Using Heaps in Recursive Hierarchical Segmentation of Data

speed has been made in the algorithm and implementing software reported in “Modified Recursive Hierarchical Segmentation of Data” (GSC-14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The segmentation process includes an iterative subprocess, in each iteration of which it is necessary to determine a best pair of regions to merge [merges being justified by one or more measure(s) similarity of pixels in the regions]. In the previously reported version of the algorithm and software, the choice of a best pair of regions to merge involved the use of a fully sorted list of regions. That version was computationally inefficient because a fully sorted list is not needed: what is needed is only the identity of the pair of regions characterized by the smallest measure of dissimilarity. The present modification replaces the use of a fully sorted list with the use of data heaps, which are computationally more efficient for performing the required comparisons among dissimilarity measures. The modification includes the incorporation of standard and modified functions for creating and updating data heaps.