Blind Image Watermark Analysis using DWT and Non-Negative Matrix Factorization

This paper proposed a blind digital image watermark analysis algorithm, which is to analyze watermarks in host images without any prior-watermarking embedding and detection information. In the proposed algorithm, DWT is firstly used to decompose images into detail subbands, and noise visibility function is used to enhance the detail subbands, then non-negative matrix factorization (NMF) is used to reveal the intrinsic features in host images. Support vector machines (SVMs) are finally used to classify these characteristics. Numerical experimental results show that the proposed scheme describes the intrinsic statistical characteristics and the proposed watermark analysis is effective.