Spatial-Perceptual Embedding with Robust Just Noticeable Difference Model for Color Image Watermarking

Abstract

In the robust image watermarking framework, watermarks are usually embedded in the direct current (DC) coefficients in discrete cosine transform (DCT) domain, since the DC coefficients have a larger perceptual capacity than any alternating current (AC) coefficients. However, DC coefficients are also excluded from watermark embedding with the consideration of avoiding block artifacts in watermarked images. Studies on human vision suggest that perceptual characteristics can achieve better image fidelity. With this perspective, we propose a novel spatial–perceptual embedding for a color image watermarking algorithm that includes the robust just-noticeable difference (JND) guidance. The logarithmic transform function is used for quantization embedding. Meanwhile, an adaptive quantization step is modeled by incorporating the partial AC coefficients. The novelty and effectiveness of the proposed framework are supported by JND perceptual guidance for spatial pixels. Experiments validate that the proposed watermarking algorithm produces a significantly better performance.

JND‐aware robust image watermarking with tri‐directional inter‐block correlation

“…Zhu 10 integrated the Watson perception model into the STDM method, weighted the expansion vector through the JND model, and proposed a new method of calculating the quantization step size to deal with an image scaling attack. Zhou et al 11 used the spatial domain JND model to guide the frequency domain coefficients to embed the watermark and avoided the block effect of the watermarked image through adaptive quantization of the step size. Li and Yuan 12 proposed an STDM watermarking method based on robust feature extraction.…”