Post-Grant Reports
Document Type
Report
Publication Date
3-6-2017
Disciplines
Applied Mathematics | Applied Statistics | Mathematics | Photography
Abstract
In this project, we studied how to enhance image quality by denoising and deblurring a given image mathematically. We compared some existing state-of-the-art methods for image denoising and deblurring. We implemented the algorithms numerically using Matlab.
We studied the possibility of combining statistical analysis with the traditional image restoration methods including using wavelets and framelets and we derived some encouraging preliminary results.
My research student Alleta Maier gave a sequence of talks on the project including the Pacific Northwest Mathematical Association of America conference at Oregon State University in April, 2016; Linfield College Taylor Series in March, 2016, and Linfield College Student Symposium in May, 2016. The results derived from this project successfully built the ground work for our further study of the problem and were used directly in the REU project on image deblurring in the summer of 2016 at Willamette University under my supervision.
Related Resource
Looking for a (Super)resolution to an Image Processing Problem
Recommended Citation
Luo, Xiaoyue, "Application of Inverse Problems in Imaging" (2017). Post-Grant Reports. Report. Submission 113.
https://digitalcommons.linfield.edu/facgrants/113
Included in
Applied Mathematics Commons, Applied Statistics Commons, Mathematics Commons, Photography Commons
Comments
This research was conducted as part of a Linfield College Student-Faculty Collaborative Research Grant in 2015, funded by the Office of Academic Affairs.
To see pictures generated using the researcher’s programs, click the Download button.