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 density
uniform connectivity of points (pixels) in the lattice
better angular resolution by virtue of having more nearest neighbours
superlative representation of curves
The 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. A CD-ROM provides code enabling the reader to develop and test algorithms for processing hexagonal images.
This fresh approach offers insight and workable know-how to both researchers and postgraduates.
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