  Most superpixel methods are sensitive to noise and cannot control the
superpixel number precisely. To solve these problems, in this paper, we propose
a robust superpixel method called fuzzy simple linear iterative clustering
(Fuzzy SLIC), which adopts a local spatial fuzzy C-means clustering and dynamic
fuzzy superpixels. We develop a fast and precise superpixel number control
algorithm called onion peeling (OP) algorithm. Fuzzy SLIC is insensitive to
most types of noise, including Gaussian, salt and pepper, and multiplicative
noise. The OP algorithm can control the superpixel number accurately without
reducing much computational efficiency. In the validation experiments, we
tested the Fuzzy SLIC and OP algorithm and compared them with state-of-the-art
methods on the BSD500 and Pascal VOC2007 benchmarks. The experiment results
show that our methods outperform state-of-the-art techniques in both noise-free
and noisy environments.
