A robust Plenoptic image watermarking method using graph-based transform

Abstract

Numerous methods have been introduced for digital images watermarking. But there are fewer studies on plenoptic images. This image has more information (such as depth) and costs more than regular digital images. So, protecting the ownership of plenoptic is important. In this paper a robust plenoptic image watermarking has been introduced which is based on Graph-based Transform (GBT). Also, in order to maximizing the robustness of watermarking an optimization has been used to find the best graph structure of GBT. This optimization has done using a Genetic Algorithm. One of the common ways to robust the watermarking is the use of discrete cosine transform (DCT). In this study, we have shown that the proposed method is much more powerful than DCT. The proposed method is tested on three plenoptic images namely Alley, Basic Shapes and Coffee Table and the results show that the proposed method is more robust to similar methods such as DCT methods. Watermarking was evaluated using BER, SSIM and PSNR criteria and Gaussian noise attacks with varying intensities.