We present a fast edge-preserving cascadic multilevel image restoration method for reducing blur and noise in contaminated images. The method also can be applied to segmentation. Our multilevel method blends linear algebra and partial differential equation techniques. Regu- larization is achieved by truncated iteration on each level. Prolongation is carried out by nonlinear edge-preserving and noise-reducing operators. A thresholding updating technique is shown to reduce “ringing” artifacts. Our algorithm combines deblurring, denoising, and segmentation within a single framework.
S.Morigi, F.Sgallari, L.Reichel (2009). An edge-preserving multilevel method for deblurring, denoising, and segmentation. BERLIN HEIDELBERG : Springer-Verlag.
An edge-preserving multilevel method for deblurring, denoising, and segmentation
MORIGI, SERENA;SGALLARI, FIORELLA;
2009
Abstract
We present a fast edge-preserving cascadic multilevel image restoration method for reducing blur and noise in contaminated images. The method also can be applied to segmentation. Our multilevel method blends linear algebra and partial differential equation techniques. Regu- larization is achieved by truncated iteration on each level. Prolongation is carried out by nonlinear edge-preserving and noise-reducing operators. A thresholding updating technique is shown to reduce “ringing” artifacts. Our algorithm combines deblurring, denoising, and segmentation within a single framework.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
