Contents Introduction
The evolution of quantum communication technology, coupled with Shor's quantum factorization algorithm [1] capable of breaking RSA encryption, is anticipated to revolutionize contemporary encryption systems. In recent years, the development of image encryption technology has gradually become an issue. With the advancement of network communication technology, digital images can be easily transmitted over the network from anywhere and at any time. Therefore, image privacy protection has gradually become a focus of public attention. Among them, quantum image encryption (QIE), a subset of quantum cryptography and quantum information processing (QIP), serves to safeguard the information security of images. However, the research data in this field is still in the development stage, and image data can contain more information than a string of numbers in terms of data transmission [2]–[3]. The security of image data has emerged as a paramount concern as well. Numerous methods for quantum image processing have been proposed over the years. One such method is the Flexible Representation of Quantum Images (FRQI), which was introduced in 2011 by [4]. FRQI is a versatile technique that can be used for tasks such as multinomial preparation, image compression, and processing. In various simulation experiments, FRQI proves effective in both storing and retrieving images, along with detecting lines in binary images through the application of quantum Fourier transform as a processing operation. In 2013, a new method called Enhanced Quantum Representation (NEQR) was proposed [5], which enhances the Flexible Representation of Quantum Images (FRQI). In NEQR, the ground state of the quantum bit sequence is employed to store the gray value of each pixel in the image, contrasting with FRQI, which utilizes the probabilistic amplitude of quantum bits for the same purpose. Quantum image processing has advanced with the development of quantum image modeling research, leading to the proposal of many algorithms such as quantum image filtering and encryption. In 2021, Jinlei Zhang proposed a method to encrypt image data by disassembling it into multiple parts [6]. Some researchers have proposed the mapping of RGB image data onto quantum circuits as a method for encryption. However, this approach requires the preparation of 24 quantum bits, which can be relatively resource-intensive [7]. In 2023, we also proposed a new image encryption method using reversible quantum gate operations [8]. However, these quantum image encryption processing methods mainly focus on encrypting the image after it has been captured. The FPGA's programmable architecture provides a significant advantage over MCU, which requires more time to process in terms of hardware resources. Designers can quickly and repeatedly reprogram FPGA to perform different functions. It also has the advantages of low latency, low power consumption, and strong parallel processing capability [9]. Therefore, in our study, we propose the implementation of a real-time quantum image encryption system on FPGA, leveraging reversible quantum gate computation. A CMOS module is used for real-time image acquisition. Then, real-time quantum image encryption is performed by FPGA. Finally, the processed image is stored on the SD card. At the same time, the image is decrypted on a computer to obtain the original captured image due to the reversible nature of quantum computation.
