ICA photographic encoding gear: Image bases towards IPEG

Yasuo Matsuyama; Hiroaki Kataoka; Naoto Katsumata; Keita Shimoda

doi:10.1109/IJCNN.2004.1380946

ICA photographic encoding gear: Image bases towards IPEG

Yasuo Matsuyama, Hiroaki Kataoka, Naoto Katsumata, Keita Shimoda

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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.

本文言語	English
ホスト出版物のタイトル	IEEE International Conference on Neural Networks - Conference Proceedings
ページ	2129-2134
ページ数	6
巻	3
DOI	https://doi.org/10.1109/IJCNN.2004.1380946
出版ステータス	Published - 2004
イベント	2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest 継続期間: 2004 7 25 → 2004 7 29

Other

Other	2004 IEEE International Joint Conference on Neural Networks - Proceedings
City	Budapest
Period	04/7/25 → 04/7/29

ASJC Scopus subject areas

Software

文献へのアクセス

10.1109/IJCNN.2004.1380946

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引用スタイル

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AB - 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.

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