Title :
Noise reduction in 3D images using morphological amoebas
Author :
Lerallut, Romain ; Goehm, M. ; Decencière, étienne ; Meyer, Fernand
Author_Institution :
Centre de Morphologie Mathematique, Ecole des Mines de Paris, Fontainebleau, France
Abstract :
This article presents the use of morphological amoebas for the enhancement of 3D medical images. Morphological amoebas are kernels adapting their shape in such a way that they do not cross the contours of the image. They can be used in morphological operations in quite a similar way as classical kernel and are well-fitted for noise-reduction in 3D medical images.
Keywords :
image denoising; image enhancement; medical image processing; microorganisms; 3D medical images enhancement; morphological amoebas; noise reduction; Anisotropic filters; Biomedical imaging; Image reconstruction; Information filtering; Information filters; Kernel; Morphological operations; Noise reduction; Noise shaping; Shape; 3D image processing; anisotropic filters; morphological filters;
Conference_Titel :
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Print_ISBN :
0-7803-9134-9
DOI :
10.1109/ICIP.2005.1529699
