Name
Title | ||
|---|---|---|
Image Noise Cancellation By Taking Advantage Of The Principal Component Analysis Technique |
Abstract | ||
|---|---|---|
In this paper, some advantages of the principal component analysis (PCA) technique have been used to carry out the reconstruction of an original image from a filtered one. First, the original image was contaminated and filtered afterwards. Then, the filtered image was decomposed in principal components (PCs), and the original image was approximately reconstructed from some PCs of the filtered image. Finally, the periodicity of the PCs was introduced, and it was used to show that it is plausible to reconstruct an image by periodizing the first PCs. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/IECON.2018.8591437 | IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | Field | DocType |
Principal components analysis, image reconstruction, image filtering | Iterative reconstruction,Pattern recognition,Control theory,Image coding,Image noise,Artificial intelligence,Engineering,Principal component analysis | Conference |
ISSN | Citations | PageRank |
1553-572X | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wilmar Hernandez | 1 | 28 | 15.89 |
| Alfredo Méndez | 2 | 0 | 0.68 |
| Francisco Ballesteros | 3 | 0 | 0.34 |