and Applications., Barcelone: France (2013)' Half Gaussian Kernels Based Shock Filter for

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Titel: and Applications., Barcelone: France (2013)' Half Gaussian Kernels Based Shock Filter for
Autoren: Image Deblurring, Baptiste Magnier, Huanyu Xu
Weitere Verfasser: The Pennsylvania State University CiteSeerX Archives
Quelle: http://hal.inria.fr/docs/00/80/79/92/PDF/Half_Gaussian_Kernels_Based_Shock_Filter_for_Image_Deblurring_and_Regularization_VISAPP_2013.pdf.
Publikationsjahr: 2013
Bestand: CiteSeerX
Schlagwörter: Shock filter, image regularization, deblurring, half Gaussian kernel
Beschreibung: 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 effectively eliminate noise and enhance edges while preserving small objects and corners simultaneously. Compared to other approaches, the proposed method offers both better visual results and qualitative measurements. 1
Publikationsart: text
Dateibeschreibung: application/pdf
Sprache: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.372.9729; http://hal.inria.fr/docs/00/80/79/92/PDF/Half_Gaussian_Kernels_Based_Shock_Filter_for_Image_Deblurring_and_Regularization_VISAPP_2013.pdf
Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.372.9729
http://hal.inria.fr/docs/00/80/79/92/PDF/Half_Gaussian_Kernels_Based_Shock_Filter_for_Image_Deblurring_and_Regularization_VISAPP_2013.pdf
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Dokumentencode: edsbas.9A09F3A9
Datenbank: BASE
Beschreibung
Abstract: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 effectively eliminate noise and enhance edges while preserving small objects and corners simultaneously. Compared to other approaches, the proposed method offers both better visual results and qualitative measurements. 1