Modeling the human visual system has become an important issue in image processing such as compression, evaluation of image quality and digital watermarking. In this paper we present a spatial JND (Just Noticeable-Difference-) model that uses a texture selector based on Faber-Schauder wavelets lifting scheme. This texture selector identify non-uniform and uniform areas. That allows to choose between JNDs models developed by Chou and Qi. The chosen JND will determine the value of the embedding strength in each pixel, related to the identified region. Results show that by this process, we can generally ameliorate the visual quality with the same robustness.
CITATION STYLE
Amar, M., Harba, R., Douzi, H., Ros, F., El Hajji, M., Riad, R., & Gourrame, K. (2016). A JND model using a texture-edge selector based on faber-schauder wavelet lifting scheme. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9680, pp. 328–336). Springer Verlag. https://doi.org/10.1007/978-3-319-33618-3_33
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