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Author: search.filters.author.Khawne, AmnachSubject: search.filters.subject.Human visual system

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    Image watermarking based on adaptive models of human visual perception
    (2010-01-01)
    Khawne, Amnach
    ;
    Hamamoto, Kazuhiko
    ;
    Chitsobhuk, Orachat
    This paper proposes a digital image watermarking based on adaptive models of human visual perception. The algorithm exploits the local activities estimated from wavelet coefficients of each subband to adaptively control the luminance masking. The adaptive luminance is thus delicately combined with the contrast masking and edge detection and adopted as a visibility threshold. With the proposed combination of adaptive visual sensitivity parameters, the proposed perceptual model can be more appropriate to the different characteristics of various images. The weighting function is chosen such that the fidelity, imperceptibility and robustness could be preserved without making any perceptual difference to the image quality. © 2010 The Institute of Electrical Engineers of Japan.
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    Ultrasonic echo image adaptive watermarking using the just-noticeable difference estimation
    (2009-12-01)
    Khawne, Amnach
    ;
    Hamamoto, Kazuhiko
    ;
    Chitsobhuk, Orachat
    Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.