Scientific Essay from the year 2014 in the subject Electrotechnology, Cairo University, language: English, abstract: Context-based adaptive lossless image codec (CALIC) is one of the most efficient lossless encoding techniques for both continuous-tone and binary images. This Paper includes a research on how to modify CALIC algorithm in continuous-tone mode by truncating tails of the error histogram and using an escape mechanism to code the errors beyond the truncated code range, if they occur which improve CALIC compression performance. Also, we are going to propose a modification to CALIC in binary mode by eliminating error feedback mechanism. This minor modification should improve CALIC performance in binary images.
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Mohamed El-Ghoboushi received his B.E. in Electronics and Electrical communications Engineering from Cairo University, Giza, Egypt, in 2007, and a M.S. degree in Electronics and Electrical communications Engineering from Cairo University, Giza, Egypt, in 2014, He received the Ph.D. degree in electrical communications engineering from Suez Canal University, Ismailia, Egypt, in 2018
Scientific Essay from the year 2014 in the subject Electrotechnology, Cairo University, language: English, abstract: Context-based adaptive lossless image codec (CALIC) is one of the most efficient lossless encoding techniques for both continuous-tone and binary images. This Paper includes a research on how to modify CALIC algorithm in continuous-tone mode by truncating tails of the error histogram and using an escape mechanism to code the errors beyond the truncated code range, if they occur which improve CALIC compression performance. Also, we are going to propose a modification to CALIC in binary mode by eliminating error feedback mechanism. This minor modification should improve CALIC performance in binary images.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Scientific Essay from the year 2014 in the subject Electrotechnology, Cairo University, language: English, abstract: Context-based adaptive lossless image codec (CALIC) is one of the most efficient lossless encoding techniques for both continuous-tone and binary images. This Paper includes a research on how to modify CALIC algorithm in continuous-tone mode by truncating tails of the error histogram and using an escape mechanism to code the errors beyond the truncated code range, if they occur which improve CALIC compression performance.Also, we are going to propose a modification to CALIC in binary mode by eliminating error feedback mechanism. This minor modification should improve CALIC performance in binary images. 12 pp. Englisch. Nº de ref. del artículo: 9783656930730
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Scientific Essay from the year 2014 in the subject Electrotechnology, Cairo University, language: English, abstract: Context-based adaptive lossless image codec (CALIC) is one of the most efficient lossless encoding techniques for both continuous-tone and binary images. This Paper includes a research on how to modify CALIC algorithm in continuous-tone mode by truncating tails of the error histogram and using an escape mechanism to code the errors beyond the truncated code range, if they occur which improve CALIC compression performance.Also, we are going to propose a modification to CALIC in binary mode by eliminating error feedback mechanism. This minor modification should improve CALIC performance in binary images. Nº de ref. del artículo: 9783656930730
Cantidad disponible: 1 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Improving Calic Compression Performance on both Continuous-Tone and Binary Images | Mohammad El-Goboushi (u. a.) | Taschenbuch | 12 S. | Englisch | 2015 | GRIN Verlag | EAN 9783656930730 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 104733615
Cantidad disponible: 5 disponibles