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Segmentation on edge preserving smoothing image based on graph theory
Author(s)
Date Issued
December 1, 2000
Type
Conference Paper
Abstract
The presented of noise in an image will cause many undesired small holes in the segmented image. This effect causes an important efficiency decreasing for classifying and describing objects. To remove the embed noise while the edges of the image still preserving, the edge preserving smoothing process must be applied. The smoothing process replaces the pixel intensity of the considered pixel by the average intensity of the most homogeneous mask among the proposed masks. The proposed masks can be preserved the thin region even its width is less than 3 pixels then, the smoothed image will be segmented by graph theory in order to obtain the higher accurate region's boundaries. In the mean time of segmentation process, the homogeneous threshold value has been applied to ensure that the maximum different gray value of each segmented region is controlled.
Citation
International Geoscience and Remote Sensing Symposium IGARSS, 2, 621-623, 2000