This book provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates.The strengths offered by hexagonal lattices over square lattices to define digital images are considerable:higher packing densityuniform connectivity of points (pixels) in the latticebetter angular resolution by virtue of having more nearest neighbourssuperlative representation of curvesThe utility of the HIP framework is shown by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. Theory and algorithms are covered as well as details such as accommodating hardware that support only images sampled on a square lattice.This fresh approach offers insight and workable know-how to both researchers and postgraduates.

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