We consider the problem of segmenting a digitized image consisting of two univariate populations. Assume a priori knowledge allows incomplete assignment of voxels in the image, in the sense that a fraction of the voxels can be identified as belonging to population ∏0, a second fraction to ∏1, and the remaining fraction have no a priori identification. Based upon estimates of the short length scale spatial covariance of the image, we develop a method utilizing indicator kriging to complete the image segmentation.
|Number of pages||13|
|Journal||IEEE Transactions on Pattern Analysis and Machine Intelligence|
|State||Published - 1999|