Reconstruction of hidden images using wavelet transform and an entropy-maximization algorithm

Naoto Nakamura; Shigeru Takano; Yoshihiro Okada; Koichi Niijima

Reconstruction of hidden images using wavelet transform and an entropy-maximization algorithm

Naoto Nakamura, Shigeru Takano, Yoshihiro Okada, Koichi Niijima

附属図書館付設教材開発センター

研究成果: Contribution to conference › Paper › 査読

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
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 4 2006 → 9 8 2006

会議

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

Signal Processing
Electrical and Electronic Engineering

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引用スタイル

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title = "Reconstruction of hidden images using wavelet transform and an entropy-maximization algorithm",

abstract = "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.",

author = "Naoto Nakamura and Shigeru Takano and Yoshihiro Okada and Koichi Niijima",

year = "2006",

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note = "The 14th European Signal Processing Conference, EUSIPCO 2006 ; Conference date: 04-09-2006 Through 08-09-2006",

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TY - CONF

T1 - Reconstruction of hidden images using wavelet transform and an entropy-maximization algorithm

AU - Nakamura, Naoto

AU - Takano, Shigeru

AU - Okada, Yoshihiro

AU - Niijima, Koichi

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

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T2 - The 14th European Signal Processing Conference

Y2 - 4 September 2006 through 8 September 2006

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