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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]

Image scaling is the basic operation that is widely used in classic image processing, including nearest-neighbor interpolation, bilinear interpolation, and bicubic interpolation. In quantum image processing (QIP), the research on image scaling is focused on nearest-neighbor interpolation, while the related research of bilinear interpolation is very rare, and that of bicubic interpolation has not been reported yet. In this study, a new method based on quantum Fourier transform (QFT) is designed for bilinear interpolation of images. Firstly, some basic functional modules are constructed, in which the new method based on QFT is adopted for the design of two core modules (i.e. addition and multiplication), and then these modules are used to design quantum circuits for the bilinear interpolation of images, including scaling-up and down. Finally, the complexity analysis of the scaling circuits based on the elementary gates is deduced. Simulation results show that the scaling image using bilinear interpolation is clearer than that using the nearest-neighbor interpolation. [ABSTRACT FROM AUTHOR]

To address quantum description for color images, an improved FRQI model called FRQCI is proposed in this paper. In our model, the qubit has two-phase parameters and , and the primary color R is stored in , the primary colors G and B are stored in . We provide several simple image processing operators, including color change and geometric transformation. Next, we focus on an encryption algorithm, which includes two parts: position scrambling and color transformation. All operations involved in this paper are implemented by the rotation of the qubit on the Bloch sphere. The simulation results on classical computer show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper we investigate the use of quantum Fourier transform (QFT) in the field of image processing. We consider QFT-based color image filtering operations and their applications in image smoothing, sharpening, and selective filtering using quantum frequency domain filters. The underlying principle used for constructing the proposed quantum filters is to use the principle of the quantum Oracle to implement the filter function. Compared with the existing methods, our method is not only suitable for color images, but also can flexibly design the notch filters. We provide the quantum circuit that implements the filtering task and present the results of several simulation experiments on color images. The major advantages of the quantum frequency filtering lies in the exploitation of the efficient implementation of the quantum Fourier transform. [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]

In this paper, a simple encryption scheme for quantum color image is proposed. Firstly, a color image is transformed into a quantum superposition state by employing NEQR (novel enhanced quantum representation), where the R,G,B values of every pixel in a 24-bit RGB true color image are represented by 24 single-qubit basic states, and each value has 8 qubits. Then, these 24 qubits are respectively transformed from a basic state into a balanced superposition state by employed the controlled rotation gates. At this time, the gray-scale values of R, G, B of every pixel are in a balanced superposition of 2 multi-qubits basic states. After measuring, the whole image is an uniform white noise, which does not provide any information. Decryption is the reverse process of encryption. The experimental results on the classical computer show that the proposed encryption scheme has better security. [ABSTRACT FROM AUTHOR]

Morphological image processing is a relatively mature image processing method in classical image processing. However, in quantum image processing, the related results are still quite scarce. In this paper, we first design the quantum circuits of the two basic operations of dilation and erosion for binary images and grayscale images. On this basis, for binary image, the quantum circuits of three morphological algorithms (noise removal, boundary extraction and skeleton extraction) are designed in detail. For grayscale image, the quantum circuits of three morphological algorithms (i.e., edge detection, image enhancement and texture segmentation) are also designed. In the design of these circuits, the parallelism of quantum computation is considered. The analysis of the circuits complexity shows that all the six morphological algorithms can speed up their classic counterparts. [ABSTRACT FROM AUTHOR]