and Applications., Barcelone: France (2013)' Half Gaussian Kernels Based Shock Filter for
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| Název: | and Applications., Barcelone: France (2013)' Half Gaussian Kernels Based Shock Filter for |
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| Autoři: | Image Deblurring, Baptiste Magnier, Huanyu Xu |
| Přispěvatelé: | The Pennsylvania State University CiteSeerX Archives |
| Zdroj: | http://hal.inria.fr/docs/00/80/79/92/PDF/Half_Gaussian_Kernels_Based_Shock_Filter_for_Image_Deblurring_and_Regularization_VISAPP_2013.pdf. |
| Rok vydání: | 2013 |
| Sbírka: | CiteSeerX |
| Témata: | Shock filter, image regularization, deblurring, half Gaussian kernel |
| Popis: | 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 |
| Druh dokumentu: | text |
| Popis souboru: | application/pdf |
| Jazyk: | 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 |
| Dostupnost: | 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 |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| Přístupové číslo: | edsbas.9A09F3A9 |
| Databáze: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | 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 |
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