ISMM05 Special Issue: Image ltering using morphological amoebas
نویسندگان
چکیده
This paper presents morphological operators with nonxed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experiments on grayscale and color images demonstrate that these novel lters outperform classical morphological operations with a xed, space-invariant structuring element for noise reduction applications. Tests on synthetic 3D images are then performed to show the high noise-reduction capacity of amoeba-based lters.
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