Description: we present an improved fuzzy
C-means (FCM) algorithm for image segmentation by introducing
a tradeoff weighted fuzzy factor and a kernel metric. The
tradeoff weighted fuzzy factor depends on the space distance of
all neighboring pixels and their gray-level difference simultaneously.
By using this factor, the new algorithm can accurately
estimate the damping extent of neighboring pixels. In order to
further enhance its robustness to noise and outliers, we introduce
a kernel distance measure to its objective function. The new
algorithm adaptively determines the kernel parameter by using
a fast bandwidth selection rule based on the distance variance
of all data points in the collection. Furthermore, the tradeoff
weighted fuzzy factor and the kernel distance measure are both
parameter free. Experimental results on synthetic and real images
show that the new algorithm is effective and efficient, and is
relatively independent of this type of noise.
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KWFLICM.m