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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Comparison of Lossless Image Compression Techniques based on Context Modeling

Comparison of Lossless Image Compression Techniques based on Context Modeling

El-Ghoboushi, Mohammad

Paperback

ApplicationsProgramming

ISBN10: 3656932840
ISBN13: 9783656932840
Publisher: Bod Third Party Titles
Published: Apr 16 2015
Pages: 84
Weight: 0.27
Height: 0.20 Width: 5.83 Depth: 8.27
Language: English
Master's Thesis from the year 2014 in the subject Computer Science - Software, course: Image Processing, language: English, abstract: In this thesis various methods for lossless compression of source image data are analyzed and discussed. The main focus in this work is lossless compression algorithms based on context modeling using tree structure. We are going to compare CALIC, GCT-I algorithms to the JPEG2000 standard algorithm which will be considered the reference of comparison. This work includes research on how to modify CALIC algorithm in continuous-tone mode by truncating tails of the error histogram which may lead to improve CALIC compression performance. Also, we are going to propose a modification to CALIC in binary mode by eliminating error feedback mechanism. As when any pixel to be encoded has a different grey level than any of the neighboring pixels, CALIC triggers an escape sequence that switches the algorithm from binary mode to continuous-tone mode. Which means in this case the pixel will be treated as if it was in continuous-tone region. This minor modification should improve CALIC performance in binary images. Finally, we are going to discuss the GCT-I on medical images and compare results to the JPEG2000 standard.

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