Hexagonal Image Processing

This book provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, & 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 & frequency domain) & some applications. Theory & algorithms are covered as well as details such as accommodating hardware that support only images sampled on a square lattice. A CD provides code enabling the reader to develop & test algorithms for processing hexagonal images. This fresh approach offers insight and workable know-how to both researchers & postgraduates.