| Paper: | MA-P8.1 |
| Session: | Image and Video Enhancement |
| Time: | Monday, September 17, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
BLOCK-COORDINATE GAUSS-NEWTON/REGRESSION METHOD FOR IMAGE REGISTRATION WITH EFFICIENT OUTLIER DETECTION |
| Authors: |
Dong Sik Kim; Hankuk University of Foreign Studies | | |
| | Kiryung Lee; University of Illinois at Urbana-Champaign | | |
| Abstract: |
In this paper, the block-coordinate Gauss-Newton/regression} method is proposed to jointly optimize the spatial registration and the intensity compensation. Here, the intensity compensation is conducted constructing a polynomial regression model, which enables the detection of occluded regions as outliers. Based on the block-coordinate method, we separate the parameter update into two steps for registration and compensation, respectively. Hence, we can perform a joint optimization with low computational complexities, and can apply an appropriate scaling technique to the parameters to be updated for a stable and fast convergence of the algorithm. Excluding outliers, we can successfully align images compensating the intensity differences. |
