src.supersampling package¶
Submodules¶
src.supersampling.uniform_grid module¶
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src.supersampling.uniform_grid.unif_grid(array, factor)¶ Scales an image by a factor using uniform using the grid algorithm in uniform distribution. Note: the result is significantly worse for non-integer factors. (Nearest-neighbor interpolation)
- Parameters
array – a numpy array representing the image
- Returns
a numpy array representing the scaled image
- Return type
ndarray
src.supersampling.uniform_grid_2 module¶
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src.supersampling.uniform_grid_2.unif_grid_2(array, factor)¶ Scales an image by a factor using uniform using the grid algorithm in uniform distribution. (Bilinear interpolation)
- Parameters
array – a numpy array representing the image
- Returns
a numpy array representing the scaled image
- Return type
ndarray
src.supersampling.bicubic module¶
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src.supersampling.bicubic.bicub_inter(array, factor)¶ Scales an image by a factor using bicubic interpolation.
- Parameters
array – a numpy array representing the image
- Returns
a numpy array representing the scaled image
- Return type
ndarray
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src.supersampling.bicubic.bicub_val(m)¶ Compututes derivatives to calculate coefficients.
- M
4 by 4 matrix
- Returns
4 by 4 matrix
- Return type
ndarray
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src.supersampling.bicubic.compute_coeff(col)¶ Computes coefficients for bicubic interpolation.
- Col
a numpy array representing a single color
- Returns
a dictionary storing every set of coefficients
- Return type
dict