A systematic comparative analysis of Quantum mechanics-based image processing and denoising algorithms

Quantum image processing is a significant branch of Quantum computing and is widely used in various industrial and research-based applications. Quantum image processing algorithms can be developed by utilizing different features of Quantum mechanics principles and image processing. This paper aims to provide a detailed review that addresses related Quantum image processing and Quantum Boolean image denoising techniques for real-time-based applications. The recent advancement in Quantum computing has led to multidisciplinary research in Quantum image processing that can process large amounts of image data at once. The characteristics of Quantum principles like parallelism, Entanglement, Fourier transformation, Filter superposition, and noise reduction provide various advantages for image processing over conventional ones. The performance measures of all Quantum-based image processing techniques are also compared and highlighted briefly to motivate innovative Quantum processing researchers. This paper also discusses the errors that occur due to sensitive characteristics of the Quantum system. The various algorithms of Quantum image denoising are discussed in the research discussion by implementing all on IBM Qiskit libraries.