Multi-dimensional image processing (scipy.ndimage)¶

This package contains various functions for multi-dimensional image processing.

Filters¶

 convolve(input, weights[, output, mode, …]) Multidimensional convolution. convolve1d(input, weights[, axis, output, …]) Calculate a one-dimensional convolution along the given axis. correlate(input, weights[, output, mode, …]) Multi-dimensional correlation. correlate1d(input, weights[, axis, output, …]) Calculate a one-dimensional correlation along the given axis. gaussian_filter(input, sigma[, order, …]) Multidimensional Gaussian filter. gaussian_filter1d(input, sigma[, axis, …]) One-dimensional 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 multi-dimensional filter using the given function. generic_filter1d(input, function, filter_size) Calculate a one-dimensional filter along the given axis. generic_gradient_magnitude(input, derivative) Gradient magnitude using a provided gradient function. generic_laplace(input, derivative2[, …]) N-dimensional Laplace filter using a provided second derivative function. laplace(input[, output, mode, cval]) N-dimensional Laplace filter based on approximate second derivatives. maximum_filter(input[, size, footprint, …]) Calculate a multi-dimensional maximum filter. maximum_filter1d(input, size[, axis, …]) Calculate a one-dimensional maximum filter along the given axis. median_filter(input[, size, footprint, …]) Calculate a multidimensional median filter. minimum_filter(input[, size, footprint, …]) Calculate a multi-dimensional minimum filter. minimum_filter1d(input, size[, axis, …]) Calculate a one-dimensional minimum filter along the given axis. percentile_filter(input, percentile[, size, …]) Calculate a multi-dimensional percentile filter. prewitt(input[, axis, output, mode, cval]) Calculate a Prewitt filter. rank_filter(input, rank[, size, footprint, …]) Calculate a multi-dimensional rank filter. sobel(input[, axis, output, mode, cval]) Calculate a Sobel filter. uniform_filter(input[, size, output, mode, …]) Multi-dimensional uniform filter. uniform_filter1d(input, size[, axis, …]) Calculate a one-dimensional uniform filter along the given axis.

Fourier filters¶

 fourier_ellipsoid(input, size[, n, axis, output]) Multi-dimensional ellipsoid fourier filter. fourier_gaussian(input, sigma[, n, axis, output]) Multi-dimensional Gaussian fourier filter. fourier_shift(input, shift[, n, axis, output]) Multi-dimensional fourier shift filter. fourier_uniform(input, size[, n, axis, output]) Multi-dimensional 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]) Multi-dimensional spline filter. spline_filter1d(input[, order, axis, …]) Calculate a one-dimensional 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(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, …]) Multi-dimensional binary closing with the given structuring element. binary_dilation(input[, structure, …]) Multi-dimensional binary dilation with the given structuring element. binary_erosion(input[, structure, …]) Multi-dimensional binary erosion with a given structuring element. binary_fill_holes(input[, structure, …]) Fill the holes in binary objects. binary_hit_or_miss(input[, structure1, …]) Multi-dimensional binary hit-or-miss transform. binary_opening(input[, structure, …]) Multi-dimensional binary opening with the given structuring element. binary_propagation(input[, structure, mask, …]) Multi-dimensional binary propagation with the given structuring element. black_tophat(input[, size, footprint, …]) Multi-dimensional 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, …]) Multi-dimensional greyscale 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, …]) Multi-dimensional greyscale opening. iterate_structure(structure, iterations[, …]) Iterate a structure by dilating it with itself. morphological_gradient(input[, size, …]) Multi-dimensional morphological gradient. morphological_laplace(input[, size, …]) Multi-dimensional morphological laplace. white_tophat(input[, size, footprint, …]) Multi-dimensional white tophat filter.

Utility¶

 imread(*args, **kwds) imread is deprecated! imread is deprecated in SciPy 1.0.0, and will be removed in 1.2.0.