Automated map sharpening by maximization of detail and connectivity
An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures in a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. This model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- National Institutes of Health (NIH); USDOE
- Grant/Contract Number:
- AC52-06NA25396; P01GM063210; AC02-05CH11231
- OSTI ID:
- 1437712
- Alternate ID(s):
- OSTI ID: 1440481; OSTI ID: 1461163
- Report Number(s):
- LA-UR-17-30952; ACSDAD; PII: S2059798318004655
- Journal Information:
- Acta Crystallographica. Section D. Structural Biology, Journal Name: Acta Crystallographica. Section D. Structural Biology Vol. 74 Journal Issue: 6; ISSN 2059-7983
- Publisher:
- IUCrCopyright Statement
- Country of Publication:
- United Kingdom
- Language:
- English
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