Analyze_Intermediate_Images
Create ensemble point clouds(.spbr) from one input point cloud
$ ./analyzeIntermediateImages [input_file] [output_path]
Input repeat level (the default repeat level is 1) : 10
Num. of input points : 1122011
Repeat level : 10
Num. of points in each ensemble : 112201
Shuffled.
ensemble1.spbr done.
ensemble2.spbr done.
ensemble3.spbr done.
ensemble4.spbr done.
ensemble5.spbr done.
ensemble6.spbr done.
ensemble7.spbr done.
ensemble8.spbr done.
ensemble9.spbr done.
ensemble10.spbr done.
File export of all ensembles is complete.
Automatically, snapshot all intermediate images by using spbr_auto_snap
$ python spbr_continuously.py [spbr_file_path] [spbr_header_file] [repeat_level]
Calculate variance(standard deviation) for each corresponding pixels
$ python calc_variance_for_each_pixel.py [input_images_path] [repeat_level] [image_resolution]
Intermediate image (L=100)
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Original point cloud (L=1)
Coords Noise |
Color Noise |
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Standard deviation image and histogram
Coords Noise |
Color Noise |
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Transition of standard deviation when increasing repeat level
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Color Noise |
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M_mean and M_max |
M/L |
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