This paper presents a new algorithm for partitioning a gray-level image into connected homogeneous regions. The novelty of this

algorithm lies in the fact that, by constructing a minimum spanning tree representation of a gray-level image, it reduces a region

partitioning problem to a minimum spanning tree partitioning problem, and hence reduces the computational complexity of the

region partitioning problem. The tree-partitioning algorithm, in essence, partitions a minimum spanning tree into subtrees, representing

different homogeneous regions, by minimizing the sum of variations of gray levels over all subtrees under the constraints that

each subtree should have at least a specified number of nodes, and two adjacent subtrees should have significantly different average

gray-levels. Two (faster) heuristic implementations are also given for large-scale region partitioning problems. Test results have

shown that the segmentation results are satisfactory and insensitive to noise.