Screen-Cam Robust and Blind Watermarking for Tile Satellite Images

Abstract

To achieve watermark synchronization from an image with perspective distortion is a challenge. This paper proposes a screen-cam robust and blind watermarking scheme for tile satellite images, which means we do not need any user interaction or additional information in watermark detection. To achieve this, at the watermark embedding side, we divide tiles into synchronization tiles and message tiles, and propose a discrete Fourier transform (DFT) based embedding method to cope with the quality degradation caused by screen-cam process. At the extraction side, based on the idea of template matching, we first use a synchronization response index to estimate an appropriate scale level and positions of embedded synchronization watermarks from the noise component, which is estimated by Wiener filter. Then, we propose verification, selection, and precise locations methods to ensure the effectiveness and accuracy of synchronization detection results. After that, we can extract the regions of message tiles. Finally, we extract watermark message based on the local max value from the DFT domain of the noise component. Experimental results demonstrate the validity of the proposed scheme against common attacks and screen-cam attack with a tripod as well as handhold shooting. INDEX TERMS Screen-cam process, robust watermark, tile satellite images, blind detection, synchronization.

Joint Image Encryption and Screen-Cam Robust Two Watermarking Scheme

“…Therefore, we do not need additional transmission of the secret key as separate data. With respect to the embedding region, considering the advantages of DFT domain in the screen-cam process [44], we employ DFT-based methods to embed both watermark messages in blocks repeatedly. With regard to the encryption algorithm, it is not only to achieve encryption but also to work with the watermark B.…”

“…The watermark is embedded in the magnitude spectrum. Because the low and medium-frequency magnitude coefficients with high values can be well preserved in screen-cam process and the low values are not [44], the embedding method is defined as:…”

“…. , n}, which contains all candidate point sets that can be used for perspective correction, based on the searching method in [44]. The s(i) are sorted according to the sum of the distances between the points from largest to smallest.…”

“…Although the ideas of these methods are valuable for studying screen-cam robust watermarking algorithms, these methods are not applicable for the screen-cam process [43]. The screen-cam process has its particularity, which causes various types of distortions [43][44][45], including linear distortion, gamma tweaking, geometric distortion, moiré noise and low-pass filter attack. To cope with these severe distortions, Fang et al [43] proposed a feature-based watermarking scheme where the message is embedded in the discrete cosine transform (DCT) domain of local feature regions.…”

“…To further improve the robustness, Fang et al [46] proposed a deep learning-based watermarking scheme. To achieve blind detection under geometric distortion, Chen et al [44] designed a watermark synchronization method and embedded the message in the discrete Fourier transform (DFT) domain. These methods are effective for screen-cam attack.…”