Half Gaussian Kernels Based Shock Filter for Image Deblurring and Regularization

Baptiste Magnier (1) , Xu Huanyu (2) , Philippe Montesinos (1)

1 LGI2P - Laboratoire de Génie Informatique et Ingénierie de Production
2 NJUST - Nanjing University of Science and Technology

In this paper, a shock-diffusion model is presented to restore both blurred and noisy image. The proposed approach uses a half smoothing kernel to get the precise edge directions, and use different shock-diffusion strategies for different image regions. Experiment results on real images show that the proposed model can ef- fectively eliminate noise and enhance edges while preserving small objects and corners simultaneously. Com- pared to other approaches, the proposed method offers both better visual results and qualitative measurements.

Domaines: Traitement des images [eess.IV]

Baptiste Magnier, Xu Huanyu, Philippe Montesinos. Half Gaussian Kernels Based Shock Filter for Image Deblurring and Regularization. 8th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications., Feb 2013, Barcelone, France. http://www.visapp.visigrapp.org/?y=2013. ⟨hal-00807992⟩