@inbook{8e1193c503544ed08b3d8babf8aa0c4e,
title = "Cellular automata enhanced quantum inspired edge detection",
abstract = "The developing of techniques for image processing based on quantum-inspired algorithms is a recent subject of study with promising results. Quantum-inspired edge detecting algorithms are a novel approach to detect fine details, especially in medical images. Since quantum inspired algorithms based on quantum measurement are susceptible to some noise related to their probabilistic nature their output can be degraded. This work proposes a quantum-inspired edge detection algorithm with an enhancement stage using cellular automata to reduce the degradation of the detected edges. The proposed method uses gradient operators applied to grayscale images that will be the input for a quantum-inspired measurement stage. After the measurement, a cellular automaton is used to eliminate noise and to obtain thinner edges. Comparative results are presented.",
keywords = "Cellular automata, Edge detection, Image enhancement, Quantum inspired, Quantum measurement",
author = "Yoshio Rubio and Oscar Montiel and Roberto Sep{\'u}lveda",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.",
year = "2018",
doi = "10.1007/978-3-319-67137-6_15",
language = "Ingl{\'e}s",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "141--146",
booktitle = "Advances in Intelligent Systems and Computing",
address = "Alemania",
}