Implementations of HVS Models in Digital Image Watermarking

In the paper two possible implementations of Human Visual System (HVS) models in digital watermarking of still images are presented. The first method performs watermark embedding in transform domain of Discrete Cosine Transform (DCT) and the second method is based on Discrete Wavelet Transform (DWT). Both methods use HVS models to select perceptually significant transform coefficients and at the same time to determine the bounds of modification of selected coefficients in watermark embedding process. The HVS models in DCT and DWT domains consist of three parts which exploit various properties of human eye. The first part is the HVS model in DCT (DWT) domain based on three basic properties of human vision: frequency sensitivity, luminance sensitivity and masking effects. The second part is the HVS model based on Region of Interest (ROI). It is composed of contrast thresholds as a function of spatial frequency and eye’s eccentricity. The third part is the HVS model based on noise visibility in an image and is described by so called Noise Visibility Function (NVF). Watermark detection is performed without use of original image and watermarks have a form of real number sequences with normal distribution zero mean and unit variance. The robustness of presented perceptual watermarking methods against various types of attacks is also briefly discussed.