 |
Technical Program
Paper Detail
| Paper: | WP-P6.1 |
| Session: | Remote Sensing Imaging and Processing |
| Time: | Wednesday, October 11, 14:20 - 17:00 |
| Presentation: |
Poster
|
| Title: |
A GENERIC BINARY TREE-BASED PROGRESSIVE DEMOSAICKING METHOD FOR MULTISPECTRAL FILTER ARRAY |
| Authors: |
Lidan Miao; University of Tennessee | | | | | Hairong Qi; University of Tennessee | | | | | Rajeev Ramanath; North Carolina State University | | |
| Abstract: |
The technique of multispectral filter array (MSFA) is a multispectral extension of the widely deployed color filter array (CFA), which uses single chip sensors and subsequent interpolation strategies to produce full color images. However, multispectral demosaicking presents unique challenges to traditional CFA demosaicking algorithms which cannot be directly extended to deal with various filter arrays with different numbers of spectral bands or different spatial patterns within each band. In addition, the more spectral bands involved, the more sparse each band samples the image plane, and the less information we can utilize when performing the interpolation. In this paper, we study a generic MSFA demosaicking method, which follows a binary tree structure to determine the order according to which different spectral bands and different pixel locations within each band are progressively interpolated, making the edge information utilized more effectively. The proposed method is demonstrated to outperform three traditional interpolation techniques as well as three advanced CFA demosaicking methods using two performance measures, the root mean square error (RMSE) for reconstruction fidelity and the classification accuracy for target recognition performance. |
|
