This book describes a new technique for compressing cartoon images by taking advantage of the distinct color regions in an image and applying a spatially-based compression algorithm. The method for storing these regions involves a combination of Binary Run-Length Encoding and Huffman Encoding. The compression of cartoon images presented here is a lossy compression scheme that removes artifacts and antialiasing before encoding the image, and upon decoding the image, uses an edge-restricted blur filter in an attempt to smooth the edges of the decoded image. Algorithms to support gradient detection, their application, and storage are also described. With these algorithms and the proposed file type, on average the test images were 13.75 times more compact than the corresponding PNG file and 7.45 times more compact than the corresponding JPEG file, with a best bit per pixel ratio of 0.00987 bpp.
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Ty Taylor graduated from Case Western Reserve University's undergraduate program in Computer Science and from CWRU's graduate program with a specialty in Computer Graphics. Currently, he is a Software Development Engineer at Microsoft.
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes a new technique for compressing cartoon images by taking advantage of the distinct color regions in an image and applying a spatially-based compression algorithm. The method for storing these regions involves a combination of Binary Run-Length Encoding and Huffman Encoding. The compression of cartoon images presented here is a lossy compression scheme that removes artifacts and antialiasing before encoding the image, and upon decoding the image, uses an edge-restricted blur filter in an attempt to smooth the edges of the decoded image. Algorithms to support gradient detection, their application, and storage are also described. With these algorithms and the proposed file type, on average the test images were 13.75 times more compact than the corresponding PNG file and 7.45 times more compact than the corresponding JPEG file, with a best bit per pixel ratio of 0.00987 bpp. 84 pp. Englisch. Bestandsnummer des Verkäufers 9783659301803
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Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Taylor TyTy Taylor graduated from Case Western Reserve University s undergraduate program in Computer Science and from CWRU s graduate program with a specialty in Computer Graphics. Currently, he is a Software Development Engineer at. Bestandsnummer des Verkäufers 519627498
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock. Bestandsnummer des Verkäufers 3659301809
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book describes a new technique for compressing cartoon images by taking advantage of the distinct color regions in an image and applying a spatially-based compression algorithm. The method for storing these regions involves a combination of Binary Run-Length Encoding and Huffman Encoding. The compression of cartoon images presented here is a lossy compression scheme that removes artifacts and antialiasing before encoding the image, and upon decoding the image, uses an edge-restricted blur filter in an attempt to smooth the edges of the decoded image. Algorithms to support gradient detection, their application, and storage are also described. With these algorithms and the proposed file type, on average the test images were 13.75 times more compact than the corresponding PNG file and 7.45 times more compact than the corresponding JPEG file, with a best bit per pixel ratio of 0.00987 bpp. Bestandsnummer des Verkäufers 9783659301803
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Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes a new technique for compressing cartoon images by taking advantage of the distinct color regions in an image and applying a spatially-based compression algorithm. The method for storing these regions involves a combination of Binary Run-Length Encoding and Huffman Encoding. The compression of cartoon images presented here is a lossy compression scheme that removes artifacts and antialiasing before encoding the image, and upon decoding the image, uses an edge-restricted blur filter in an attempt to smooth the edges of the decoded image. Algorithms to support gradient detection, their application, and storage are also described. With these algorithms and the proposed file type, on average the test images were 13.75 times more compact than the corresponding PNG file and 7.45 times more compact than the corresponding JPEG file, with a best bit per pixel ratio of 0.00987 bpp.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 84 pp. Englisch. Bestandsnummer des Verkäufers 9783659301803
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Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Compression of Cartoon Images | A novel technique specific for the compression of low color palette images | Ty Taylor | Taschenbuch | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659301803 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 120714335
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