Title: Automatic registration of high resolution satellite images using artificial immune system and mutual information
Authors: Akram Bennour; Bornia Tighiouart
Addresses: Department of Mathematics and Computer Science, University of Tébessa, Constantine Road, 12000 Tébessa, Algeria; Department of Computer Science, Badji Mokhtar-Annaba University, B.P. 12 – 23000 Annaba, Algeria ' Department of Computer Science, Badji Mokhtar-Annaba University, B.P. 12 – 23000 Annaba, Algeria
Abstract: Image registration is the process that allows geometric alignment of two images by determining the transformation that provides the most accurate match between two images. It is a crucial underlying process in many remote sensing applications such as multi-temporal classification, change detection, environmental monitoring, cloud removal, video geo-registration and map updating, etc. In this paper, we introduce a new approach for automated image registration without the need of sensors parameters and control points. The main characteristic of the algorithm is the use of a powerful search strategy based on artificial immune system (AIS) and mutual information as similarity measure. The method was implemented and tested using a variety of high-resolution satellite imagery such as Ikonos (0.8 metre resolution), QuickBird (0.8 m) and WorldView-2 (0.5 metres) respectively taken from Brazil, Iran and China. Experimental results and comparative studies demonstrate the effectiveness of the proposed approach for registration of high resolution satellite images.
Keywords: satellite images; image registration; teledetection; mutual information; artificial immune system; AIS; artificial intelligence; computer vision; automatic registration; geometric alignment; image alignment; remote sensing; Brazil; Iran; China.
International Journal of Computational Vision and Robotics, 2014 Vol.4 No.1/2, pp.145 - 160
Received: 25 Mar 2013
Accepted: 09 Aug 2013
Published online: 18 Feb 2014 *