Titlebook: Automating the Analysis of Spatial Grids; A Practical Guide to Valliappa Lakshmanan Book 2012 Springer Science+Business Media Dordrecht. 20

Nonconformist

ALOFT

https://doi.org/10.1007/978-90-481-2510-4 variance is explained. Local measures are computed in the vicinity of a pixel; practical considerations of missing data, wrapping, and window sizes are detailed. Structural measures based on a co-occurrence matrix are defined, and the ways of computing these explained. Finally, we turn our attentio

HUMP

人類(lèi)

Rheumatologist

periodontitis

Automated Analysis of Spatial Grids: Motivation and Challenges, encode every relationship. Another challenge with creating automated algorithms to analyze spatial grids is that low-level image processing operations are rarely sufficient, so domain knowledge needs to be incorporated. Hence, in order to create an automated algorithm to operate on geospatial data,

cortisol

Geospatial Grids,ent distances. Often geospatial grids have to be created from nonuniform 2D arrays such as from an instrument, from vector graphics such as lines or polygons or by interpolating between point observations. Techniques to handle these cases are described.

致敬

Picks-Disease

Neighborhood and Window Operations,oncern, however. We discuss a couple of edge filtering techniques and point out the use of median filters in speckle removal. Morphological operations for dilation and erosion are described and the use of combinations of morphological operations for denoising and gap filling described. Finally, we d

Synchronism

Identifying Objects, allows for local, adaptive thresholds using an immersion metaphor. An enhancement of the watershed transform, suitable for many real-world spatial grids, is to specify objects in terms of a minimum size requirement. The final object identification technique presented in this chapter is contiguity-e