ICA photographic encoding gear: Image bases towards IPEG

Yasuo Matsuyama, Hiroaki Kataoka, Naoto Katsumata, Keita Shimoda

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    Independent component analysis (ICA) is applied to image coding. There, new design methods for ICA bases are presented. The new feature of this learning algorithm includes the weak guidance, or decreasing supervisory information. The weak guidance reduces the permutation indeterminacy which is unavoidable in usual ICA algorithms. In view of the image compression, this effect corresponds to the generation of image bases honoring the space frequency's neighborhood and 2-D ordering. Following the presentation of this learning algorithm, experiments are performed to obtain serviceable ICA bases. Finally, image compression and restoration are demonstrated to show the eligibility for "image. ipeg." Other applications such as image retrieval are also commented.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
    Pages2129-2134
    Number of pages6
    Volume3
    DOIs
    Publication statusPublished - 2004
    Event2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest
    Duration: 2004 Jul 252004 Jul 29

    Other

    Other2004 IEEE International Joint Conference on Neural Networks - Proceedings
    CityBudapest
    Period04/7/2504/7/29

    ASJC Scopus subject areas

    • Software

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  • Cite this

    Matsuyama, Y., Kataoka, H., Katsumata, N., & Shimoda, K. (2004). ICA photographic encoding gear: Image bases towards IPEG. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 3, pp. 2129-2134) https://doi.org/10.1109/IJCNN.2004.1380946