Particle Swarm Optimization and Discrete Wavelet Transform based Robust Image Watermarking

Abstract

Objectives: Watermarking technique on digital images with improved robustness and with optimum results can be achieved by using the intelligent technique Particle Swarm Optimization (PSO). Discrete Wavelet Transform (DWT) is used to uncover perceptually significant coefficients from the digital image. Methods: PSO is one amongst the efficient techniques in optimizing a problem having many numbers of candidates. This robust technique consists of two stages namely embedding and extraction stages. Insertion of watermark into the image is done at the embedding stage. Before embedding watermark into the image perform DWT and select any one of the bands LL, LH, HL and HH. Initially select the coefficients randomly and the optimal DWT coefficients for embedding the watermark at various positions are identified by PSO. Findings: In watermark extraction stage, the embedded watermark is identified by doing the reverse process. Robustness of the digital image watermarks implies the strength of the watermark against various image processing attacks and this can be checked by evaluating Cross Correlation value that is Normalized (NCC) and for fidelity Peak Signal to Noise Ratio (PSNR). It is evident that the robustness of the image is well maintained by this technique. As a further improvement any of the other intelligent technique namely Ant Colony Optimization can be used for optimization evaluation. Applications: Digital image watermarking plays a vital role in copyright infringement issues and it helps in predicting the authorized user by the digital signature that is watermarked in the image.Keywords: Discrete Wavelet Transform, Fidelity, NCC, Particle Swarm Optimization, PSNR, Robustness, Watermarking