CNF:Weighted Mesh To Image: Difference between revisions

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===Best Algorithm===
===Best Algorithm===
Evidently the best algorithm both visually and by looking into the metrics is the algorithm 4.
Evidently the best algorithm both visually and by looking into the metrics is algorithm 4.
 
=Changed Weights Examples=
==Summer 2020==
 
'''Algorithm 4 will be used'''
===Inverted weighted abs(weight[i] - maxWeight)===

Revision as of 12:10, 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. 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.

Comparison Metrics:

  1. Mean Weighted pixel value difference
    1. File:MeanWeightedPixelValueFormula.png
  2. Average Hausdorff Distance (itk filter)
  3. Similarity Index (itk filter)

Comparison Examples

Summer 2020

Left: Mesh, Middle: Algorithm Result. Right: Image

KNN, number of points = 4, power = 1.5

  1. Mean Weighted pixel value difference: 0.000395461
  2. Average Hausdorff Distance: 0.030885
  3. Similarity Index: 0.986463

Cell Points, number of points = 4, power = 1.5

  1. Mean Weighted pixel value difference: 0.0002258
  2. Average Hausdorff Distance: 0.030885
  3. Similarity Index: 0.986463

Intersection of KNN and Cell points, number of points = 5, power = 1.5

  1. Mean Weighted pixel value difference: 0.000273839
  2. Average Hausdorff Distance: 0.030885
  3. Similarity Index: 0.986463

Cell points with probing weights, number of points = 4, power = 1.5

  1. Mean Weighted pixel value difference: 9.17551e-05
  2. Average Hausdorff Distance: 0.030885
  3. Similarity Index: 0.986463

Best Algorithm

Evidently the best algorithm both visually and by looking into the metrics is algorithm 4.

Changed Weights Examples

Summer 2020

Algorithm 4 will be used

Inverted weighted abs(weight[i] - maxWeight)

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