Quantum image encoding and processing

This project explores the potential of quantum computing for image encoding and processing, with a focus on efficient representations of grayscale, RGB, and thermal images using quantum image representations (QIRs). Quantum-enhanced imaging holds great promise for areas like low-light vision and biomedical analysis, where classical methods often struggle with resolution and noise.

I implemented and evaluated several QIR models by designing quantum circuits to map classical image data into quantum states. I systematically studied encoding efficiency, retrieval accuracy, and circuit depth, aiming to understand the trade-offs between fidelity and resource consumption in quantum systems.

In addition, I investigated the encoding of infrared and thermal images, motivated by applications in medical imaging and night-vision technologies. These tasks required adapting quantum representations to accommodate non-visible spectrum data, opening up possibilities for more sensitive and compact image processing solutions on near-term quantum hardware.