The objective of this thesis is to present a robust watermarking algorithm for H.264 and to address challenges in compressed-domain video watermarking. To embed a perceptually invisible watermark in highly compressed H.264 video, we use a human visual model. We extend Watson's human visual model developed for 8x8 DCT block to the 4x4 block used in H.264. In addition, we use P-frames to increase the watermark payload. The challenge in embedding the watermark in P-frames is that the video bit rate can increase significantly. By using the structure of the encoder, we significantly reduce the increase in video bit rate due to watermarking. Our method also exploits both temporal and texture
masking.
We build a theoretical framework for watermark detection using a likelihood ratio test. This framework is used to develop two different video watermark detection algorithms; one detects the watermark only from watermarked coefficients and one detects the watermark from all the ac coefficients in the video. These algorithms can be used in different video watermark detection applications where the detector knows and does not know the precise location of watermarked coefficients. Both watermark detection schemes obtain video watermark detection with controllable detection performance. Furthermore, control of the detector's performance lies completely with the detector and does not place any burden on the watermark embedding system. Therefore, if the video has been attacked, the detector can maintain the same detection performance by using more frames to obtain its detection response. This is not the case with images, since there is a limited number of coefficients that can be watermarked in each image before the watermark is visible.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/16267 |
| Date | 05 June 2007 |
| Creators | Noorkami, Maneli |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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