Date of Award
2020
Publisher
North Dakota State University
Document Type
Thesis
Degree Awarded
Master of Science (MS)
Department
Computer Science
College
Engineering
Faculty Advisor
Denton, Anne
Description
A vertical-style data structure and operations on data in that structure are explored and tested in the domain of sliding window average algorithms for geographical information systems (GIS) data. The approach allows working with data of arbitrary precision, which is centrally important for very large GIS data sets. The novel data structure can be constructed from existing multi-channel image data, and data in the structure can be converted back to image data. While in the new structure, operations such as addition, division, and bit-level shifting can be performed in a parallelized manner. It is shown that the computation of averages for sliding windows on this data structure can be performed faster than using traditional computation techniques, and the approach scales to larger sliding window sizes.
Recommended Citation
Helsene, Adam Paul, "Vertical Data Structures and Computation of Sliding Window Averages in Two-Dimensional Data" (2020). Computer Science. 99.
https://digitalcommons.ndsu.edu/computer-sci/99
Rights
NDSU policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Author ORCID Identifier
0000-0002-4453-7817
Handle Identifier
https://hdl.handle.net/10365/31823