Progressive exponential clustering-based steganography

Chang Tsun Li, Yue Li

    Research output: Contribution to journalArticlepeer-review


    Cluster indexing-based steganography is an important branch of data-hiding techniques. Such schemes normally achieve good balance between high embedding capacity and low embedding distortion. However, most cluster indexing-based steganographic schemes utilise less efficient clustering algorithms for embedding data, which causes redundancy and leaves room for increasing the embedding capacity further. In this paper, a new clustering algorithm, called progressive exponential clustering (PEC), is applied to increase the embedding capacity by avoiding redundancy. Meanwhile, a cluster expansion algorithm is also developed in order to further increase the capacity without sacrificing imperceptibility.

    Original languageEnglish
    Article number212517
    JournalEurasip Journal on Advances in Signal Processing
    Publication statusPublished - 2010


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