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.
|ホスト出版物のタイトル||IEEE International Conference on Neural Networks - Conference Proceedings|
|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月 25 → 2004 7月 29
|Other||2004 IEEE International Joint Conference on Neural Networks - Proceedings|
|Period||04/7/25 → 04/7/29|
ASJC Scopus subject areas