Title :
Adaptative shock filter for image characters enhancement and denoising
Author :
Guemri, Khouloud ; Drira, Fadoua
Author_Institution :
REGIM-Lab., Univ. of Sfax, Sfax, Tunisia
Abstract :
The paper proposes an adaptive shock filter to restore noisy blurred image characters. This filter introduces an fuzzy decision mechanism to sharpen image features like edges and singularities while an anisotropic diffusion process is used to remove noise. A useful application of the proposed filter is the improvement of image segmentation and binarization task. Its efficiency on degraded document images is appropriately proven via a well-established experimental study based on a comparison with the state-of-the-art methods.
Keywords :
adaptive filters; fuzzy set theory; image denoising; image enhancement; image segmentation; adaptative shock filter; anisotropic diffusion process; binarization task; degraded document images; edges; fuzzy decision mechanism; image characters enhancement; image denoising; image features; image segmentation; noise removal; noisy blurred image restoration; singularities; Databases; Electric shock; Image edge detection; Image enhancement; Image restoration; Noise; Noise reduction; anisotropic diffusion; image denoising; image enhancement; partial differential equations; shock filter;
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2014 6th International Conference of
Conference_Location :
Tunis
DOI :
10.1109/SOCPAR.2014.7008019