Particle swarm optimization for blurred contour retrieval

This paper concentrates on the estimation of linear and circular blurred contours in an image. To solve this problem, we start from recently investigated signal models, derived through the association of an array of virtual sensors and the image. The array is linear when linear blurred contours are expected, and circular when circular blurred contours are expected. For the first time in this paper, we propose a common array processing model for both types of contours, which makes their retrieval closer to each other. We propose a common criterion to minimize for the estimation of the contour parameters, and justify the usage of particle swarm optimization for its minimization. An application to fire characterization exemplifies our method.