.png){kind=icon}
.png){kind=icon}
Return
A non-linear image processing approach through fuzzy measures
.png){kind=icon}
PRE
AI
DOI：10.1016/S0167-8655(97)00090-1.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In the general framework of non-linear image processing techniques, a new approach to non-linear image filtering is presented. Non-linear techniques have proved to give better results, which are also more robust to noise as compared to linear approaches. The proposed approach tries to overcome some of the drawbacks of these techniques through a simple application of fuzzy measures and operators. The originality and the strength of the proposed work consists in the simultaneous use of intensity and topological information, as evaluated through the use of a fuzzy distance measure named intensity-connectedness. Evaluation of the performance through the use of various error measures is shown on standard images, corrupted with various kinds of noise, and compared to different filtering techniques. (C) 1997 Elsevier Science B.V.
Keywords:
image filtering
non-linear techniques
fuzzy measures
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
7.9K
Citations:
1.6W
Organization
No organization information available