In this paper we concentrate on robust image watermarking (i.e. capable of resisting common signal processing
operations and intentional attacks to destroy the watermark) based on image features. Kutter et al.7 motivated
that well chosen image features survive admissible image distortions and hence can benefit the watermarking
process. These image features are used as location references for the region in which the watermark is embedded.
To realize the latter, we make use of previous work16 where a ring-shaped region, centered around an image
feature is determined for watermark embedding. We propose to choose a specific sequence of image features
according to strict criteria so that the image features have large distance to other chosen image features so
that the ring shaped embedding regions do not overlap. Nevertheless, such a setup remains prone to insertion,
deletion and substitution errors. Therefore we applied a two-step coding scheme similar to the one employed by
Coumou and Sharma4 for speech watermarking. Our contribution here lies in extending Coumou and Sharma's
one dimensional scheme to the two dimensional setup that is associated with our watermarking technique.
The two-step coding scheme concatenates an outer Reed-Solomon error-correction code with an inner, blind,
synchronization mechanism.
Digital watermarking of images, the act of hiding a message inside an image, is still a young, yet growing, research
field. We have developed an environment in Matlab that allows researchers, teachers and students alike to get
acquainted with the concepts of digital image watermarking techniques. This user-friendly environment is divided
into two parts. First there is the educational part, which visualizes watermarking techniques and gives users the
possibility to observe the results of various attacks. This part can be used as a demonstrator during lectures
on image watermarking. The second part is dedicated to a benchmarking tutorial section, which allows users to
easily compare watermarking techniques. A user new to the field of benchmarking can simply insert existing or
newly developed watermarking algorithms, attacks and metrics into the benchmarking tutorial environment. We
also included an attack section that is easy to adjust and extend with new attacks. Furthermore, we provided a
report generator that will summarize all the benchmarking results in a clear, visually appealing manner. Through
the use of Matlab, we were able to make a framework that is easy to modify, update and expand and also enables
everyone to use the existing signal processing libraries of Matlab.
Using the scalable video coding (SVC) extension of the H.264/AVC video coding standard, encoding a video sequence
yields a quality, resolution, and frame-rate scalable bit-stream. This means that a version of the video sequence with a
lower resolution, quality and/or frame rate can be obtained by extracting selected parts of the scalable bit-stream, without
the need for re-encoding. In this way, easy adaptation of the video material to the end-users' device (computational
power and display resolution) and channel characteristics is possible. In this paper, the use of unequal error protection
(UEP) for error-resilient transmission of H.264/SVC-encoded video sequences is studied. By using unequal error
protection, graceful degradation of the video quality is achieved when the targeted packet loss probability is exceeded. In
contrast, using equal error protection (EEP), an immediate and dramatic drop in quality is observed under these
conditions.
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