Anomaly Detection Algorithm Based on Nonsubsampled Pyramid Decomposition and Kernel Unsharp Masking for Hyperspectral Image

In this paper, a novel image zero-watermarking scheme against rotation attacks is proposed based on nonsubsampled pyramid decomposition (NSPD) and discrete cosine transform (DCT). It utilizes the intrinsic characteristics of NSPD and DCT to extract the robust feature of an image as the original zero-watermark. To increase the security of the proposed scheme, a variable parameter chaotic mapping (VPCM) is designed for the processes of watermark encryption and robust feature extraction. Firstly, the host gray-scale image is decomposed by NSPD, and the low-frequency sub-band image is divided into nonoverlapping blocks. After the blocks are transformed by DCT, the signs of the first AC coefficients from all the blocks are used to construct a binary feature image. Then an exclusive-or operation is performed between the binary feature image and the encrypted watermark image to obtain the verification zero-watermark image. Furthermore, a method against arbitrary rotation attacks is employed to improve the robustness of the scheme against geometric attacks. The experimental results demonstrate that the proposed scheme is highly robust against various image processing attacks such as filtering, JPEG compression, scaling, translation, rotation and Checkmark attacks. INDEX TERMS Discrete cosine transform, Nonsubsampled pyramid decomposition, Rotation attacks, Variable parameter chaotic mapping, Zero-watermarking.

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A Novel Zero-Watermarking Scheme Based on Variable Parameter Chaotic Mapping in NSPD-DCT Domain

Wang

Han

Zhang

et al. 2020

IEEE Access

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Anomaly Detection Algorithm Based on Nonsubsampled Pyramid Decomposition and Kernel Unsharp Masking for Hyperspectral Image

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A Novel Zero-Watermarking Scheme Based on Variable Parameter Chaotic Mapping in NSPD-DCT Domain

A Novel Zero-Watermarking Scheme Based on Variable Parameter Chaotic Mapping in NSPD-DCT Domain

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