LeDebruiteur

Computer vision project done during the last Bachelor semester.
The aim is to show the use of a few filtering methods to reduce different kind of noises.
And compare deep learning models with more conventional filters.

Authors :

• Jonas Freiburghaus @JonasFreibur
• Romain Capocasale @RomainCapo

Filters

• Sharpness and edge
  • Wiener
  • Laplacian
  • High pass using FFT
  • Gaussian weighted
• Noise
  • Mean
  • Median
  • Low pass using FFT
  • Conservative
  • Gaussian

Inspired from :

• Image De-raining Using a Conditional Generative Adversarial Network

Credits :

To train the models we used the Calthech101 Dataset.

L. Fei-Fei, R. Fergus and P. Perona. One-Shot learning of object
categories. IEEE Trans. Pattern Recognition and Machine Intelligence. In
press