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Mathematical Problems in Engineering
Volume 2015, Article ID 138930, 10 pages
Research Article

Quaternion-Based Improved Artificial Bee Colony Algorithm for Color Remote Sensing Image Edge Detection

1College of Geophysics, Chengdu University of Technology, Chengdu 610059, China
2School of Computer Science, Sichuan University of Arts and Science, Dazhou 635000, China
3State Key Laboratory of Wireless Mobile Communications, China Academy of Telecommunications Technology, Beijing 100191, China

Received 12 June 2014; Revised 13 August 2014; Accepted 24 August 2014

Academic Editor: Wai Yuen Szeto

Copyright © 2015 Dujin Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


As the color remote sensing image has the most notable features such as huge amount of data, rich image details, and the containing of too much noise, the edge detection becomes a grave challenge in processing of remote sensing image data. To explore a possible solution to the urgent problem, in this paper, we first introduced the quaternion into the representation of color image. In this way, a color can be represented and analyzed as a single entity. Then a novel artificial bee colony method named improved artificial bee colony which can improve the performance of conventional artificial bee colony was proposed. In this method, in order to balance the exploration and the exploitation, two new search equations were presented to generate candidate solutions in the employed bee phase and the onlookers phase, respectively. Additionally, some more reasonable artificial bee colony parameters were proposed to improve the performance of the artificial bee colony. Then we applied the proposed method to the quaternion vectors to perform the edge detection of color remote sensing image. Experimental results show that our method can get a better edge detection effect than other methods.