Light field denoising using 4D anisotropic diffusion

Pierre Allain (1) , Laurent Guillo (1) , Christine Guillemot (1)

1 Sirocco - Analysis representation, compression and communication of visual data

In this paper, we present a novel light field denoising algorithm using a vector-valued regularization operating in the 4D ray space. More precisely, the method performs a PDE-based anisotropic diffusion along directions defined by local structures in the 4D ray space. It does not require prior estimation of disparity maps. The local structures in the 4D light field are extracted using a 4D tensor structure. The paper then describes the strategy retained for setting the diffusion tensor parameters for the targeted denoising application. It then analyzes the influence of the model parameters on the denoising performance. Experimental results show that the proposed denoising algorithm performs well compared to state of the art methods while keeping tractable complexity.

Mots clés: anisotropic diffusion; denoising; Light Field; regularization

Domaines: Traitement du signal et de l'image [eess.SP]

Pierre Allain, Laurent Guillo, Christine Guillemot. Light field denoising using 4D anisotropic diffusion. ICASSP 2019 - IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. pp.1692-1696, ⟨10.1109/ICASSP.2019.8682709⟩. ⟨hal-02116372⟩