Title :
Morphological anisotropic diffusion
Author :
Segall, C. Andrew ; Acton, Scott T.
Author_Institution :
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA
Abstract :
Current formulations of anisotropic diffusion are unable to prevent feature drift and smooth small regions. These deficiencies reduce the effectiveness of the diffusion operation in many image processing tasks, including segmentation, edge detection, compression, and multiscale processing. This paper introduces a morphological diffusion coefficient capable of smoothing small objects while maintaining edge locality. Results are presented that demonstrate its efficacy in edge detection tasks
Keywords :
edge detection; image representation; image segmentation; iterative methods; mathematical morphology; smoothing methods; approximation; edge detection; edge locality; feature drift; image compression; image processing; image representation; image segmentation; iterative solution; morphological anisotropic diffusion; morphological diffusion coefficient; multiscale processing; smooth small regions; Adaptive filters; Anisotropic magnetoresistance; Equations; Filtering; Image edge detection; Image processing; Kernel; Laboratories; Nonlinear filters; Smoothing methods;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.632112
