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Air Force

Efficient Hexagonally Sampled Image Processing

Hexagonally arranged data sampling elements improves image resolution

Software & Information Technology
Two Potential Hexagonal RedGreenBlue Display Geometries
Two Potential Hexagonal RedGreenBlue Display Geometries

It has been known since the early 1960s that hexagonal sampling is the optimal sampling approach for isotropically band-limited images, providing a 13.4% improvement in sampling efficiency over rectangular sampling.
Despite this fact and other significant advantages of hexagonal sampling, rectangular sampling is still used for virtually all modern digital image processing systems. This is arguably due to the lack of an efficient addressing system for hexagonal grids.
A new method for addressing hexagonally arranged image sensors that produces an output that can be efficiently computationally manipulated, particularly in digital systems, has been developed by a US Air Force R&D lab. The patented invention, called array set addressing, or ASA, solves the problems for any hexagonally arranged data sampling elements. A primary concept behind ASA is that a hexagonal grid can be represented as a set of two rectangular arrays distinguished by a single binary coordinate. What’s particularly new in the present invention is extending that concept and applying it to addressing captured information from a hexagonal grid of image sensor pixels. The hexagonal grid has greater angular resolution, equidistant spacing, and a higher degree of symmetry than rectangular grids.  Also, since all neighboring pixels in a hexagonal grid share a side, there is no connectivity ambiguity as there is with rectangular grids, which leads to more efficient algorithms that deal with connectivity.

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