Attack resistant watermarking technique based on fast curvelet transform and Robust Principal Component Analysis

Abstract

Watermarking is a technique which embeds the copyright information/identifier to provide authenticity in robust and imperceptible manner. In this paper, a hybrid watermarking technique is proposed based on combination of Fast Curvelet Tansform (FCT), Robust Principal Component Analysis (RPCA) and Singular Value Decomposition (SVD). The gray-scale watermark logo is scrambled using Generalized Arnold Transform (GAT) to enhance the robustness and security. The original image is decomposed to low rank and sparse components using RPCA; the curvelet coefficients are obtained using FCT via Unequally-Spaced Fast Fourier Transforms (USFFT) to embed the processed watermark using SVD into the color image. In curvelet transform, fewer coefficients contain the most energy, also giving optimally sparse representation of the significant image features and edges that helps in efficient recovery of the embedded watermark even after severe image degradation. The robustness and imperceptibility of the proposed technique is verified against a variety of processing operations (noise, filtering) and geometric attacks (crop, resize, projection etc.). The quantitative and visual results reveal that the watermarking technique proposed is more efficient and provides high tolerance against different geometric and image processing attacks.