Title :
Image segmentation by iterative parallel region growing with applications to data compression and image analysis
Author :
Tilton, James C.
Author_Institution :
NASA, Greenbelt, MD, USA
Abstract :
An iterative parallel segmentation algorithm, which avoids the problem of dependency on the order in which portions of the image are processed by performing the globally best merges first, is presented. The segmentation approach and two implementations of the approach on a massively parallel processor (MPP) are discussed. Application of the segmentation approach to data compression and image analysis is described, and results of the application are given for a Landsat thematic mapper image
Keywords :
computerised picture processing; data compression; iterative methods; parallel algorithms; Landsat thematic mapper image; data compression; dependency; globally best merges; image analysis; iterative parallel region growing; iterative parallel segmentation algorithm; massively parallel processor; Clustering algorithms; Convergence; Data compression; Data mining; Government; Image reconstruction; Image segmentation; Iterative methods; Pixel; Testing;
Conference_Titel :
Frontiers of Massively Parallel Computation, 1988. Proceedings., 2nd Symposium on the Frontiers of
Conference_Location :
Fairfax, VA
Print_ISBN :
0-8186-5892-4
DOI :
10.1109/FMPC.1988.47452
