Image Watermarking Using Hybrid Wavelets and Directional Filter Banks

This paper aims at developing a robust directional invisible watermark which focuses on copy control and near perceptual watermark images. Wavelets are small signals which are dealt simultaneously in time and frequency spaces, the directional filter banks used to study the directional nature of an image across its edges and curves causing more significant to human vision. The wavelet decomposition of an image along with application of modified directional filter banks to the higher resolution scales provides the significant coefficients which are more robust and invisible to many and capable of handling is watermark data. Generalized white Gaussian noise is used as the watermark and proved to be effective when compared with a more generalized wavelet transform watermark implementation. In this paper the quincunx non-separable sampling and filtering is used in directional filter banks along the horizontal and vertical wavelet frames. The correlation of the proposed method and the wavelet transform watermark are compared with a higher resemblance to the concerned method. The PSNR is also used to show the large watermark handling capability of the hybrid wavelet and directional filter banks application for watermarking of images.