# 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. `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.