ABSTRACT
In this paper we present a blind low frequency watermarking scheme on gray level images, which is based on DCT transform and spread spectrum communications technique. We compute the DCT of non overlapping 8×8 blocks of the host image, and then using the DC coefficients of each block we construct a low-resolution approximation image. We apply block based DCT on this approximation image, then a pseudo random noise sequence is added into its high frequencies.
For detection, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method, higher robustness is obtained because of embedding the watermark in low frequency. In addition, higher imperceptibility is gained by scattering the watermark’s bit in different blocks.
We evaluated the robustness of the proposed technique against many common attacks such as JPEG compression, additive Gaussian noise and median filter. Compared with related works, our method proved to be highly resistant in cases of compression and additive noise, while preserving high PSNR for the watermarked images.
In recent years, many digital watermarking techniques have been proposed to protectthe copyright of digital multimedia data. Watermark embedding is performed in many domains such as spatial, Fourier transform, DCT and DWT. One of the commonly used domains for embedding a watermark in an image is the DCT. DCT splits up the image into the frequency bands, so upon the application, the watermark can be embedded in different frequencies. Furthermore, the sensitivity of human visual system to DCT frequencies has been extensively studied; which resulted in the recommended JPEG quantization table.
These results can be used for predicting and minimizing the visual impact of distortion caused by embedding the watermark. If we know the image compression domain, for example DCT, then it is better to embed watermark in those DCT are
1. Discrete Cosine Transform
2. Discrete Wavelet Transform
Coefficients which are unlikely to be discarded during the compression process. Since we are able to anticipate which DCT coefficients will be quantized by the compression scheme, we can choose not to embed the watermark in those coefficients.