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Soft Feature-Based Watermark Decoding with Insertion/Deletion Correction

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 4567))

Abstract

Hard decisions constitute the major problem in digital watermarking applications, especially when content adaptive embedding methods are used. Soft-decision decoding, on the other hand, has proved to be performance gaining, often realized during forward error correction. But despite this insight, no adaptive watermarking approach integrates the adaptation process into soft decoding, up to now. Further, insertion/deletion errors can occur in a content dependent watermarking system due to hard decisions if data is embedded only in some selected regions of the host signal. This kind of error usually desynchronizes the decoder and disables the correct watermark extraction. In this paper, we work out three fundamental properties of content dependent quantization-based watermarking. We show how the coupling between these properties and common soft-decision forward error correction decoding can be used to build up an overall soft processing watermarking. No pre-distortion has to be used, and hence, the image quality is not degraded. Even adaptation techniques can be used where it is computational infeasible to project a pre-distortion back onto the host image. Afterwards, we describe how to modify a common Viterbi decoder to enable the correction of insertion/deletion errors combined with our new soft decoding approach and hence improve the overall performance.

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© 2007 Springer-Verlag Berlin Heidelberg

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Schlauweg, M., Pröfrock, D., Müller, E. (2007). Soft Feature-Based Watermark Decoding with Insertion/Deletion Correction. In: Furon, T., Cayre, F., Doërr, G., Bas, P. (eds) Information Hiding. IH 2007. Lecture Notes in Computer Science, vol 4567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77370-2_16

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  • DOI: https://doi.org/10.1007/978-3-540-77370-2_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77369-6

  • Online ISBN: 978-3-540-77370-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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