The Application Of Compressive Sensing In Digital Watermarking

Compressive sensing theory is a popular research direction in the field of signal processing in recent years. The collection and compression of the data can be achieved at the same time, through a simple coding. It has broken the traditional law of Nyquist sampling and original signal accurate reconstruction through the optimization algorithm. Compressive sensing theory has been successfully applied to medical images, digital forensics, image de-noising, secure communications and other fields. In this paper, the compressed sensing theory applied to digital watermarking technology, main research content of the following:(1) Because most of the compressed sensing theory is used in one dimensional signal, this article analyzes the several classic compressed greed reconstruction algorithm for2d image experiment results. The experimental results indicate that the ROMP algorithm for image reconstruction effect is better with the higher sparse degree and higher sampling rate. And the OMP algorithm is more stable in the process of sample rate changing. The SAMP algorithm doesn’t need a sparse degree. It has the reconfiguration also.(2) A color image digital watermarking algorithm based on compressed sensing. This paper proposes a color image digital watermarking algorithm based on compressed sensing theory. The watermarking uses compressed sensing to preprocessing, which meets the watermark scrambling effect, and reduces the watermark information. The experiment shows that the algorithm has good invisibility and robust.