Knowledge-based segmentation of SAR images
Publication
, Journal Article
Haker, S; Sapiro, G; Tannenbaum, A
Published in: IEEE International Conference on Image Processing
December 1, 1998
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 classifications of the smoothed data. When segmenting sequences of images, the smoothed posterior probabilities of past frames are used to learn the prior distributions in the succeeding frame. 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.
Duke Scholars
Published In
IEEE International Conference on Image Processing
Publication Date
December 1, 1998
Volume
1
Start / End Page
597 / 601
Citation
APA
Chicago
ICMJE
MLA
NLM
Haker, S., Sapiro, G., & Tannenbaum, A. (1998). Knowledge-based segmentation of SAR images. IEEE International Conference on Image Processing, 1, 597–601.
Haker, S., G. Sapiro, and A. Tannenbaum. “Knowledge-based segmentation of SAR images.” IEEE International Conference on Image Processing 1 (December 1, 1998): 597–601.
Haker S, Sapiro G, Tannenbaum A. Knowledge-based segmentation of SAR images. IEEE International Conference on Image Processing. 1998 Dec 1;1:597–601.
Haker, S., et al. “Knowledge-based segmentation of SAR images.” IEEE International Conference on Image Processing, vol. 1, Dec. 1998, pp. 597–601.
Haker S, Sapiro G, Tannenbaum A. Knowledge-based segmentation of SAR images. IEEE International Conference on Image Processing. 1998 Dec 1;1:597–601.
Published In
IEEE International Conference on Image Processing
Publication Date
December 1, 1998
Volume
1
Start / End Page
597 / 601