Created by W.Langdon from gp-bibliography.bib Revision:1.7185
It has multi-resolution hierarchical characteristics, and lower resolution embedding and detection which are computationally inexpensive.
The presentation of the image because of the hierarchical multi-resolution properties of the transformation is well-suited for applications where the multimedia data is transmitted regularly, as such in the application of video systems, or applications in real time.
Wavelet transform is closer to HVS contrast to DCT. For this reason, the range of artifacts introduced by wavelet is less infuriating as compared to DCT.
For better imperceptibility, the watermarking technique should support a vision model which integrates various masking effects of the Human Visual System (HVS), to embed watermark in an invisible manner. For HVS we have used Watson's Perceptual Model of JPEG2000. The basic aim of perceptual coding is, to conceal the watermark below the detection threshold.This can be obtained by making use of the HVS and JND threshold.The watermarking technique based on this model resists all types of common signal processing operations and many geometric attacks but unfortunately was not resistant against rotation.
Keeping in mind this we explored Morton scanning. Morton scanning is used to frequency wise arrange the coefficients to resist geometric attacks. We have used Genetic Programming (GP) in order to make an optimum trade off between imperceptibility and robustness by choosing an optimum watermarking level for each coefficient of the cover image. In addition to the suitable watermarking strength, the selection of best block size is also necessary for superior perceptual shaping functions.To achieve this goal we have trained and used GP to pick the best block size to tailor the watermark in a manner such that it can survive all kinds of intentional and unintentional attacks.Extensive experiments have been carried out, to demonstrate the strong robustness and imperceptibility of the proposed technique over the existing approaches.",
Genetic Programming entries for Zahoor Jan