Dynamic Quantization: Two Adaptive Data Structures for Multidimensional Spaces
Joseph O’Rourke, Kenneth R. Sloan · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1984
Two new data structures are defined for use in multidimensional histogramming. Their purpose is to cover a parameter space with a limited number of histogram bins so that fine precision is maintained where it is needed. The original motivation for these data structures was to implement Hough-like transforms in high-dimensional parameter spaces. The two data structures share the ability to adapt to distributions that change with time.