A Quantum Image Watermarking Scheme Based on Two-Bit Superposition

Quantum watermarking technology protects copyright by embedding an invisible quantum signal in quantum multimedia data. This paper proposes a two-bit superposition method which embeds a watermark image (or secret information) into a carrier image. Firstly, the bit-plane is used to encrypt the watermark image. At the same time, the quantum expansion method is used to extend the watermark image to the same size with the carrier image, and then the image is encrypted through the Fibonacci scramble method again. Secondly, the first proposed method is the two bits of the watermark image which is embedded into the carrier image in accordance with the order of the high and lowest qubit, and the second proposed method which is the high bit of the watermark image is embedded to the lowest bit. Then the lowest bit of the watermark image is embedded in carrier image. Third, the watermark image is extracted through 1-CNOT and swap gates, and the watermark image is restored by inverse Fibonacci scramble, inverse expansion method and inverse bit-plane scramble method. Finally, for the validation of the proposed scheme, the signal-to-noise ratio (PSNR), the image histogram and the robustness of the two watermarking methods are analyzed.

     

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.