Use of Statistical Distribution for Segmentation of Sar Imagens of Oceanic Areas

In this work the use of statistical techniques will be approached for segmentation of SAR images, with the purpose of ship detection, being used RADARSAT images of the Brazilian coast. As described in Rocha et al (2001) and Rocha and Stech (2003), a specific software for ship detection was developed where, based on Eldhuset (1996), Vachon et al (1997), Oliver and Quegan (1998), Zaart et al (1999), Ferreira et al (2000) and Macedo et al (2001), some routines were implemented for the use of several statistical distributions for the segmentation of the images, as, for example, the Weibull, Gama, and K distributions. Initially, the shape and scale factors were dear in function of the statistical characteristics of each image, as average, variance and standard deviation. However due to the variability of these characteristics in agreement with each image, they were established values patterns for these factors, that allowed a desirable adaptation of the curve of the distribution to the curve of the histogram of the image. These routines were, then, tested for this group of images and its results were analyzed. The results were analyzed individually, through a comparison among them and, also, using a RGB composition among them.