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

Algorithm 2

MRIFCM_GF algorithm.

	Input: The raw noise image including pixels, the cluster number , the influence factor , the fuzzification index , and a small error threshold .
	Initialization: Compute the reconstructed image of the raw noise image as (28). Select the raw noise image as the guidance image of the guided filter. 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 (30).
	For every cluster , reshape the membership vector into an image with the size of the input image, and implement guided filter on it. Then reshape the filtered membership image into the vector with the size of the membership.
	Update the cluster center matrix by (31).
	Calculate the objective function by (29).
	Until:
	Output: Results of segmentation