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Digital Watermarking SIMG 786 Advanced Digital Image Processing Mahdi Nezamabadi, Chengmeng Liu, Michael Su
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Different types of Digital Image Watermarking Visible: watermark is a secondary translucent overlaid into primary image. Invisible-fragile: invisible, any modification of the image will destroy the watermark. Invisible robust: watermark is perceptually not noticed and it can be recovered only with appropriate decoding mechanism. It’s robust to friendly or malicious attacks.
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Image Watermarking Using Phase Dispersion: Embedding I’(x,y) Watermarked image I(x,y) Source image (no watermark) M(x,y) Message Image, to be embedded, preferable to use the edge maps of an icon
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Image Watermarking Using Phase Dispersion: Embedding C(x,y) Carrier function. It is generated by the private key. It has random Fourier phase and non uniform magnitude An arbitrary constant α chosen to make the embedded message simultaneously invisible and robust to common processing Tiling the original image and embed the same image in each tile independently improves the robustness
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Embedding process illustration
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Image Watermarking Using Phase Dispersion: Extraction Extraction function M(x,y) can be calculated from M’(x,y) For a carrier with uniform amplitude
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Image Watermarking Using Phase Dispersion: Extraction
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Carrier Function Design Consideration P(x,y) denotes the autocorrelation function of the carrier function In order to improve the extracted image quality, it should be as close to a delta function as possible Human visual system falls off rapidly with increasing spatial frequency
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Carrier Function Design Most of the carrier energy should be concentrated in high frequencies to make invisible The phase of the carrier is generated using pseudo-random number generator with a user-specified key The magnitude is set to 0 at 0 frequency (DC value)
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Carrier Function Design Magnitude gradually increased with increasing spatial frequency up to about 1/5 of Nyquist frequency For frequencies greater than 1/5 of Nuquist frequency, the carrier envelope is derived from the Contrast Sensitivity Function (CSF) data The CSF provides a measure of sensitivity of the average observer to changes in contrast at a given spatial frequency
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Contrast Sensitivity Function Reciprocal of the CSF can be used to determine the carrier magnitude needed at a given frequency to bring the embedded signal just below the threshold of detectability by an average observer
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Message Template Design T(x,y): Message Template Function, the image resulting from placing a positive delta function at every message location This is for binary message
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Rotation/Scale Detection and Correction Moment normalization, set local mean of the watermarked image to 0 and its standard deviation to a target value σ d Do autocorrelation on the processed image and then process with a high-pass filter
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Rotation/Scale Detection and Correction The ability to handle rotation and scale is a fundamental requirement of robust data embedded techniques
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Thank you, Questions?
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