Image segmentation by region growing and spectral clustering with a natural convergence criterion

The image segmentation approach described is a new hybrid of region growing and spectral clustering. This approach produces a specified number of hierarchical segmentations at different levels of detail, based upon jumps in a dissimilarity criterion. A recursive implementation of this segmentation approach on a cluster of 66 Pentium Pro PCs is described, and the effectiveness of this segmentation approach on Landsat Multispectral Scanner data is discussed.