GPU accelerated image processing for everyone
This reference contains all methods currently available in CLIJ, CLIJ2 and CLIJx for processing graphs.. Read more about CLIJs release cycle
Please note: CLIJ is deprecated. Make the transition to CLIJ2.
Method is available in CLIJ (deprecated release)
Method is available in CLIJ2 (stable release)
Method is available in CLIJx (experimental release)
Method is available in clEsperanto (experimental)
Categories: Binary, Filter, Graphs, Labels, Math, Matrices, Measurements, Projections, Transformations, Detection, CLIc
[A], B, C,[D], E, F,[G], H, I, J, K,[L],[M],[N], O,[P], Q,[R],[S],[T], U, V, W, X, Y, Z
Converts a adjacency matrix in a touch matrix.
Takes a label map, determines distances between all centroids and replaces every label with the average distance to the n closest neighboring labels.
Determines the average of the n closest points for every point in a distance matrix.
Determines the average of the n far off (most distant) points for every point in a distance matrix.
Takes a touch matrix and a distance matrix to determine the average distance of touching neighbors for every object.
Takes a label map, determines which labels touch and replaces every label with the average distance to their neighboring labels.
Generates a mesh from a distance matric and a list of point coordinates.
Starting from a label map, draw lines between touching neighbors resulting in a mesh.
Starting from a label map, draw lines between n closest labels for each label resulting in a mesh.
Starting from a label map, draw lines between n closest labels for each label resulting in a mesh.
Starting from a label map, draw lines between labels that are closer than a given distance resulting in a mesh.
Starting from a label map, draw lines between touching neighbors resulting in a mesh.
Starting from a label map, draw lines between touching neighbors resulting in a mesh.
Computes the angle in radians between all point coordinates given in two point lists.
Takes two labelmaps with n and m labels and generates a (n+1)*(m+1) matrix where all pixels are set to 0 exept those where labels overlap between the label maps.
Computes the distance between all point coordinates given in two point lists.
Computes the distance in X, Y or Z (specified with parameter axis) between all point coordinates given in two point lists.
Takes two labelmaps with n and m labels_2 and generates a (n+1)*(m+1) matrix where all labels_1 are set to 0 exept those where labels_2 overlap between the label maps.
Produces a touch-matrix where the n nearest neighbors are marked as touching neighbors.
Produces a touch-matrix where the neighbors within a given distance range are marked as touching neighbors.
Takes a label map with n labels and generates a (n+1)*(n+1) matrix where all pixels are set the number of pixels where labels touch (diamond neighborhood).
Takes a labelmap with n labels and generates a (n+1)*(n+1) matrix where all pixels are set to 0 exept those where labels are touching.
Deprecated: Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the maximum distance of touching labels.
Deprecated: Takes a label map, determines which labels touch, the distance between their centroids and the maximum distancebetween touching neighbors. It then replaces every label with the that value.
Deprecated: Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local maximum of this count.
Deprecated: Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the mean distance of touching labels.
Deprecated: Takes a label map, determines which labels touch, the distance between their centroids and the mean distancebetween touching neighbors. It then replaces every label with the that value.
Takes a label map, determines which labels touch and how much, relatively taking the whole outline of each label into account, and determines for every label with the mean of this value and replaces the label index with that value.
Deprecated: Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local mean of this count.
Deprecated: Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the median distance of touching labels.
Deprecated: Takes a label map, determines which labels touch, the distance between their centroids and the median distancebetween touching neighbors. It then replaces every label with the that value.
Deprecated: Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local median of this count.
Deprecated: Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the minimum distance of touching labels.
Deprecated: Takes a label map, determines which labels touch, the distance between their centroids and the minimum distancebetween touching neighbors. It then replaces every label with the that value.
Deprecated: Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local minimum of this count.
Deprecated: Takes a label map, determines distances between all centroids, the mean distance of the n closest points for every point and replaces every label with the standard deviation distance of touching labels.
