FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

Zhao, J.; Huang, G.; Zhang, J.

The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

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Zhao, J. / Huang, G. / Zhang, J.: FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES. 2017. Copernicus Publications.

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