Advisor
Mau Nam Nguyen
Document Type
Report
Publication Date
8-23-2019
Abstract
In this project, we apply nonconvex optimization techniques to study the problems of image recovery and dictionary learning. The main focus is on reconstructing a digital image in which several pixels are lost and/or corrupted by Gaussian noise. We solve the problem using an optimization model involving a sparsity-inducing regularization represented as a difference of two convex functions. Then we apply different optimization techniques for minimizing differences of convex functions to tackle the research problem.
Persistent Identifier
https://archives.pdx.edu/ds/psu/29451
Citation Details
Rodriguez, Karina, "Numerical Algorithms for Solving Nonsmooth Optimization Problems and Applications to Image Reconstructions" (2019). REU Final Reports. 10.
https://pdxscholar.library.pdx.edu/reu_reports/10
Annotations of 5 papers
CryoEM using MicroED Method.pptx (2533 kB)
Summary of research paper and exercise
symposium_presentation.pdf (1251 kB)
Final presentation