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])

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.

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.

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.