Knowledge-based Segmentation of SAR Images

A new approach for the segmentation of still and video SAR images is described in this paper. A priori knowledge about the objects present in the image, e.g., target, shadow, and background terrain, is introduced via Bayes rule. Posterior probabilities obtained in this way are then anisotropically smoothed, and the image segmentation is obtained via MAP classificationsof the smoothed data. When segmenting sequences of images, the smoothed posterior probabilities of past frames are used to learn the prior distributions in the succeedingframe. We show, via a large number of examples from public data sets, that this method provides an efficient and fast technique for addressing the segmentation of SAR data.

• Type: Conference
• Year: 1998
• Where: ICIP
• Authors: Steven Haker, Guillermo Sapiro, Allen Tannenbaum
• Keywords: ICIP 1998, Image Processing, Posterior Probabilities, SAR Images, Smoothed Posterior Probabilities