Multidimensional image processing (scipy.ndimage)#
This package contains various functions for multidimensional image processing.
Filters#
convolve(input, weights[, output, mode, ...])
Multidimensional convolution.
convolve1d(input, weights[, axis, output, ...])
Calculate a 1-D convolution along the given axis.
correlate(input, weights[, output, mode, ...])
Multidimensional correlation.
correlate1d(input, weights[, axis, output, ...])
Calculate a 1-D correlation along the given axis.
gaussian_filter(input, sigma[, order, ...])
Multidimensional Gaussian filter.
gaussian_filter1d(input, sigma[, axis, ...])
1-D Gaussian filter.
gaussian_gradient_magnitude(input, sigma[, ...])
Multidimensional gradient magnitude using Gaussian derivatives.
gaussian_laplace(input, sigma[, output, ...])
Multidimensional Laplace filter using Gaussian second derivatives.
generic_filter(input, function[, size, ...])
Calculate a multidimensional filter using the given function.
generic_filter1d(input, function, filter_size)
Calculate a 1-D filter along the given axis.
generic_gradient_magnitude(input, derivative)
Gradient magnitude using a provided gradient function.
generic_laplace(input, derivative2[, ...])
N-D Laplace filter using a provided second derivative function.
laplace(input[, output, mode, cval, axes])
N-D Laplace filter based on approximate second derivatives.
maximum_filter(input[, size, footprint, ...])
Calculate a multidimensional maximum filter.
maximum_filter1d(input, size[, axis, ...])
Calculate a 1-D maximum filter along the given axis.
median_filter(input[, size, footprint, ...])
Calculate a multidimensional median filter.
minimum_filter(input[, size, footprint, ...])
Calculate a multidimensional minimum filter.
minimum_filter1d(input, size[, axis, ...])
Calculate a 1-D minimum filter along the given axis.
percentile_filter(input, percentile[, size, ...])
Calculate a multidimensional percentile filter.
prewitt(input[, axis, output, mode, cval])
Calculate a Prewitt filter.
rank_filter(input, rank[, size, footprint, ...])
Calculate a multidimensional rank filter.
sobel(input[, axis, output, mode, cval])
Calculate a Sobel filter.
uniform_filter(input[, size, output, mode, ...])
Multidimensional uniform filter.
uniform_filter1d(input, size[, axis, ...])
Calculate a 1-D uniform filter along the given axis.
vectorized_filter(input, function, *[, ...])
Filter an array with a vectorized Python callable as the kernel
Fourier filters#
fourier_ellipsoid(input, size[, n, axis, output])
Multidimensional ellipsoid Fourier filter.
fourier_gaussian(input, sigma[, n, axis, output])
Multidimensional Gaussian fourier filter.
fourier_shift(input, shift[, n, axis, output])
Multidimensional Fourier shift filter.
fourier_uniform(input, size[, n, axis, output])
Multidimensional uniform fourier filter.
Interpolation#
affine_transform(input, matrix[, offset, ...])
Apply an affine transformation.
geometric_transform(input, mapping[, ...])
Apply an arbitrary geometric transform.
map_coordinates(input, coordinates[, ...])
Map the input array to new coordinates by interpolation.
rotate(input, angle[, axes, reshape, ...])
Rotate an array.
shift(input, shift[, output, order, mode, ...])
Shift an array.
spline_filter(input[, order, output, mode])
Multidimensional spline filter.
spline_filter1d(input[, order, axis, ...])
Calculate a 1-D spline filter along the given axis.
zoom(input, zoom[, output, order, mode, ...])
Zoom an array.
Measurements#
center_of_mass(input[, labels, index])
Calculate the center of mass of the values of an array at labels.
extrema(input[, labels, index])
Calculate the minimums and maximums of the values of an array at labels, along with their positions.
find_objects(input[, max_label])
Find objects in a labeled array.
histogram(input, min, max, bins[, labels, index])
Calculate the histogram of the values of an array, optionally at labels.
label(input[, structure, output])
Label features in an array.
labeled_comprehension(input, labels, index, ...)
Roughly equivalent to [func(input[labels == i]) for i in index].
maximum(input[, labels, index])
Calculate the maximum of the values of an array over labeled regions.
maximum_position(input[, labels, index])
Find the positions of the maximums of the values of an array at labels.
mean(input[, labels, index])
Calculate the mean of the values of an array at labels.
median(input[, labels, index])
Calculate the median of the values of an array over labeled regions.
minimum(input[, labels, index])
Calculate the minimum of the values of an array over labeled regions.
minimum_position(input[, labels, index])
Find the positions of the minimums of the values of an array at labels.
standard_deviation(input[, labels, index])
Calculate the standard deviation of the values of an N-D image array, optionally at specified sub-regions.
sum_labels(input[, labels, index])
Calculate the sum of the values of the array.
value_indices(arr, *[, ignore_value])
Find indices of each distinct value in given array.
variance(input[, labels, index])
Calculate the variance of the values of an N-D image array, optionally at specified sub-regions.
watershed_ift(input, markers[, structure, ...])
Apply watershed from markers using image foresting transform algorithm.
Morphology#
binary_closing(input[, structure, ...])
Multidimensional binary closing with the given structuring element.
binary_dilation(input[, structure, ...])
Multidimensional binary dilation with the given structuring element.
binary_erosion(input[, structure, ...])
Multidimensional binary erosion with a given structuring element.
binary_fill_holes(input[, structure, ...])
Fill the holes in binary objects.
binary_hit_or_miss(input[, structure1, ...])
Multidimensional binary hit-or-miss transform.
binary_opening(input[, structure, ...])
Multidimensional binary opening with the given structuring element.
binary_propagation(input[, structure, mask, ...])
Multidimensional binary propagation with the given structuring element.
black_tophat(input[, size, footprint, ...])
Multidimensional black tophat filter.
distance_transform_bf(input[, metric, ...])
Distance transform function by a brute force algorithm.
distance_transform_cdt(input[, metric, ...])
Distance transform for chamfer type of transforms.
distance_transform_edt(input[, sampling, ...])
Exact Euclidean distance transform.
generate_binary_structure(rank, connectivity)
Generate a binary structure for binary morphological operations.
grey_closing(input[, size, footprint, ...])
Multidimensional grayscale closing.
grey_dilation(input[, size, footprint, ...])
Calculate a greyscale dilation, using either a structuring element, or a footprint corresponding to a flat structuring element.
grey_erosion(input[, size, footprint, ...])
Calculate a greyscale erosion, using either a structuring element, or a footprint corresponding to a flat structuring element.
grey_opening(input[, size, footprint, ...])
Multidimensional grayscale opening.
iterate_structure(structure, iterations[, ...])
Iterate a structure by dilating it with itself.
morphological_gradient(input[, size, ...])
Multidimensional morphological gradient.
morphological_laplace(input[, size, ...])
Multidimensional morphological laplace.
white_tophat(input[, size, footprint, ...])
Multidimensional white tophat filter.