Blind image watermarking via derivation and quantization of robust semi-global statistics

We introduce a new approach for blind image watermarking: We derive robust semi-global features in wavelet domain and quantize them in order to embed the watermark. Quantization of statistics is carried out by adding scaled pseudo-random sequences that are visually unnoticeable. Our algorithm exhibits increased robustness against various attacks and it withstands standard benchmark attacks of wider trange than earlier methods (e.g., Stirmark, random bending etc.) and modifications such as compression, provided they do not cause too severe visual distortions.