Translator Disclaimer
Paper
17 November 2000 KL-transform-based color image watermarking
Author Affiliations +
Abstract
The extension of gray level watermarking to the color case is one of the open issues watermarking researchers are still facing with. To get rid of the correlation among image color bands, a new approach is proposed in this paper which is based on the decorrelation property of the Karhunen-Loeve Transform (KLT). First, the KLT is applied to the RGB components of the host image, then watermarking is performed independently in the DFT domain of the KL-transformed bands. In order to preserve watermark invisibility, embedding is achieved by modifying the magnitude of mid-frequency DFT coefficients according to an additive-multiplicative rule. Different weights are used for the three KL bands to further enhance invisibility. On the decoder side, KL decorrelation is exploited to optimally detect the watermark presence. More specifically, by relying on Bayes statistical decision theory, the probability of missing the watermark is minimized subject to a fixed false detection rate. Basing on the Neymann-Pearson criterion, the watermark presence is revealed by comparing a likelihood function against a threshold, if the former is above the latter the decoder decides for the watermark presence, otherwise such an hypothesis is rejected. Experimental results are shown proving the robustness of the algorithm against the most common image manipulations, and its superior performance with respect to conventional techniques based on luminance watermarking.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luca Boccardi, Mauro Barni, Franco Bartolini, Alessia De Rosa, and Alessandro Piva "KL-transform-based color image watermarking", Proc. SPIE 4122, Mathematics and Applications of Data/Image Coding, Compression, and Encryption III, (17 November 2000); https://doi.org/10.1117/12.409251
PROCEEDINGS
11 PAGES


SHARE
Advertisement
Advertisement
Back to Top