抄録
This paper proposes a blind image separation method using wavelet transform and an entropy-maximization algorithm. Our blind separation algorithm is an improved version of the entropy-maximization algorithms presented by Bell- Sejnowsky and Amari. These algorithms work well for signals having a supergaussian distribution, such as speech and audio. The proposed method is to apply the improved algorithm to the wavelet coefficients of a natural image, whose distribution is close to supergaussian. Our method successfully reconstruct twelve images hidden in another twelve images which are similar each other.
本文言語 | 英語 |
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出版ステータス | 出版済み - 2006 |
イベント | The 14th European Signal Processing Conference - 継続期間: 9月 4 2006 → 9月 8 2006 |
会議
会議 | The 14th European Signal Processing Conference |
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Abbreviated title | EUSIPCO 2006 |
Period | 9/4/06 → 9/8/06 |
All Science Journal Classification (ASJC) codes
- 信号処理
- 電子工学および電気工学