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Illustration of the partitioning scheme used to extract texture samples.
All the images, rotated by hardware and software, are divided into smaller texture samples.
For each dataset four texture samples from four classes are shown.
The computational time was measured while rotating the 2500 texture samples to the eight orientations.
There are 20 nonoverlapping 128×128 texture samples for each class under each situation.
The descriptors are applied to all the texture samples, rotated by hardware and by each of the five interpolation methods.
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Given a specific application, these methods can produce, reproduce or extend a given texture sample.
Figure 7 shows the computation time relative to rotating the texture sample using linear interpolation.
Figure 5 shows one texture sample from each dataset under three different noise levels.
One texture sample from each one of the six datasets under increasing levels of additive Gaussian white noise.
Each texture sample is intensity normalized to have a mean value of 127 and a standard deviation of 40.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com