Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion
SIAM Journal on Numerical Analysis
A New Interpretation and improvement of the Nonlinear Anisotropic Diffusion for Image Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear diffusion filtering on extended neighborhood
Applied Numerical Mathematics
Fuzzy anisotropic diffusion for speckle filtering
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Noise reduction and edge detection via kernel anisotropic diffusion
Pattern Recognition Letters
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering
IEEE Transactions on Image Processing
Hi-index | 12.05 |
Anisotropic diffusion filters, which are motivated from heat diffusion between mediums, have become a widely used technique in the field of image processing. In the initial proposals of anisotropic diffusion filters, 4-neighborhood values with diffusivity functions are computed independently for each spatial location because of numerical approximation. However, anisotropic diffusion filters could not be used in real-time image and video processing applications because they need diffusivity parameters, which must be specified by users in every sampling period. In this study, a fuzzy adaptive diffusion filter using extended neighborhood without diffusivity functions has been developed. The fuzzy adaptive diffusion filter does not require any parameter chosen by user and therefore they could be employed in real-time applications. In the fuzzy adaptive diffusion filter, a similarity transformation by means of relation matrix and fuzzy logic is carried out. Accordingly, the similarity image, output of transformation, is directly used as a heat diffusion coefficient in the diffusion filter. Results show that the fuzzy adaptive diffusion filter is very efficient for removing noise in image while preserving edges.