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3-D Image Analysis via Jacobi Moments with GPU-Accelerated Algorithms

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Wang_Puwei_Thesis_final_copy_2021-12-06.pdf (2.448Mb)

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Author

Wang, Puwei

Uri

https://hdl.handle.net/10680/1977

Date

2021-11-22

Doi

10.36939/ir.202112171430

Citation

Wang, Puwei. 3-D Image Analysis via Jacobi Moments with GPU-Accelerated Algorithms; A thesis submitted to the Faculty of Graduate Studies in partial fulfillment of the requirements for the Master of Science degree, Department of Applied Computer Science, The University of Winnipeg. Winnipeg, Manitoba, Canada: University of Winnipeg, December 2021. DOI: 10.36939/ir.202112171430.

Abstract

This research has developed a parallel algorithm to compute 3-Dimensional Jacobi moments with high efficiency and accuracy. The algorithm was implemented in CUDA C. Our developing progress was in the order of Legendre moments, Gegenbauer moments, and Jacobi moments investigated on the 2-D image. Then, we extended research from 2-D to 3-D image. To verify the algorithm’s performance, we have implemented image reconstruction from higher orders up to 500 on testing image sized at 512×512×512. The experiment was deployed on Nvidia Tesla V100, which restrained computational time within 400 milliseconds, and the PSNR value of reconstructed image reached up to 53.6382.

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