Robust removal of fixed pattern noise on multi-focus images
Kazuya Kodama, Kenta Fukui, Takayuki Hamamoto
Abstract
In this paper, we propose a novel method restoring multi-focus images based on convex optimization with new constraint for fixed pattern noise. Even weak fixed pattern noise on multi-focus images degrades all-in-focus images reconstructed by linear combination of them, especially, when using telecentric optical systems such as microscopes. Our novel method introduces constraint for additive fixed pattern noise into total variation minimization and then it is improved for multiplicative fixed pattern noise. The proposed method suppresses fixed pattern noise on multi-focus images very robustly to avoid such degradation on reconstructed images. Experimental results show that our method achieves high performance compared to simple total variation minimization.
BibTeX
@inproceedings{icassp2017_robustremovaloff,
title = {Robust removal of fixed pattern noise on multi-focus images},
author = {Kazuya Kodama and Kenta Fukui and Takayuki Hamamoto},
booktitle = {ICASSP 2017},
year = {2017}
}