An image segmentation process, based on the level set method, consists in the time evolution of an initial curve until it reaches the boundary of the objects to be extracted. Classically the evolution of the initial curve is determined by a speed function. In this paper, the speed in the level set procedure is characterized by the combination of two different speed functions and the resulting algorithm is applied to speckled images, like SAR (Synthetic Aperture Radar) images. In order to assess improvements of the segmentation performance, the computational process is tested on synthetic and then applied to real images. Performances are evaluated on synthetic images by using the Hausdorff distance. The real SAR images were acquired during the ERS2 mission.
Speckled images segmentation and algorithm comparison
2015
Abstract
An image segmentation process, based on the level set method, consists in the time evolution of an initial curve until it reaches the boundary of the objects to be extracted. Classically the evolution of the initial curve is determined by a speed function. In this paper, the speed in the level set procedure is characterized by the combination of two different speed functions and the resulting algorithm is applied to speckled images, like SAR (Synthetic Aperture Radar) images. In order to assess improvements of the segmentation performance, the computational process is tested on synthetic and then applied to real images. Performances are evaluated on synthetic images by using the Hausdorff distance. The real SAR images were acquired during the ERS2 mission.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
