Edge Detection of Impulse Noise Image Based on Quantum Collapsing Theory

Abstract

It is the key to select the appropriate structure elements in the edge detection using morphological gradient operator. A new quantum measurement is proposed in this paper based on quantum collapsing theory in which the possible noisy pixels are collapsed to state 0 while no participating in morphological operation. As the noise intensity increases, the size of the window of the structural elements of superposition states is adaptively increased and quantum collapsing morphological gradient operator is created. The experimental results on the edge detection of the image corrupted with impulse noise show that the proposed algorithm has strongly ability of anti-noise. The normalized mean square error of the new algorithm increases slowly with impulse noise intensity. Further more, the new algorithm is consistent with the traditional morphological gradient operator on noise-free image edge detection.