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Open Access Estimating Digital Watermark Synchronization Signal Using Partial Pixel Least Squares

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To read a digital watermark from printed images requires that the watermarking system read correctly after affine distortions. One way to recover from affine distortions is to add a synchronization signal in the Fourier frequency domain and use this synchronization signal to estimate the applied affine distortion. If the synchronization signal contains a collection of frequency impulses, then a least squares match of frequency impulse locations results in a reasonably accurate linear transform estimation. Nearest neighbor frequency impulse peak location estimation provides a good rough estimate for the linear transform, but a more accurate refinement of the least squares estimate is accomplished with partial pixel peak location estimates. In this paper we will show how to estimate peak locations to any desired accuracy using only the complex frequencies computed by the standard DFT. We will show that these improved peak location estimates result in a more accurate linear transform estimate. We conclude with an assessment of detector robustness that results from this improved linear transformation accuracy.
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Keywords: Watermarking; frequency interpolation; linear transform estimation; phase estimation; synchronization signal

Document Type: Research Article

Publication date: January 26, 2020

This article was made available online on January 26, 2020 as a Fast Track article with title: "Estimating digital watermark synchronization signal using partial pixel least squares".

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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