Optimal Gaussian weight predictor and sorting using genetic algorithm for reversible watermarking based on PEE and HS - Panyindee, Chaiyaporn; Pintavirooj, Chuchart (My University, 2016)
This paper introduces a reversible watermarking algorithm that exploits an adaptable predictor and sorting parameter customized for each image and each payload. Our proposed method relies on a well-known prediction-error expansion (PEE) technique. Using small PE values and a harmonious PE sorting parameter greatly decreases image distortion. In order to exploit adaptable tools, Gaussian weight predictor and expanded variance mean (EVM) are used as parameters in this work. A genetic algorithm is also introduced to optimize all parameters and produce the best results possible. Our results show an improvement in image quality when compared with previous conventional works.
Keywords: Expanded variance mean (EVM); Gaussian weight predictor; Histogram shifting (HS); Prediction-error expansion (PEE); Reversible watermarking