filters Package
filters Package
frost Module
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pyradar.filters.frost.calculate_all_Mi(window_flat, factor_A, window)[source]
Compute all the weights of pixels in the window.
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pyradar.filters.frost.calculate_local_weight_matrix(window, factor_A)[source]
Returns an array with the weights for the pixels in the given window.
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pyradar.filters.frost.compute_coef_var(image, x_start, x_end, y_start, y_end)[source]
Compute coefficient of variation in a window of [x_start: x_end] and
[y_start:y_end] within the image.
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pyradar.filters.frost.frost_filter(img, damping_factor=2.0, win_size=3)[source]
Apply frost filter to a numpy matrix containing the image, with a window of
win_size x win_size.
By default, the window size is 3x3.
kuan Module
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pyradar.filters.kuan.kuan_filter(img, win_size=3, cu=0.25)[source]
Apply kuan to a numpy matrix containing the image, with a window of
win_size x win_size.
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pyradar.filters.kuan.weighting(window, cu=0.25)[source]
Computes the weighthing function for Kuan filter using cu as the noise
coefficient.
lee Module
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pyradar.filters.lee.lee_filter(img, win_size=3, cu=0.25)[source]
Apply lee to a numpy matrix containing the image, with a window of
win_size x win_size.
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pyradar.filters.lee.weighting(window, cu=0.25)[source]
Computes the weighthing function for Lee filter using cu as the noise
coefficient.
lee_enhanced Module
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pyradar.filters.lee_enhanced.assert_parameters(k, cu, cmax)[source]
Asserts parameters in range.
Parameters:
- k: in [0:10]
- cu: positive
- cmax: positive and greater equal than cu
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pyradar.filters.lee_enhanced.lee_enhanced_filter(img, win_size=3, k=1.0, cu=0.523, cmax=1.73)[source]
Apply Enhanced Lee filter to a numpy matrix containing the image, with a
window of win_size x win_size.
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pyradar.filters.lee_enhanced.weighting(pix_value, window, k=1.0, cu=0.523, cmax=1.73)[source]
Computes the weighthing function for Lee filter using cu as the noise
coefficient.
mean Module
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pyradar.filters.mean.mean_filter(img, win_size=3)[source]
Apply a ‘mean filter’ to ‘img’ with a window size equal to ‘win_size’.
Parameters:
- img: a numpy matrix representing the image.
- win_size: the size of the windows (by default 3).
utils Module
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pyradar.filters.utils.assert_indices_in_range(width, height, xleft, xright, yup, ydown)[source]
Asserts index out of image range.
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pyradar.filters.utils.assert_window_size(win_size)[source]
Asserts invalid window size.
Window size must be odd and bigger than 3.