MASTER THESIS Video Watermarking - Computer Graphics Group ...

watermark, i.e. values of the watermark elements are either 0 or 1. When 0 is to
be embedded into a pixel, the value of the pixel color sample is altered to the
nearest even value. Similarly, when 1 is to be embedded into a pixel, the value of
the pixel color sample is altered to the nearest odd value.
The detection process then consists in reading even pixel color sample values
as 0 and odd values as 1.
This method is not robust very much because the watermark can be
completely destroyed by altering all the sample values to become either odd or
even. These modifications definitely do not severely degrade quality of the
picture; the method is mentioned only to give more comprehension what
watermarking is about.
Watermarking of uncompressed images in frequency domain requires doing
the particular frequency transform of the image before the embedding and the
inverse transform after the embedding.
The result of the transform is frequency spectrum of the image. Value of
each coefficient Ci represents amplitude of the corresponding frequency. In this
case, the following embedding formula is better than formula (1) because
especially small amplitudes would be altered too much using formula (1), which
would lead to perceptible distortion in the picture:
It must be mentioned that this formula is invertible only if Ci is not zero,
therefore implementations must count on this.
The classical approach to watermarking of a compressed image is to
decompress the image, embed the watermark using spatial or frequency domain
technique and recompress the image again. Full decompression and
recompression of the image can be computationally expensive, especially
concerning a video sequence.
The majority of compression algorithms used in image and video formats are
based on a frequency transform, thus watermarking in frequency domain can be
applied directly to coefficients of that transform. In practice, it means that the
compressed image is partially decoded to obtain those transform coefficients,
watermarked and encoded back again.
With certain knowledge of the particular transform, spatial domain
watermarking is possible in a such way as described in the previous paragraph.
For example, 2D-DCT of a block of size 8×8 can be implemented as
multiplication of the block by a transform matrix from left and the same but
transposed matrix from right. Forward (matrix Tf) and inverse (matrix Ti)
transforms are then expressed by the following formulas (P is a 8×8 matrix of
11
(2)