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The proposed approach to correct for optical distortions consists in resorting to a random numerical texture that is printed onto a plate by laser engraving.
In order to obtain numerical texture measures from the matrices, statistical texture features can be extracted from the GLRLM as follows: 1.
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A numerical analysis of texture data was conducted to identify the type of Ni grain boundaries, which control grain growth and texture transformation.
Numerical simulations of texture development in polycrystalline oxygen-free high conductivity (OFHC) copper have been studied using the Taylor, viscoplastic self-consistent (VPSC) and a recent Taylor type polycrystal grain refinement (GR) model for the forward and reverse strain conditions.
Here, we show by numerical examples that texture images satisfy the NAP in the GBT domain and are therefore viable of being reconstructed using the HCoSaMP.
Other features are mathematical descriptors, or numerical 'fingerprints', of texture and intensity patterns; the use of these is well-established in cellular image analysis (Boland and Murphy, 2001), and while they are not directly interpreted as a specific process or function, they sensitively pick up complex changes in the cellular network caused by the genetic perturbations.
Some studies have suggested that humans may be able to make numerical judgements in textures containing large numbers of dots (over 300 dots: [36], [40]).
In the following, we show with the help of numerical examples that also texture images verify the NAP in the graph-based transform (GBT) [16] domain.
The fractal dimension was used as a numerical measure of image texture on digital chest radiographs to distinguish patients with normal lung from those with a diffuse nodular interstitial abnormality.
Using the well-known Reynolds equation, numerical modelling of surface texturing is implemented via finite difference method.
We have implemented the model in modern programmable graphics hardware using a few small numerical lookup tables stored as texture maps.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com