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

Naoto Nakamura, Shigeru Takano, Yoshihiro Okada, Koichi Niijima

    Research output: Contribution to journalConference article

    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.

    Original languageEnglish
    JournalEuropean Signal Processing Conference
    Publication statusPublished - Dec 1 2006
    Event14th European Signal Processing Conference, EUSIPCO 2006 - Florence, Italy
    Duration: Sep 4 2006Sep 8 2006

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Electrical and Electronic Engineering

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