An Adaptive Content Based Localized Watermarking Algorithm for Remote Sensing Image

In this paper, we proposed a new adaptive content-based localized watermarking algorithm for remote sensing images based on DWT, which adaptively embeds corresponding watermarks into the local regions of the remote sensing image instead of the entire one. In order to improve watermarking capability against attacks in the frequency area, we selected some stable feature points in the remote sensing image, then used them to identify the locations where we inserted the local watermarks, namely we embedded the watermarks into the local sub-images centered by those feature points. When the remote sensing image is cropped , we can also detect and orient watermarks by the feature points in the remaining one. Moreover the algorithm took the new watermarking-embedding strategy based on DWT domain to embed the local watermarks, namely watermarks should be embedded into the low frequency space firstly, and the remains are embedded into the high frequency spaces according to their significance. And different embedding strength for watermarks should be applied to the low frequency space and the high ones respectively. In order to further improve robustness of watermarks, the embedded local watermark is designed to be orthogonal to the feature vector of the low frequency space (LL3) in DWT area of the corresponding sub-image, which means that watermarking casting is remote sensing image content dependent. In addition, the algorithm exploited the Neymann-Pearson criterion to detect watermarks. Experimental results show that the watermarking algorithm is robust to all kinds of attacks, especially cropping.