Morphological Reconstruction-Based Image-Guided Fuzzy Clustering with a Novel Impact Factor

Algorithm 1

IFCM_GF algorithm.

	Input: The original noise image including pixels, the cluster number , the influence factor , the fuzzification index , and a small error threshold .
	Initialization: Select the raw noise image as the guidance image. Adjust the guidance image by multiplying the influence factor . Randomly pick pixels as the initialized cluster centers. Set the iteration index .
	Repeat:
	Update the membership matrix by (5).
	For every cluster , reshape the membership vector [] into an image with the size of the input image, and implement a guided filter on it. Then reshape the filtered membership image back to the vector shape.
	Update the cluster center matrix by (7).
	Calculate the objective function by (1).
	Until:
	Output: Results of segmentation