Abstract: A method includes receiving a recursively subdivided and reassembled first image comprising pixels, each pixel assigned a region label, subdividing the image into overlapping subsections, determining overlapping pixels surrounding seams along which the overlapping subsections are joined together, accumulating a histogram of co-occurrences of region label pairs of the overlapping pixels surrounding the seams along which the overlapping subsections are joined together, merging overlapping pixels having region labels with a co-occurrence histogram count exceeding a predetermined threshold, and merging spatially and non-spatially adjacent regions of the first image to form a second image with reduced artifacts proximate the seams along which the overlapping subsections are joined together.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing image information using a more computationally efficient version of a previously developed HSEG (Hierarchical Segmentation) algorithm. The HSEG algorithm includes iterations intertwining two forms of region growing to produce a set of hierarchically related image segmentations. The first form is a commonly used approach in which regions are grown by merging the most similar spatially adjacent regions. The second form is a unique approach in which regions are grown by also merging spatially non-adjacent regions that are at least as similar as the spatially adjacent regions merged by the first form in the same iteration. The improved HSEG algorithm limits the regions considered for non-adjacent region merging in the second form of operation to regions having at least a minimum number of pixels. This minimum is dynamically controlled to optimize processing efficiency and image segmentation quality.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for processing image information using a more computationally efficient version of a previously developed HSEG (Hierarchical Segmentation) algorithm. The HSEG algorithm includes iterations intertwining two forms of region growing to produce a set of hierarchically related image segmentations. The first form is a commonly used approach in which regions are grown by merging the most similar spatially adjacent regions. The second form is a unique approach in which regions are grown by also merging spatially non-adjacent regions that are at least as similar as the spatially adjacent regions merged by the first form in the same iteration. The improved HSEG algorithm limits the regions considered for non-adjacent region merging in the second form of operation to regions having at least a minimum number of pixels. This minimum is dynamically controlled to optimize processing efficiency and image segmentation quality.

Abstract: A method, computer readable storage, and apparatus for implementing recursive segmentation of data with spatial characteristics into regions including splitting-remerging of pixels with contagious region designations and a user controlled parameter for providing a preference for merging adjacent regions to eliminate window artifacts.

Abstract: Systems, methods and apparatus are provided through which in some embodiments of recursive hierarchical segmentation of data with any number of spatial dimensions. Some embodiments of the recursive hierarchical segmentation include computationally efficient parallel implementations and other embodiments of the recursive hierarchical segmentation include computationally efficient serial implementations.

Abstract: A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.

Abstract: A method, computer readable storage, and apparatus for implementing a recursive hierarchical segmentation algorithm on a parallel computing platform. The method includes setting a bottom level of recursion that defines where a recursive division of an image into sections stops dividing, and setting an intermediate level of recursion where the recursive division changes from a parallel implementation into a serial implementation. The segmentation algorithm is implemented according to the set levels. The method can also include setting a convergence check level of recursion with which the first level of recursion communicates with when performing a convergence check.