An SVD-based image watermarking in wavelet domain using SVR and PSO

作者：Tsai Hung Hsu; Jhuang Yu Jie; Lai Yen Shou^*

来源：Applied Soft Computing, 2012, 12(8): 2442-2453.

DOI：10.1016/j.asoc.2012.02.021

• Blind watermarking
• Particle swarm optimization
• Singular value decomposition
• Support vector regression

The paper presents a novel blind watermarking scheme for image copyright protection, which is developed in the discrete wavelet transform (DWT) and is based on the singular value decomposition (SVD) and the support vector regression (SVR). Its embedding algorithm hides a watermark bit in the low-low (LL) subband of a target non-overlap block of the host image by modifying a coefficient of U component on SVD version of the block. A blind watermark-extraction is designed using a trained SVR to estimate original coefficients. Subsequently, the watermark bit can be computed using the watermarked coefficient and its corresponding estimate coefficient. Additionally, the particle swarm optimization (PSO) is further utilized to optimize the proposed scheme. Experimental results show the proposed scheme possesses significant improvements in both transparency and robustness, and is superior to existing methods under consideration here.

• 出版日期2012-8