PROJECT TITLE :
Robust Removal Of Fixed Pattern Noise On Multi-Focus Images - 2017
In this paper, we tend to propose a unique methodology restoring multi-focus images based on convex optimization with new constraint for mounted pattern noise. Even weak mounted pattern noise on multi-focus pictures degrades all-in-focus images reconstructed by linear combination of them, particularly, when using telecentric optical systems like microscopes. Our novel methodology introduces constraint for additive mounted pattern noise into total variation minimization and then it is improved for multiplicative fastened pattern noise. The proposed methodology suppresses fixed pattern noise on multi-focus pictures very robustly to avoid such degradation on reconstructed pictures. Experimental results show that our technique achieves high performance compared to straightforward total variation minimization.
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