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.
|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||The 14th European Signal Processing Conference|
|Abbreviated title||EUSIPCO 2006|
|Period||9/4/06 → 9/8/06|
All Science Journal Classification (ASJC) codes