Title :
Curvelet based adaptive watermarking for images
Author :
Haohao Song ; Jian Gu
Author_Institution :
MPS Quality Supervision & Testing Center of Security Products for Comput. Inf. Syst., Shanghai, China
Abstract :
In this paper, we propose a curvelet based adaptive watermarking for images (CvAWI). A image is firstly transformed into curvelet domain; the watermark is embedded into the curvelet coefficients of the middle-frequency subbands of image lastly. On the one hand, the embedded watermark is well invisible because contrast sensitivity function and watermark visual mask are adopted in our CvAWI. On the other hand, the embedded watermark is very robust due to the spread specialty of curvelet transform (CvT). The corresponding watermarking detection algorithm is proposed to decide whether the watermark is present or not by exploiting the unique transform structure of curvelet. Experimental results show the validity of CvAWI in terms of both watermarking invisibility and watermarking robustness.
Keywords :
curvelet transforms; image watermarking; CvAWI; CvT; contrast sensitivity function; curvelet based adaptive watermarking; curvelet coefficients; curvelet domain; curvelet transform; embedded watermark; middle-frequency subbands; spread specialty; transform structure; watermark visual mask; watermarking detection algorithm; watermarking invisibility; watermarking robustness; contrast sensitivity function; curvelet; image watermarking; watermark visual mask;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526117