Multi-Parameter Algorithms For Smoothing Data As Applied to Curves, Contours, and Images

<p>Embark on an exploration of subdivision schemes and some heuristics for developing new schemes with applications to curves and surfaces, as well as, to image smoothing and analysis. An explanation of the planning and development stages of smoothing schemes is given. Steps are then taken to derive the rules for new schemes, which implement derivatives and gradients in order to improve the performance of specially localized schemes. Consideration is taken for one dimensional and two dimensional settings. These algorithms have applications such as smoothing the appearance of data sets represented by curves, contours, and surfaces. The algorithms discussed here result in a smooth curve without losing as much information as observed with some traditional algorithms. </p>

Name thesis:degree_name

M.S.

Level thesis:degree_level

Campus Access Thesis

Discipline thesis:degree_discipline

Mathematics

Year

2011

Author dc:creator

• Watson, Holly Lynn

Contributors dc:contributor

• Peter G Binev

• Mathematics
• Physical Sciences and Mathematics
• Data Smoothing

Statement dc:rights

• © 2011, Holly Lynn Watson

Repository record dc:identifier

https://scholarcommons.sc.edu/etd/1617

OAI identifier oai:identifier

oai:scholarcommons.sc.edu:etd-2618