A robust multiwavelet-based watermarking scheme for copyright protection of digital images using human visual system

الملخص EN

The contemporary period of information technology facilitates simple duplication, manipulation and distribution of digital data.

This enduringly, has insisted the rightful ownership of digital images to be protected efficiently.

For content owners and distributors, there emerged a necessary concern in regard to the content authentication of digital images as well as copyright protection.

A latent solution to this issue is bestowed by Digital watermarking.

To certify efficient copyright protection, the watermarking scheme should own the characteristics, such as robustness and imperceptibility.

Integration of Human Visual System (HVS) models with in the watermarking scheme helps to attain an effective copyright protection.

Currently, wavelet domain based watermarking scheme mainly interested in watermarking researches.

An undetectable and proficient wavelet-based watermarking scheme to safe guard the copyrights of images are portrayed here on contrary to the prior works.

By effecting few modifications to our prior works, we have presented a new proficient watermarking scheme by incorporating the HVS models for watermark embedding.

Additionally, we have applied the GHM multiwavelet transform in the watermarking process.

Based on the computed distance using Hausdorff distance measure, the image components for embedding are selected and a new procedure is designed for watermark embedding by multiplying the embedding strength with the random matrix that is generated by key image as a primary element and is engaged in both embedding and extraction processes.

The correlation coefficient computation is used for extraction of watermark process.

The experimental results illustrate the robustness and imperceptibility of the proposed approach.

From the results, we can identify that the proposed watermarking process has achieved the correlation value of 0.9848 even if the watermarked image is affected by the Gaussian noise.