A Comparative Study on Chaotic Map Approaches for Transform Domain Watermarking Algorithm

Watermarking is identified as a major technology to achieve copyright protection and multimedia security. In this study, combination of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) via Lower-and-Upper (LU) Decomposition is used as a transform domain watermarking algorithm with a comparative study on chaotic map approaches as Logistic Map (LM), Asymmetric Tent Map (ATM), and Arnold's Cat Map (ACM). As quality metrics, Similarity Ratio (SR) values for ACM are greater by approximately 20% than that of LM and ATM despite nearly same Peak Signal-to-Noise Ratios (PSNRs) after attacks. This study expands the application areas of watermarking with the algorithm consisting DWT, SVD, and LU with chaotic maps together.