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

fYear

2009

fDate

7-10 Nov. 2009

Firstpage

2265

Lastpage

2268

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2009 16th IEEE International Conference on

Conference_Location

Cairo

ISSN

1522-4880

Print_ISBN

978-1-4244-5653-6

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2009.5414365

Filename

5414365