Title :
Improving data hiding performance by using quantization in a projected domain
Author :
P?©rez-Gonz??lez, Fernando ; Balado, F?©lix
Author_Institution :
Signal Theor. & Commun. Dept., Vigo Univ., Spain
fDate :
6/24/1905 12:00:00 AM
Abstract :
The quantization of a linear projective transformation first proposed by Chen and Wornell is shown to allow for much better performance figures than those yielded by previous approaches. The procedure to achieve this improvement is explained through the proposal and analysis of an improved data hiding method called quantized projection (QP), based in the quantization of a statistic similar to those used at detection in spread-spectrum algorithms. Both the theoretical analysis and the empirical validation show that projection-based methods exhibit huge performance improvements over existing ones under the same conditions - i.e. same degree of diversity and level of random additive attacking distortion.
Keywords :
data encapsulation; quantisation (signal); statistical analysis; watermarking; data hiding performance; detection; diversity; linear projective transformation; quantization; quantized projection; random additive attacking distortion; spread-spectrum algorithms; statistic; Algorithm design and analysis; Data encapsulation; Maximum likelihood decoding; Proposals; Quadratic programming; Quantization; Signal analysis; Spread spectrum communication; Statistical analysis; Watermarking;
Conference_Titel :
Multimedia and Expo, 2002. ICME '02. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7304-9
DOI :
10.1109/ICME.2002.1035844