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In this paper, a neural networks model for quantum computer is proposed. The core of this model is quantum neuron. Firstly, the inner product of the input qubits and the weight qubits is mapped to the phase of the control qubits in the neuron by the swap test technology, and then these phases are obtained by the phase estimation method, which are further used as the phase of the output qubit in the neuron. In this way, the mapping of input qubits to output qubit in quantum neuron is completed. The quantum neurons mentioned above can be used to construct quantum neural networks. In this paper, the quantum circuit for each operation step are given. The simulation results on the classic computer verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In this paper, a design method of quantum circuits for threshold segmentation of gray-scale image is proposed, which is a quantum counterpart of classical optimum global thresholding using Otsu's method. First, we design a quantum circuit to obtain the histogram of the pixels distribution. Then, on this basis, we design the quantum circuits of some sub-modules, such as the cumulative histogram, cumulative mean, multiplication, division, the between-class variance and so on. Finally, all the between-class variances corresponding to each gray-level are sorted. At this time, the gray-level corresponding to the maximum of the between-class variance is the Otsu's threshold. For all the operations involved in the classical Otsu's threshold selection, we designed the corresponding quantum circuits, analyzed the computational complexity, and verified the correctness of these circuits by simulations on classical computers. [ABSTRACT FROM AUTHOR]

In quantum image steganography, embedding capacity and security are two important issues. This paper presents a novel quantum steganography scheme using color images as cover images. First, the secret information is divided into 3-bit segments, and then each 3-bit segment is embedded into the LSB of one color pixel in the cover image according to its own value and using Gray code mapping rules. Extraction is the inverse of embedding. We designed the quantum circuits that implement the embedding and extracting process. The simulation results on a classical computer show that the proposed scheme outperforms several other existing schemes in terms of embedding capacity and security. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the quantum image spatial filtering, and focused on the design method of quantum weighted averaging filter and its application in image de-noising. To this end, we first designed the quantum circuits for some auxiliary modules, such as swapping two numbers, comparing two numbers, computing the weighted average of some integers, etc. Next, we constructed a weighted averaging filter of size 3 × 3 using auxiliary modules. The spatial filtering directly on the image itself can be accomplished by using designed filter. We provided the quantum circuits that implements the filtering task and presented the results of several simulation experiments on some gray images with different noises. The significance of this paper is to explore the quantum realization method of image filtering in spatial domain. [ABSTRACT FROM AUTHOR]