Date of Award

2024

Document Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

Committee Chair

David Pan

Committee Member

Laurie Joiner

Committee Member

Sivaguru S. Ravindran

Research Advisor

David Pan

Subject(s)

Quantum optics, Quantum computing, Image processing

Abstract

Quantum image processing (QIMP) uses quantum information processing to create and work with quantum images. Due to the inherent properties of quantum computation, QIMP technologies have the potential to surpass their classical computing equivalents in terms of computing speed and storage requirements. In this thesis, we investigated quantum image edge detection, which is a fundamental tool used in image processing for feature detection and extraction. Quantum edge detection can exploit quantum mechanics' superposition and entanglement properties to perform operations simultaneously on all pixels and accelerate the process. To this end, we adopted the bitplane based framework of Quantum Boolean Image Processing that utilizes the computational basis states, with the advantage of having low computational cost and low impact on quantum measurements. We conducted a comprehensive and in-depth study of the Quantum Boolean Edge Extraction method. More specifically, we decomposed an image into bitplanes and then converted the most significant bitplane from the classical state to the quantum state. Subsequently, we applied the quantum algorithm to extract edges. We assessed the effectiveness of edge extraction by using different bitplanes. Besides, we compared the results of edge extraction using classical implementations with quantum implementations. We also conducted a detailed analysis of the quantum implementation complexity in terms of the number of quantum logic gates. Finally, we presented the results of running the quantum edge extraction algorithm on both ideal and noisy simulator backends of various quantum computing platforms, including the IBM Qiskit, Google Cirq, as well as AQT (Alpine Quantum Technologies) backend. These simulation results demonstrated the robustness of the quantum edge extraction algorithm.

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