An optimized watermarking technique based on self-adaptive DE in DWT–SVD transform domain

• We have applied a self-adaptive differential evolution (SDE) in image watermarking, which adopt mutation factor and crossover rate dynamically.
• The major contribution is the self-adaptation of DE parameters in solving watermarking problems.
• We have investigated the performance of SDE on two test images and compared with two other algorithms.

The performance of differential evolution (DE) algorithm is significantly affected by its parameters setting that are highly problem dependent. In this paper, an optimal discrete wavelet transform–singular value decomposition (DWT–SVD) based image watermarking scheme using self-adaptive differential evolution (SDE) algorithm is presented. SDE adjusts the mutation factor F and the crossover rate Cr dynamically in order to balance an individual's exploration and exploitation capability for different evolving phases. Two-level DWT is applied to the cover image to transform it into sub-bands of different frequencies and then apply the SVD to each sub-band at level second. After applying one-level DWT to the watermark and subsequent application of SVD, the principal components of each sub-band are properly scaled down by multiplying with different scaling factors to make the watermark invisible. These scaled principal components are inserted into the singular value matrix of the corresponding blocks of the host image. The scaling factors are optimized using the self-adaptive DE algorithm to obtain the highest possible robustness with better imperceptibility. Experimental results show that the proposed scheme maintains a satisfactory image quality and watermark can still be identified after various attacks even though the watermarked image is seriously distorted.