2020/10/01 by Khaled A. Helal Kelany, Kelany, Khaled A. Helal, N.J. Dimopoulos +7
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image Processing Techniques and Applications #Optical measurement and interference techniques #Signal Processing (eess.SP) #Synthetic Aperture Radar (SAR) Applications and Techniques #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2010.00220
openalex publication_date 2020/10/01 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
The focus of this work is to explore the use of quantum annealing solvers for\nthe problem of phase unwrapping of synthetic aperture radar (SAR) images.\nAlthough solutions to this problem exist based on network programming, these\ntechniques do not scale well to larger-sized images. Our approach involves\nformulating the problem as a quadratic unconstrained binary optimization (QUBO)\nproblem, which can be solved using a quantum annealer. Given that present\nembodiments of quantum annealers remain limited in the number of qubits they\npossess, we decompose the problem into a set of subproblems that can be solved\nindividually. These individual solutions are close to optimal up to an integer\nconstant, with one constant per sub-image. In a second phase, these integer\nconstants are determined as a solution to yet another QUBO problem. We test our\napproach with a variety of software-based QUBO solvers and on a variety of\nimages, both synthetic and real. Additionally, we experiment using D-Wave\nSystems's quantum annealer, the D-Wave 2000Q. The software-based solvers obtain\nhigh-quality solutions comparable to state-of-the-art phase-unwrapping solvers.\nWe are currently working on optimally mapping the problem onto the restricted\ntopology of the quantum annealer to improve the quality of the solution.\n