Title :
Adaptive mathematical morphology: A unified representation theory
Author :
Bouaynaya, Nidhal ; Schonfeld, Dan
Author_Institution :
Dept. of Syst. Eng., Univ. of Arkansas at Little Rock, Little Rock, AR, USA
Abstract :
In this paper, we present a general theory of adaptive mathematical morphology (AMM) in the Euclidean space. The proposed theory preserves the notion of a structuring element, which is crucial in the design of geometrical signal and image processing applications. Moreover, we demonstrate the theoretical and practical distinctions between adaptive and spatially-variant mathematical morphology. We provide examples of the use of AMM in various image processing applications, and show the power of the proposed framework in image denoising and segmentation.
Keywords :
image denoising; image segmentation; mathematical morphology; set theory; Euclidean space; adaptive mathematical morphology; geometrical signal; image denoising; image processing applications; image segmentation; set theory; spatially-variant mathematical morphology; structuring element; unified representation theory; Data mining; Image denoising; Image processing; Image segmentation; Kernel; Morphology; Psychology; Signal design; Signal processing; Systems engineering and theory; adaptive mathematical morphology; basis representation; kernel representation;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414365
