1. A method for detection of local image structures represented as clusters in a joint-spatial range domain, comprising: receiving an input image made having one or more clusters in a joint-spatial range domain, and each of the one or more clusters having a corresponding mode; receiving a set of analysis matrices; selecting through each one of the analysis matrices, using the selected analysis matrix to partition the input image into the one or more clusters and their corresponding modes, and computing a mean, μ, and a local covariance matrix Σ for each of the corresponding modes of each of the one or more clusters; building a mode tree with at least one branch having a plurality of leaves, each leaf representing a respective one of the modes and the corresponding cluster, and cycling through each branch of the mode tree and selecting at least one of the one or more clusters corresponding to the modes represented by the plurality of leaves, wherein each selected cluster has a stable mean and stable covariance matrix across the set of analysis matrices, and each of the selected clusters is indicative of a local image structure.