porespy.filters

This module contains a variety of functions for altering images based on the structural characteristics, such as pore sizes. A definition of a filter is a function that returns an image the same shape as the original image, but with altered values.

Functions

apply_chords(im[, spacing, axis, trim_edges, label])	Adds chords to the void space in the specified direction.
apply_chords_3D(im[, spacing, trim_edges])	Adds chords to the void space in all three principle directions.
apply_padded(im, pad_width, func[, pad_val])	Applies padding to an image before sending to func, then extracts
capillary_transform(im[, dt, sigma, theta, g, rho_wp, ...])	Uses the Washburn equation to convert distance transform values to a capillary
chunked_func(func[, parallel_kw, im_arg, strel_arg])	Performs the specfied operation "chunk-wise" in parallel using dask.
dilate(im, r[, dt, method, smooth])	Perform dilation with a round structuring element
distance_transform_lin(im[, axis, mode])	Replaces each void voxel with the linear distance to the nearest solid
erode(im, r[, dt, method, smooth])	Perform erosion with a round structuring element
fftmorphology(im, strel[, mode])	Perform morphological operations on binary images using fft approach for
fill_closed_pores(im[, conn])	Fills all closed pores that are isolated from the main void space.
fill_invalid_pores(im[, axis, conn])	Fills invalid pores which are either closed or do not span the domain
fill_surface_pores(im[, axis, conn])	Fill surface pores
find_closed_pores(im[, conn])	Finds closed pores that a not connected to any surface
find_disconnected_voxels(im[, inlets, conn])	Identifies all voxels that are not connected to specified inlets
find_dt_artifacts(dt)	Label points in a distance transform that are closer to image boundary
find_floating_solid(im[, conn, incl_surface])	Finds all solid that that is not attached to main solid structure.
find_invalid_pores(im[, axis, conn])	Finds invalid pores which are either closed or do not span the domain
find_peaks(dt[, r_max, strel, sigma, parallel_kw])	Finds local maxima in the distance transform
find_small_clusters(im[, trapped, min_size, conn])	Finds small isolated clusters of voxels which were identified as trapped and
find_surface_pores(im[, axis, conn])	Finds surface pores that do not span the domain
find_trapped_clusters(im, seq, outlets[, conn, method])	Find the trapped regions given an invasion sequence map and specified outlets
flood(im, labels[, mode])	Floods/fills each region in an image with a single value based on the
flood_func(im, func[, labels])	Flood each isolated region in an image with a constant value calculated by
hold_peaks(im[, axis, ascending])	Replaces each voxel with the highest value along the given axis.
local_thickness(im[, dt, method, smooth, mask, ...])	Insert a maximally inscribed sphere at every pixel labelled by sphere radius
local_thickness_bf(im[, dt, mask, smooth])	Insert a maximally inscribed sphere at every pixel labelled by sphere radius
local_thickness_conv(im[, dt, sizes, smooth])	Calculates the radius of the largest sphere that overlaps each voxel while
local_thickness_dt(im[, dt, sizes, smooth])	Calculates the radius of the largest sphere that overlaps each voxel while
local_thickness_imj(im[, dt, smooth, approx])	Insert a maximally inscribed sphere at every pixel labelled by sphere radius
nl_means_layered(im[, cores, axis, patch_size, ...])	Apply the non-local means filter to each 2D layer of a stack in parallel.
nphase_border(im[, conn])	Identifies the voxels in regions that border N other regions.
pc_to_satn(pc, im[, mode])	Converts a capillary pressure map to a saturation map
pc_to_seq(pc, im[, mode])	Converts a capillary pressure map to a sequence map
porosimetry(im[, dt, inlets, sizes, method, smooth])	Each location is assigned the radius of the largest sphere that can reach it
prune_branches(skel[, branch_points, iterations])	Remove all dangling ends or tails of a skeleton
reduce_peaks(peaks)	Any peaks that are broad or elongated are replaced with a single voxel
region_size(im[, conn])	Replace each voxel with the size of the region to which it belongs
satn_to_seq(satn, im[, residual, mode])	Converts a saturaiton map to a sequence map
seq_to_satn(seq, im[, mode])	Converts a sequence map to a saturation map
size_to_pc(im, size[, f])	Converts size map into capillary pressure map
size_to_satn(size[, im, bins, mode])	Converts size map to a saturation map
size_to_seq(size[, im, bins, mode])	Converts a size map to a sequence map
snow_partitioning(im[, dt, r_max, sigma, peaks])	Partition the void space into pore regions using a marker-based
snow_partitioning_n(im[, r_max, sigma, peaks])	This function partitions an imaging oontain an arbitrary number of
snow_partitioning_parallel(im[, r_max, sigma, parallel_kw])	Performs SNOW algorithm in parallel (or serial) to reduce time
trim_disconnected_voxels(im[, inlets, conn])	Removes foreground voxels not connected to specified inlets.
trim_extrema(im, h[, mode])	Trims local extrema in greyscale values by a specified amount.
trim_floating_solid(im[, conn, incl_surface])	Removes all solid that that is not attached to main solid structure.
trim_nearby_peaks(peaks, dt[, f])	Removes peaks that are nearer to another peak than to solid
trim_nonpercolating_paths(im[, axis, inlets, outlets, ...])	Remove all nonpercolating pores between specified locations
trim_saddle_points(peaks, dt[, maxiter])	Removes peaks that were mistakenly identified because they lied on a
trim_saddle_points_legacy(peaks, dt[, maxiter])	Removes peaks that were mistakenly identified because they lied on a
trim_small_clusters(im[, min_size])	Removes clusters voxel of a given size or smaller