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IEEE Access

Quantum Geometric Transformation Based on QIRHSI Quantum Color images

Xianhua Song, Guanglong Chen, Ahmed A. Abd El‐Latif, Mudasir Ahmad Wani, Bassem Abd-El-Atty

Published Jan 1, 2023• 8 citations
Publisher

Abstract

The negative effects caused by geometric distortion can be removed to the maximum extent possible through appropriate geometric transformations, allowing us to focus on the image content itself in subsequent processing and recognition. Therefore, geometric transformations are often used as a pre-processing step for other image processing applications. In this paper, quantum algorithms are designed to implement geometric transformations, including two-point swapping, circular translation, flipping transformations and right-angle rotation, across a quantum image representation QIRHSI (Quantum Image Representation based on HSI color space) which is built on HSI (Hue-Saturation-Intensity) color space. The above geometric transformations are realized by quantum circuits composed of elementary quantum gates. By analyzing the complexity of the fundamental quantum gates needed for the above geometric transformations, it is found that the global transformations (circular translation, flip transformation and right-angle rotation) are lower than the local transformation (two-point swapping). The proposed geometric transforms are used to facilitate the applications of quantum images with low complexity and high efficiency.

DOI
10.1109/access.2023.3247507

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The negative effects caused by geometric distortion can be removed to the maximum extent possible through appropriate geometric transformations, allowing us to focus on the image content itself in subsequent processing and recognition. Therefore, geometric transformations are often used as a pre-processing step for other image processing applications. In this paper, quantum algorithms are designed to implement geometric transformations, including two-point swapping, circular translation, flipping transformations and right-angle rotation, across a quantum image representation QIRHSI (Quantum Image Representation based on HSI color space) which is built on HSI (Hue-Saturation-Intensity) color space. The above geometric transformations are realized by quantum circuits composed of elementary quantum gates. By analyzing the complexity of the fundamental quantum gates needed for the above geometric transformations, it is found that the global transformations (circular translation, flip transformation and right-angle rotation) are lower than the local transformation (two-point swapping). The proposed geometric transforms are used to facilitate the applications of quantum images with low complexity and high efficiency.
Circuits to achieve geometric trans- formations including two-point swapping, flip, co- ordinate swapping, orthogonal rotations and their variants on N -sized quantum images are proposed based on the basic quantum gates; NOT, CNOT and Toffoli gates. The complexity of the circuits is O(log 2 N) for two-point swapping and O(logN) for flip, co-ordinate swapping and orthogonal rotations. The results indicate that local operations like two- point swapping are slower than global operations like flip, co-ordinate swapping, and orthogonal rotations in quantum image processing. This is in contrast to performing such operations in classical image process- ing where the local operations are faster. All the proposed transformations are confirmed by simula- tion on a classical computer. With their low com- plexity, these geometric transformations can be used as the major components to build circuits for other applications on quantum images.
This chapter first presents the general framework structure of quantum image representation, and then introduces some research results on quantum color image representation in our group. In this study, quantum color image representation based on the HSI color space (QIRHSI) is a quantum color image representation based on the hue, saturation, and intensity (HSI) color space in the right-angle coordinate system, novel color quantum image (NCQI) and Color Quantum Image based on Phase Transform (CQIPT) are quantum color image representations based on the RGB color space in the right-angle coordinate system, and MLCPQI is a quantum color image representation based on the RGB color space in the polar coordinate system. In addition, the preparation scheme on a quantum computer and the computational complexity of the prepared image are provided for each quantum color image representation method. Ultimately, a general framework and preparation strategy for quantum video representation are proposed based on quantum image representation.
Arithmetic operations on images are important primary transformations that can be applied to many complicated image operations. We mainly study the intensity-based arithmetic operations on the QIRHSI quantum image representation model to facilitate the development of quantum image processing. The quantum circuits and unitary matrices for four arithmetic operations including reverse, complement, addition, and subtraction are proposed. Finally, the complexity analysis of quantum networks is illustrated to show the effectiveness of the proposed arithmetic operations.
A quantum color image encryption algorithm based on geometric transformation and intensity channel diffusion was designed. Firstly, a plaintext image was transformed into a quantum state form using the quantum image representation based on HSI color space (QIRHSI) representation as a carrier. Next, a pseudo-random sequence was generated using the generalized logistic map, and the pixel positions permuted multiple two-point swap operations. Immediately afterward, the intensity values were changed by an intensity bit-plane cross-swap and XOR, XNOR operations. Finally, the intensity channel of the above image was diffused in combination with the pseudo-confusion sequence as produced by the quantum logistic map to perform a diffusion operation on the intensity bit-plane to obtain the ciphertext image. Numerical simulations and analyses show that the designed algorithm is implementable and robust, especially in terms of outstanding performance and less computational complexity than classical algorithms in terms of security perspective.
To achieve a certain desired visual effect, the pixel positions of the input image are mapped to positions different from the original ones so as to change the display effect of the original image. This process is called the geometric transformation of the image. Geometric transformations mainly include geometric correction of the image and spatial transformations (scaling transformation, rotation, and affine transformation) [ 1 – 26 ] . This chapter proposes the geometric transformations of the QIRHSI quantum color image, including basic geometric transformations and scaling operations, and further studies the unitary operators of geometric transformations and the corresponding quantum circuits.