There are two types of image compression schemes – lossless and lossy algorithms. In lossless compression schemes, the reconstructed image, after compression, is numerically identical to the original image. However lossless compression can only achieve a modest amount of compression. An image reconstructed following lossy compression contains degradation relative to the original. Often this is because the compression scheme completely discards redundant information. However, lossy schemes are capable of achieving much higher compression. The aim of this research is to create an efficient lossy image compression algorithm, using heuristic data clusterization methods; perform experiments of the new algorithm, measure its performance, analyze advantages and disadvantages of the proposed method, propose possible improvements and compare it with other popular algorithms. In this paper is presented new algorithm for image compression, which uses data base of popular image fragments. Proposed algorithm is... [to full text]KlasterizacijaVaizdų suspaudimasImage compressionClusterizationMaster thesisKazanavičius, EgidijusJasinevičius, RaimundasMatickas, Jonas KazimierasPlėštys, RimantasValantinas, JonasPranevičius, HenrikasMockus, JonasBarauskas, RimantasTelksnys, LaimutisKaunas University of TechnologyKaunas University of Technologyhttp://vddb.library.lt/obj/LT-eLABa-0001:E.02~2004~D_20040525_170905-97621LT-eLABa-0001:E.02~2004~D_20040525_170905-97621KTU-LABT20040525-170905-97621http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2004~D_20040525_170905-97621/DS.005.0.02.ETDUnrestrictedapplication/pdf |
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Lithuanian |
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Dissertation |
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Informatics Klasterizacija Vaizdų suspaudimas Image compression Clusterization |
spellingShingle |
Informatics Klasterizacija Vaizdų suspaudimas Image compression Clusterization Dusevičius, Vytautas Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
description |
Uncompressed multimedia data requires considerable storage capacity and transmission bandwidth. Despite rapid progress in mass-storage density, processor speeds, and digital communication system performance, demand for data storage capacity and data-transmission bandwidth continues to outstrip the capabilities of available technologies. The recent growth of data intensive multimedia-based web applications even more sustained the need for more efficient ways to encode such data.
There are two types of image compression schemes – lossless and lossy algorithms. In lossless compression schemes, the reconstructed image, after compression, is numerically identical to the original image. However lossless compression can only achieve a modest amount of compression. An image reconstructed following lossy compression contains degradation relative to the original. Often this is because the compression scheme completely discards redundant information. However, lossy schemes are capable of achieving much higher compression.
The aim of this research is to create an efficient lossy image compression algorithm, using heuristic data clusterization methods; perform experiments of the new algorithm, measure its performance, analyze advantages and disadvantages of the proposed method, propose possible improvements and compare it with other popular algorithms.
In this paper is presented new algorithm for image compression, which uses data base of popular image fragments. Proposed algorithm is... [to full text] |
author2 |
Kazanavičius, Egidijus |
author_facet |
Kazanavičius, Egidijus Dusevičius, Vytautas |
author |
Dusevičius, Vytautas |
author_sort |
Dusevičius, Vytautas |
title |
Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
title_short |
Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
title_full |
Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
title_fullStr |
Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
title_full_unstemmed |
Efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
title_sort |
efektyvaus vaizdų suspaudimo algoritmo sudarymas ir tyrimas |
publisher |
Lithuanian Academic Libraries Network (LABT) |
publishDate |
2004 |
url |
http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2004~D_20040525_170905-97621/DS.005.0.02.ETD |
work_keys_str_mv |
AT duseviciusvytautas efektyvausvaizdususpaudimoalgoritmosudarymasirtyrimas AT duseviciusvytautas analysisanddevelopmentofefficientimagecompressionalgorithm |
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