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Intelligent system for image compression. (Khashman, Adnan,)
Bibliographical information (record 269964)
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Intelligent system for image compression.
Author:
 Khashman, Adnan, Search Author in Amazon Books

Publisher:
Insticc-Inst Syst Technologies Information Control & Communication,
ISBN:
 978-972-8865-89-4
Edition:
 2007.
Classification:
 QA76
Detailed notes
    - The parallel processing capability of neural networks provides efficient means for processing images with large amount of data. Image compression using Discrete Cosine Transforms (DCT) is a lossy compression method where at higher compression ratios the quality of the compressed images is reduced, thus the need for finding an optimum compression ratio that combines high compression and good quality. This paper suggests that the image intensity can affect the choice of an optimum compression ratio. A neural network will be trained to establish the non-linear relationship between the image intensity and its compression ratios in search for an optimum ratio. Experimental results suggest that a trained neural network can relate image intensity or pixel values to its compression ratio and thus can be successfully used to predict optimum DCT compression ratios for different images.
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Library
Section
EOL-1741
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NEU Grand LibraryOnline (QA76 .I58 2007)
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