Evaluating the Influence of Quantum Noise on Different Perspectives of Quantum Image State Preparation Protocols

Quantum Image Processing is based on principles of quantum computing to represent visual information effectively, preparation of a quantum state plays a crucial rule in circuit performance. In Noisy Intermediate-Scale Quantum (NISQ) era, quantum noise and decoherence predominantly affect the fidelity of image-encoded quantum states. This paper deals with a comparative analysis of Four quantum image encoding schemes namely, Flexible Representation of Quantum Images (FRQI), Quantum Probability Image Encoding (QPIE), Order-Encoded Quantum Image Model (OQIM), and Enhanced Flexible Representation of Quantum Images (EFRQI). Noise free and Noisy state preparation simulations are executed using gate-based quantum simulators in the Pennylane environment, incorporating Bit Flip (BF), Phase Flip (PF), Amplitude Damping (AD), Phase Damping (PD), and Depolarizing noise (DN) channels. Image related performance metrics such as, Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR) in dB, Structural Similarity Index Measure (SSIM), and Intersection over Union (IoU) are used to measure the performance of image encoded quantum states. Our results reveal that distinct noise robustness characteristics’ across various encoding methods reveals the importance of Noise aware encoding selection for NISQ era quantum image processing applications.