BUIFD

BUIFD

Deep learning image denoiser

Blind and universal image denoising consists of using a unique model that denoises images with any level of noise. It is especially practical as noise levels do not need to be known when the model is developed or at test time. We propose a blind and universal deep learning image denoiser based on an optimal denoising solution, which we call fusion denoising. Our approach improves real-world grayscale additive image denoising. It also improves state-of-the-art color image denoising performance on every single noise level by an average of 0.1dB.

Deep Neural NetworksImages
Key facts
Maturity
Support
C4DT
Inactive
Lab
Unknown
  • Technical
  • Research papers

Image and Visual Representation Lab

Image and Visual Representation Lab
Sabine Süsstrunk

Prof. Sabine Süsstrunk

The Image and Visual Representation Lab (IVRL) performs research that is primarily focused on the capture, analysis, and reproduction of color images. Aiming to improve everyone’s photographic experience, we develop algorithms and systems that help us understand, process, and measure images.
Their research areas are computational photography, color image processing, computer vision, and image quality.

This page was last edited on 2024-04-14.