Optimal blind colour image watermarking based on adaptive chaotic grasshopper optimization algorithm

Abstract

ABSTRACT This paper proposes an effective optimal blind colour image watermarking based on Triangular Vertex Transform (TVT), Lifting Wavelet Transform (LWT) and Schur decomposition. Firstly, the RGB channels of the colour host image are processed with TVT to attain , and coefficients. The image quality is preserved by applying LWT on the coefficients. As the middle frequency (HL and LH) components of the LWT wavelet domain achieve much robustness, these two components are split into nonoverlapping blocks further it is processed with Schur decomposition for improving perceptual transparency. The optimal solution attained by an Adaptive Chaotic Grasshopper Optimization Algorithm (ACGOA) is used as the embedding factor to ensure the embedding strength of the watermark. The confidentiality of the watermark is improved by 2D Logistic-Modulated-Sine-Coupling-Logistic Chaotic Map (LSMCL). Subsequently, each bit of encrypted watermark image is inserted in the highest eigenvalue of upper triangular matrix of Schur decomposition using the embedding factor β obtained by ACGOA to accomplish the watermarked image. The watermark recovery is performed using the embedding factor β and the decryption process is done using LSMCL. The efficiency of the ACGOA based scheme is estimated and the highest Peak signal-to-noise ratio (PSNR) value achieved is 54.2987 dB. The Normalized Cross-Correlation (NCC) results show better reliability for different attacks including geometric attacks and the NCC value obtained is close to 1.