Deprecated: Takes a label map, determines which labels touch, the distance between their centroids and the standard deviation distancebetween touching neighbors. It then replaces every label with the that value.
Deprecated: Takes a label map, determines which labels touch, determines for every label with the number of touching neighboring labels and replaces the label index with the local standard deviation of this count.
Takes a touch matrix and a distance matrix to determine the maximum distance of touching neighbors for every object.
Takes a label map, determines which labels touch and replaces every label with the maximum distance to their neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the maximum value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the maximum value of neighboring labels.
Takes a touch matrix and a vector of values to determine the maximum value among touching neighbors for every object.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the maximum value of neighboring labels. The radius of the neighborhood can be configured: * radius 0: Nothing is replaced * radius 1: direct neighbors are taken into account * radius 2: neighbors and neighbors or neighbors are taken into account * radius n: …
Takes a label map, determines which labels touch and replaces every label with the maximum distance to their neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the minimum value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the mean average value of neighboring labels.
Takes a touch matrix and a vector of values to determine the mean value among touching neighbors for every object.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the mean average value of neighboring labels. The radius of the neighborhood can be configured: * radius 0: Nothing is replaced * radius 1: direct neighbors are taken into account * radius 2: neighbors and neighbors or neighbors are taken into account * radius n: …
Takes a touch matrix and a vector of values to determine the median value among touching neighbors for every object.
Starts from a label map, determines median touch portion to neighbors (between 0 and 1) and draws a map.
Takes a touch matrix and a distance matrix to determine the shortest distance of touching neighbors for every object.
Takes a label map, determines which labels touch and replaces every label with the minimum distance to their neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the minimum value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the minimum value of neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the minimum value of neighboring labels. The radius of the neighborhood can be configured: * radius 0: Nothing is replaced * radius 1: direct neighbors are taken into account * radius 2: neighbors and neighbors or neighbors are taken into account * radius n: …
Takes a label map, determines which labels touch and replaces every label with the minimum distance to their neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the mode value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the most popular value of neighboring labels.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the most popular value of neighboring labels. The radius of the neighborhood can be configured: * radius 0: Nothing is replaced * radius 1: direct neighbors are taken into account * radius 2: neighbors and neighbors or neighbors are taken into account * radius n: …
Determine the n point indices with shortest distance for all points in a distance matrix.
Determine the n point indices with shortest distance for all points in a distance matrix.
Starts from a label map, determines touch portion to neighbors, counts those above a given value (between 0 and 1) and draws a map.
Takes a label map, determines which labels touch and replaces every label with the distance range ratio (maximum distance divided by minimum distance) to their neighboring labels.
Determines neighbors of neigbors from touch matrix and saves the result as a new touch matrix.
Meshes all points in a given point list which are indiced in a corresponding index list.
Takes a list of point indices to generate a touch matrix (a.k.a. adjacency graph matrix) out of it.
Takes a label map, determines which labels are within a given distance range and replaces every label with the number of neighboring labels.
Takes a label image and an parametric image and reads parametric values from the labels positions.
Takes a label image and an parametric image and reads parametric values from the labels positions.
Determine the shortest distance from a distance matrix.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the standard deviation value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the standard deviation value of neighboring labels.
Takes a touch matrix and a vector of values to determine the standard deviation value among touching neighbors for every object.
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the standard deviation value of touching neighbor labels. The radius of the neighborhood can be configured: * radius 0: Nothing is replaced * radius 1: direct neighbors are taken into account * radius 2: neighbors and neighbors or neighbors are taken into account * radius n: …
Converts a touch matrix in an adjacency matrix
Takes a pointlist with dimensions nd with n point coordinates in d dimensions and a touch matrix of size nn to draw lines from all points to points if the corresponding pixel in the touch matrix is 1.
Takes a label map, determines which labels touch and replaces every label with the number of touching neighbor labels.
Takes a label map, determines which labels touch and replaces every label with the distance range ratio (maximum distance divided by minimum distance) to their neighboring labels.
79 methods listed.