DocumentCode :
2676571
Title :
Maximum segmented-scene spatial entropy thresholding
Author :
Leung, C.K. ; Lam, F.K.
Author_Institution :
Dept. of Electron. Eng., Hong Kong Polytech. Univ., Hong Kong
Volume :
3
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
963
Abstract :
The segmented-scene spatial entropy (SSE) is defined as the amount of information contained in the spatial structure of a segmented scene resulting from segmenting an image. An automatic, nonparametric, unsupervised thresholding algorithm that maximizes the SSE of an image is described, and this algorithm is known as the maximum segmented-scene spatial entropy (MSSE) thresholding algorithm. It is shown that the MSSE-thresholded image contains the maximum amount of information about the original scene and hence good thresholding results are warranted. Simulation and practical results are presented to illustrate the improvement in performance as compared to some other histogram-based thresholding algorithms
Keywords :
image classification; image segmentation; maximum entropy methods; nonparametric statistics; automatic nonparametric algorithm; image segmentation; maximum segmented-scene spatial entropy thresholding; spatial structure; unsupervised thresholding algorithm; Algorithm design and analysis; Entropy; Error correction; Gray-scale; Image processing; Image segmentation; Layout; Pattern recognition; Pixel; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560984
Filename :
560984
Link To Document :
بازگشت