This paper proposes the median-type filters with an impulse noise detector
using the decision tree and the particle swarm optimization, for the recovery
of the corrupted gray-level images by impulse noises. It first utilizes an
impulse noise detector to determine whether a pixel is corrupted or not. If
yes, the filtering component in this method is triggered to filter it.
Otherwise, the pixel is kept unchanged. In this work, the impulse noise
detector is an adaptive hybrid detector which is constructed by integrating
10 impulse noise detectors based on the decision tree and the particle swarm
optimization. Subsequently, the restoring process in this method respectively
utilizes the median filter, the rank ordered mean filter, and the progressive
noise-free ordered median filter to restore the corrupted pixel. Experimental
results demonstrate that this method achieves high performance for detecting
and restoring impulse noises, and outperforms the existing well-known
methods.