CNF:Weighted Mesh To Image: Difference between revisions

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CNF, external, internal
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Spyridon97 (talk | contribs)
CNF, external, internal
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==Summer 2020==
==Summer 2020==
Create a new image using the weights of:
Create a new image using the weights of:
# k-nearest-neighbors points for each pixel point.
# k-nearest-neighbors points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, neighbor-point[i]) ^ power.
# cell points for each pixel point. Note: If the pixel point is not inside a cell, then weights of the k-nearest-neighbor points will be used.
# cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, cell-point[i]) ^ power.
# the intersection of k-nearest-neighbors points and cell points for each pixel point.
## Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.
Note: Each pixel value is calculated as a weighted mean of the values(weight) of the points. The distance of the pixel from each point is used for the mean-weights, where mean-weight[i] = 1 / (distance[i] ^ power).
# the intersection set of k-nearest-neighbors points and cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, intersection-point[i]) ^ power.
## Note 1: If the Intersection set is empty, then the algorithm `2` will be used.
## Note 2: If the pixel point is not inside a cell, then the algorithm `1` will be used.
# 4) cell points as values in a weighted-mean, were weight[i] = probe-value[i] based on the location of each pixel point inside a cell. Probing values are result of FindCell function.
## Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.

Revision as of 11:07, 10 June 2020

Repository

  1. https://git-community.cs.odu.edu/crtc/Utilities/weightedmeshtoimage

Code

Summer 2020

Create a new image using the weights of:

  1. k-nearest-neighbors points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, neighbor-point[i]) ^ power.
  2. cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, cell-point[i]) ^ power.
    1. Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.
  3. the intersection set of k-nearest-neighbors points and cell points as values in a weighted-mean, were weight[i] = 1 / distance(pixel-point, intersection-point[i]) ^ power.
    1. Note 1: If the Intersection set is empty, then the algorithm `2` will be used.
    2. Note 2: If the pixel point is not inside a cell, then the algorithm `1` will be used.
  4. 4) cell points as values in a weighted-mean, were weight[i] = probe-value[i] based on the location of each pixel point inside a cell. Probing values are result of FindCell function.
    1. Note: If the pixel point is not inside a cell, then the algorithm `1` will be used.
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