A new way to represent an image in the quantum circuit for compression and representation perspective

Quantum image processing has recently received much attention due to the opportunity to place image data in quantum mechanics systems. The literature survey has shown that the complexity of preparing image data raises the question of how and in what efficient way a medium-and high-size image is represented inside the quantum domain, which is still a big question. Quantum properties such as entanglement, superposition, and parallelism make the quantum system faster and more robust. Qubit is the central basic unit that maps the image data in the quantum processor, which propagates from left to right. The number of qubits and their connection determine the efficiency of the circuit architecture. This chapter aims to investigate the performance of the transformed coefficient-based quantum image representation and compression approaches in terms of the required number of gates and PSNR values. Moreover, the challenges and prospects of quantum image compression and processing will be discussed as a future research direction.