Abstract
The just noticeable distortion (JND) model plays an important role in measuring the visual visibility for spread transform dither modulation (STDM) watermarking. However, the existing JND model characterizes the suprathreshold distortions with an equal saliency level. Visual saliency (VS) has been widely studied by psychologists and computer scientists during the last decade, where the distortions are more likely to be noticeable to any viewer. With this consideration, we proposed a novel STDM watermarking method for a monochrome image by exploiting a visual saliency-based JND model. In our proposed JND model, a simple VS model is employed as a feature to reflect the importance of a local region and compute the final JND map. Extensive experiments performed on the classic image databases demonstrate that the proposed watermarking scheme works better in terms of the robustness than other related methods.
Highlights
With the development of imaging devices, such as digital cameras, smartphones, and medical imaging equipments, our world has been witnessing a tremendous growth in the quantity, availability, and importance of images
We present a novel spread transform dither modulation (STDM) watermarking scheme based on an effective visual saliency-based just noticeable distortion (JND) model
The experiments were conducted to compare the performance of the proposed scheme and other proposed STDM improvements, termed as STDM-RW [7], STDM-AdpWM [12], STDM-RDMWm [13], and LSTDM-WM [34]
Summary
With the development of imaging devices, such as digital cameras, smartphones, and medical imaging equipments, our world has been witnessing a tremendous growth in the quantity, availability, and importance of images. An improved method was proposed [9], where the perceptual model is used to determine the projection vector and used to select the quantization step size It must use many DCT coefficients for one-bit embedding and a low embedding rate can be resulted. The simple visual saliency model used can not achieve better prediction performance, and the existing VS-based JND models cannot provide maximum performance in terms of robustness while maintaining the fidelity constraint for a practical watermarking framework. We present a novel STDM watermarking scheme based on an effective visual saliency-based JND model. The new proposed VS-based JND model is implemented in the STDM watermarking framework.
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