Application of Quantum Generative Adversarial Learning in Quantum Image Processing

Abstract

Quantum machine learning is a hot topic in the quantum community recently. The combination of quantum machine learning and image processing is also one of the researchers’ concerns. With the promotion of deep learning to process images, the field of image processing has also shown amazing potential. The combination of quantum computing and artificial intelligence can not only exert the computing power of quantum computing but also find more applications in the field of image processing. This article combines quantum generative adversarial learning with the field of image processing. A quantum generative adversarial network is designed to load and learn classical image data. Numerical simulations intuitively show that quantum algorithms can also effectively process images. In our scheme, using N qubits can load 2N classical bits of image data.