An improved scalar quantization-based digital video watermarking scheme for H.264/AVC

• Main Author: Golikeri, Adarsh
• Language: English
• Published: 2009
• Online Access: http://hdl.handle.net/2429/16749

Digital watermarking, a robust information-embedding technique, has gained significant attention in the past few years, due to the spread of illegal redistribution and unauthorized use of digital multimedia content. In general, a watermark is a secure, perceptually invisible, unique, low-power signal which is robustly inserted into original digital content. In this thesis, we propose an improved, scalar quantization-based digital video watermarking scheme. The aim is to enable video content producers and owners to embed a robust watermark into their video. If such a scheme is implemented on a large scale, it could serve as a deterrent against rampant distribution and sharing of pirated copies of video content. Our scheme embeds a locally adaptive, robust, Rate-Distortion (R-D) optimized watermark signal into the transform domain of the macroblock residual. This ensures that watermark signal is embedded in the most robust manner, with least visual distortion. We use a unique perceptual mask which limits the amount of spatial and temporal distortion due to watermark insertion. Therefore, our scheme achieves higher watermarked picture quality compared to existing schemes. Our scheme is designed with a built-in bit-rate controller, which ensures that the watermark bits are distributed in proportion to the visual importance of different regions of the video frame. We adapt our scheme to H.264/AVC, which is the latest video coding standard. Our scheme overcomes the challenges for watermarking of H.264/AVC video, namely high compression efficiency, small residual data, integer transform, R-D coding decisions and video bit-rate control. Experimental results on several standard video sequence show that compared to existing quantization-based watermarking schemes, our proposed scheme is significantly more robust in terms of Bit Error Rate (BER) to different types of attacks, including video compression and decompression, transcoding, low-pass filtering, scaling, rotation and collusion. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate