CLIJ2 (BETA test release)

This reference contains all methods currently available in CLIJ2 and CLIJx. Read more about CLIJs release cycle

**Please note:** CLIJ2 and CLIJx are under heavy construction. This list may change at any point.

Method is available in CLIJ (stable release)

Method is available in CLIJ2 (alpha release, read more)

Method is available in CLIJx (experimental version)

[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

Computes the absolute value of every individual pixel x in a given image.

Computes the absolute value of every individual pixel x in a given image.

Adds a scalar value s to all pixels x of a given image X.

Calculates the sum of pairs of pixels x and y of two images X and Y.

Calculates the sum of pairs of pixels x and y from images X and Y weighted with factors a and b.

Converts a adjacency matrix in a touch matrix

Applies an affine transform to a 2D image. Individual transforms must be separated by spaces.

Applies an affine transform to a 3D image. Individual transforms must be separated by spaces.

Deforms an image according to distances provided in the given vector images. It is recommended to use 32-bit images for input, output and vector images.

Deforms an image stack according to distances provided in the given vector image stacks. It is recommended to use 32-bit image stacks for input, output and vector image stacks.

Deforms an image according to distances provided in the given vector images. It is recommended to use 32-bit images for input, output and vector images.

Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

Determines the maximum projection of an image stack along Z. Furthermore, another 2D image is generated with pixels containing the z-index where the maximum was found (zero based).

The automatic thresholder utilizes the threshold methods from ImageJ on a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method. Enter one of these methods in the method text field: [Default, Huang, Intermodes, IsoData, IJ_IsoData, Li, MaxEntropy, Mean, MinError, Minimum, Moments, Otsu, Percentile, RenyiEntropy, Shanbhag, Triangle, Yen]

The automatic thresholder utilizes the threshold methods from ImageJ on a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method. Enter one of these methods in the method text field: [Default, Huang, Intermodes, IsoData, IJ_IsoData, Li, MaxEntropy, Mean, MinError, Minimum, Moments, Otsu, Percentile, RenyiEntropy, Shanbhag, Triangle, Yen]

Takes a pointlist and a touch matrix to determine the average angle of adjacent triangles in a surface mesh. For every point, the average angle of adjacent triangles is saved.

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.

Applies a bilateral filter using a box neighborhood with sigma weights for space and intensity to the input image.

Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary AND operator &. All pixel values except 0 in the input images are interpreted as 1.

Determines pixels/voxels which are on the surface of binary objects and sets only them to 1 in the destination image. All other pixels are set to 0.

Fills holes (pixels with value 0 surrounded by pixels with value 1) in a binary image.

Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary intersection operator &. All pixel values except 0 in the input images are interpreted as 1.

Computes a binary image (containing pixel values 0 and 1) from an image X by negating its pixel values x using the binary NOT operator ! All pixel values except 0 in the input image are interpreted as 1.

Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary OR operator |. All pixel values except 0 in the input images are interpreted as 1.<pre>f(x, y) = x | y</pre>

Subtracts one binary image from another.

Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary union operator |.

Computes a binary image (containing pixel values 0 and 1) from two images X and Y by connecting pairs of pixels x and y with the binary operators AND &, OR | and NOT ! implementing the XOR operator. All pixel values except 0 in the input images are interpreted as 1.

Computes the Gaussian blurred image of an image given two sigma values in X and Y. Thus, the filterkernel can have non-isotropic shape.

Computes the Gaussian blurred image of an image given two sigma values in X, Y and Z. Thus, the filterkernel can have non-isotropic shape.

Computes the Gaussian blurred image of an image given two sigma values in X and Y. Thus, the filterkernel can have non-isotropic shape.

Apply a bottom-hat filter for background subtraction to the input image.

Applies a bottom-hat filter for background subtraction to the input image.

Determines the bounding box of all non-zero pixels in a binary image.

Acquires an image (in fact an RGB image stack with three slices) of given size using a webcam.

Determines the center of mass of an image or image stack and writes the result in the results table in the columns MassX, MassY and MassZ.

Determines the centroids of all labels in a label image or image stack.

Analyses a label map and if there are gaps in the indexing (e.g. label 5 is not present) all subsequent labels will be relabelled.

Apply a binary closing to the input image by calling n dilations and n erosions subsequenntly.

Apply a binary closing to the input image by calling n dilations and n erosions subsequently.

Combines two images or stacks in X.

Combines two images or stacks in Y.

Concatenates two stacks in Z.

Performs connected components analysis to a binary image and generates a label map.

Performs connected components analysis inspecting the box neighborhood of every pixel to a binary image and generates a label map.

Performs connected components analysis inspecting the diamond neighborhood of every pixel to a binary image and generates a label map.

Performs connected components analysis to a binary image and generates a label map.

Converts a three channel image (stack with three slices) to a single channel image (2D image) by multiplying with factors 0.299, 0.587, 0.114.

Convolve the image with a given kernel image.

Copies an image.

This method has two purposes: It copies a 2D image to a given slice z position in a 3D image stack or It copies a given slice at position z in an image stack to a 2D image.

Determines the number of all pixels in a given image which are not equal to 0.

Counts non-zero pixels in a sphere around every pixel.Put the number in the result image.

Counts non-zero pixels in a sphere around every pixel slice by slice in a stack and puts the resulting number in the destination image stack.

Counts non-zero voxels in a sphere around every voxel.Put the number in the result image.

Takes a touch matrix as input and delivers a vector with number of touching neighbors per label as a vector.

Crops a given rectangle out of a given image.

Crops a given sub-stack out of a given image stack.

Performs cross correlation analysis between two images.

Executes a custom operation wirtten in OpenCL on a custom list of images.

Applies particle image velocimetry to two images and registers them afterwards by warping input image 2 with a smoothed vector field.

Determines a maximum projection of an image stack and does a color coding of the determined arg Z (position of the found maximum).

Takes a labelmap and returns an image where all pixels on label edges are set to 1 and all other pixels to 0.

Detects local maxima in a given square/cubic neighborhood. Pixels in the resulting image are set to 1 if there is no other pixel in a given radius which has a higher intensity, and to 0 otherwise.

Detects local maxima in a given square neighborhood of an input image stack. The input image stack is processed slice by slice. Pixels in the resulting image are set to 1 if there is no other pixel in a given radius which has a higher intensity, and to 0 otherwise.

Detects local minima in a given square/cubic neighborhood. Pixels in the resulting image are set to 1 if there is no other pixel in a given radius which has a lower intensity, and to 0 otherwise.

Detects local minima in a given square neighborhood of an input image stack. The input image stack is processed slice by slice. Pixels in the resulting image are set to 1 if there is no other pixel in a given radius which has a lower intensity, and to 0 otherwise.

Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other.

Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other.

Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image. The dilation takes the Moore-neighborhood (8 pixels in 2D and 26 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image. The dilation takes the Moore-neighborhood (8 pixels in 2D and 26 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image. The dilation takes the von-Neumann-neighborhood (4 pixels in 2D and 6 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image. The dilation takes the von-Neumann-neighborhood (4 pixels in 2D and 6 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Generates a distance map from a binary image.

Generates a mesh from a distance matric and a list of point coordinates.

Divides two images X and Y by each other pixel wise.

Scales an image using given scaling factors for X and Y dimensions. The nearest-neighbor method is applied. In ImageJ the method which is similar is called ‘Interpolation method: none’.

Scales an image using given scaling factors for X and Y dimensions. The nearest-neighbor method is applied. In ImageJ the method which is similar is called ‘Interpolation method: none’.

Scales an image using scaling factors 0.5 for X and Y dimensions. The Z dimension stays untouched. Thus, each slice is processed separately. The median method is applied. Thus, each pixel value in the destination image equals to the median of four corresponding pixels in the source image.

Draws a box at a given start point with given size. All pixels other than in the box are untouched. Consider using `set(buffer, 0);`

in advance.

Draws a line between two points with a given thickness.

Draws a sphere around a given point with given radii in x, y and z (if 3D).

Draws a line between two points with a given thickness.

Determines the local entropy in a box with a given radius around every pixel.

Determines if two images A and B equal pixel wise.

Determines if an image A and a constant b are equal.

Determines correction factors for each z-slice so that the average intensity in all slices can be made the same and multiplies these factors with the slices.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image. The erosion takes the Moore-neighborhood (8 pixels in 2D and 26 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image. The erosion takes the Moore-neighborhood (8 pixels in 2D and 26 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image. The erosion takes the von-Neumann-neighborhood (4 pixels in 2D and 6 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image. The erosion takes the von-Neumann-neighborhood (4 pixels in 2D and 6 pixels in 3d) into account. The pixels in the input image with pixel value not equal to 0 will be interpreted as 1.

This operation removes labels from a labelmap and renumbers the remaining labels.

Removes all labels from a label map which touch the edges of the image (in X, Y and Z if the image is 3D).

This operation follows a ray from a given position towards a label (or opposite direction) and checks if there is another label between the label an the image border.

This operation follows a ray from a given position towards a label (or opposite direction) and checks if there is another label between the label an the image border.

This operation removes labels from a labelmap and renumbers the remaining labels.

This operation removes labels from a labelmap and renumbers the remaining labels.

Computes base exponential of all pixels values.

Returns an image with pixel values most distant from 0:

Flips an image in X and/or Y direction depending on boolean flags.

Flips an image in X, Y and/or Z direction depending on boolean flags.

Replaces recursively all pixels of value a with value b if the pixels have a neighbor with value b.

Gauss Jordan elimination algorithm for solving linear equation systems.

Computes the Gaussian blurred image of an image given two sigma values in X and Y.

Computes the Gaussian blurred image of an image given two sigma values in X, Y and Z.

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.

Takes two images containing coordinates and builds up a matrix containing distance between the points.

Generates a feature stack for Trainable Weka Segmentation.

Take a labelmap and a vector of values to replace label 1 with the 1st value in the vector.

Take a labelmap and a column from the results table to replace label 1 with the 1st value in the vector.

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.

The automatic thresholder utilizes the threshold methods from ImageJ on a histogram determined on the GPU to determine a threshold value as similar as possible to ImageJ ‘Apply Threshold’ method.

Determines the bounding box of all non-zero pixels in a binary image.

Determines the center of mass of an image or image stack.

Reads out the size of an image [stack] and writes it to the variables ‘width’, ‘height’ and ‘depth’.

Determines the overlap of two binary images using the Jaccard index.

Determines the maximum of all pixels in a given image.

Determines the mean of all pixels in a given image.

Determines the minimum of all pixels in a given image.

Reads out the size of an image [stack] and writes it to the results table in the columns ‘Width’, ‘Height’ and ‘Depth’.

Determines the overlap of two binary images using the Sorensen-Dice coefficent.

Determines the sum of all pixels in a given image.

Computes the gradient of gray values along X. Assuming a, b and c are three adjacent pixels in X direction. In the target image will be saved as: <pre>b’ = c - a;</pre>

Computes the gradient of gray values along Y. Assuming a, b and c are three adjacent pixels in Y direction. In the target image will be saved as: <pre>b’ = c - a;</pre>

Computes the gradient of gray values along Z. Assuming a, b and c are three adjacent pixels in Z direction. In the target image will be saved as: <pre>b’ = c - a;</pre>

Determines if two images A and B greater pixel wise.

Determines if two images A and B greater pixel wise.

Determines if two images A and B greater or equal pixel wise.

Determines if two images A and B greater or equal pixel wise.

Determines the histogram of a given image.

Converts an image into a table.

Copies a single slice into a stack a given number of times.

Computes the negative value of all pixels in a given image. It is recommended to convert images to 32-bit float before applying this operation.

Determines the overlap of two binary images using the Jaccard index.

Transforms a binary image with single pixles set to 1 to a labelled spots image.

Masks a single label in a label map.

Takes a labelled image and dilates the labels using a octagon shape until they touch.

Generates a coordinate list of points in a labelled spot image.

Applies the Laplace operator (Box neighborhood) to an image.

Applies the Laplace operator (Diamond neighborhood) to an image.

Applies a local minimum and maximum filter.

local id

Computes a binary image with pixel values 0 and 1 depending on if a pixel value x in image X was above of equal to the pixel value m in mask image M.

Computes base e logarithm of all pixels values.

Computes a masked image by applying a mask to an image. All pixel values x of image X will be copied to the destination image in case pixel value m at the same position in the mask image is not equal to zero.

Computes a masked image by applying a label mask to an image.

Computes a masked image by applying a 2D mask to an image stack. All pixel values x of image X will be copied to the destination image in case pixel value m at the same spatial position in the mask image is not equal to zero.

Checks if all elements of a matrix are different by less than or equal to a given tolerance.

Computes the local maximum of a pixels rectangular neighborhood. The rectangles size is specified by its half-width and half-height (radius).

Computes the local maximum of a pixels ellipsoidal neighborhood. The ellipses size is specified by its half-width and half-height (radius).

Computes the local maximum of a pixels cube neighborhood. The cubes size is specified by its half-width, half-height and half-depth (radius).

Computes the local maximum of a pixels spherical neighborhood. The spheres size is specified by its half-width, half-height and half-depth (radius).

Computes the maximum of a constant scalar s and each pixel value x in a given image X.

Computes the maximum of a pair of pixel values x, y from two given images X and Y.

Applies a maximum filter with kernel size 3x3 n times to an image iteratively.

Determines the maximum of all pixels in a given image. It will be stored in a new row of ImageJs Results table in the column ‘Max’.

Determines the maximum intensity in an image, but only in pixels which have non-zero values in another mask image.

Takes a touch matrix and a vector of values to determine the maximum value among touching neighbors for every object.

Determines the maximum projection of an image along X.

Determines the maximum projection of an image along a given dimension. Furthermore, the X and Y dimesions of the resulting image must be specified by the user according to its definition: X = 0 Y = 1 Z = 2

Determines the maximum projection of an image along X.

Determines the maximum projection of an image along Z.

Determines the maximum projection of an image along Z within a given z range.

Computes the local mean average of a pixels rectangular neighborhood. The rectangles size is specified by its half-width and half-height (radius).

Computes the local mean average of a pixels ellipsoidal neighborhood. The ellipses size is specified by its half-width and half-height (radius).

Computes the local mean average of a pixels cube neighborhood. The cubes size is specified by its half-width, half-height and half-depth (radius).

Computes the local mean average of a pixels spherical neighborhood. The spheres size is specified by its half-width, half-height and half-depth (radius).

Determines the distance between pairs of closest spots in two binary images.

Determines the mean average of all pixels in a given image. It will be stored in a new row of ImageJs Results table in the column ‘Mean’.

Determines the mean intensity in a masked image.

Determines the mean intensity in a threshleded image.

Takes a touch matrix and a vector of values to determine the mean value among touching neighbors for every object.

Computes the local mean average of a pixels ellipsoidal 2D neighborhood in an image stack slice by slice. The ellipses size is specified by its half-width and half-height (radius).

Determines the mean squared error (MSE) between two images.

Determines the mean average projection of an image along Z.

Determines the mean projection of an image along Z within a given z range.

Computes the local median of a pixels rectangular neighborhood. The rectangle is specified by its half-width and half-height (radius).

Computes the local median of a pixels ellipsoidal neighborhood. The ellipses size is specified by its half-width and half-height (radius).

Computes the local median of a pixels cuboid neighborhood. The cuboid size is specified by its half-width, half-height and half-depth (radius).

Computes the local median of a pixels spherical neighborhood. The spheres size is specified by its half-width, half-height and half-depth (radius).

Takes a touch matrix and a vector of values to determine the median value among touching neighbors for every object.

Determines the median projection of an image stack along Z.

Computes the local minimum of a pixels rectangular neighborhood. The rectangles size is specified by its half-width and half-height (radius).

Computes the local minimum of a pixels ellipsoidal neighborhood. The ellipses size is specified by its half-width and half-height (radius).

Computes the local minimum of a pixels cube neighborhood. The cubes size is specified by its half-width, half-height and half-depth (radius).

Computes the local minimum of a pixels spherical neighborhood. The spheres size is specified by its half-width, half-height and half-depth (radius).

Takes a touch matrix and a distance matrix to determine the shortest distance of touching neighbors for every object.

Computes the maximum of a constant scalar s and each pixel value x in a given image X.

Computes the minimum of a pair of pixel values x, y from two given images X and Y.

Applies a minimum filter with kernel size 3x3 n times to an image iteratively.

Determines the minimum of all pixels in a given image. It will be stored in a new row of ImageJs Results table in the column ‘Min’.

Determines the minimum intensity in a masked image.

Takes a touch matrix and a vector of values to determine the minimum value among touching neighbors for every object.

Determines the minimum projection of an image along Z.

Determines the minimum projection of an image along Z within a given z range.

Determines the minimum projection of all pixels in an image above a given threshold along Z within a given z range.

Multiplies all pixel intensities with the x, y or z coordinate, depending on specified dimension.

Multiplies all pixels value x in a given image X with a constant scalar s.

Multiplies all pixels value x in a given image X with a constant scalar s from a list of scalars.

Multiplies all pairs of pixel values x and y from two image X and Y.

Multiplies two matrices with each other.

Multiplies all pairs of pixel values x and y from an image stack X and a 2D image Y. x and y are at the same spatial position within a plane.

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.

Determines neighbors of neigbors from touch matrix and saves the result as a new touch matrix.

Applies a non-local means filter using a box neighborhood with a Gaussian weight specified with sigma to the input image.

Apply a maximum filter (box shape) to the input image.

Apply a maximum filter (diamond shape) to the input image.

Apply a minimum filter (box shape) to the input image.

Apply a minimum filter (diamond shape) to the input image.

Determines if two images A and B equal pixel wise.

Determines if two images A and B equal pixel wise.

Apply a local maximum filter to an image which only overwrites pixels with value 0.

Apply a local maximum filter to an image which only overwrites pixels with value 0.

Apply a binary opening to the input image by calling n erosions and n dilations subsequenntly.

Apply a binary opening to the input image by calling n erosions and n dilations subsequenntly.

Organises windows on screen.

For every pixel in source image 1, determine the pixel with the most similar intensity in the local neighborhood with a given radius in source image 2. Write the distance in X and Y in the two corresponding destination images.

Run particle image velocimetry on a 2D+t timelapse.

Pastes an image into another image at a given position.

Pastes an image into another image at a given position.

Meshes all points in a given point list which are indiced in a corresponding index list.

Takes a pointlist with dimensions n*d with n point coordinates in d dimensions and a touch matrix of size n*n to draw lines from all points to points if the corresponding pixel in the touch matrix is 1.

Computes all pixels value x to the power of a given exponent a.

Calculates x to the power of y pixel wise of two images X and Y.

This plugin takes two image filenames and loads them into RAM. The first image is returned immediately, the second image is loaded in the background and will be returned when the plugin is called again.

Determines the extrema of pixel values:

Visualises an image on standard out (console).

Pulls a binary image from the GPU memory and puts it on the currently active ImageJ window as region of interest.

Pulls all labels in a label map as ROIs to a list.

Pulls all labels in a label map as ROIs to the ROI manager.

Writes an image into a string.

Pushes a tile in an image specified by its name, position and size from GPU memory.

Converts an image into a table.

Converts an array to an image.

Converts a table to an image.

Converts a table column to an image.

Converts an string to an image.

Push a tile in an image specified by its name, position and size to GPU memory in order to process it there later.

Read an image from disc.

Reads a raw file from disc and pushes it immediately to the GPU.

Reduces the number of slices in a stack by a given factor. With the offset you have control which slices stay: * With factor 3 and offset 0, slices 0, 3, 6,… are kept. * With factor 4 and offset 1, slices 1, 5, 9,… are kept.

Replaces integer intensities specified in a vector image.

Replaces a specific intensity in an image with a given new value.

Resamples an image with given size factors using an affine transform.

Flippes Y and Z axis of an image stack. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Flippes X, Y and Z axis of an image stack. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Computes a radial projection of an image stack. Starting point for the line is the center in any X/Y-plane of a given input image stack. This operation is similar to ImageJs ‘Radial Reslice’ method but offers less flexibility.

Flippes X, Y and Z axis of an image stack. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Flippes Y and Z axis of an image stack. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Converts a table column to an image.

Converts a table to an image.

Rotates an image in plane. All angles are entered in degrees. If the image is not rotated around the center, it is rotated around the coordinate origin.

Rotates an image stack in 3D. All angles are entered in degrees. If the image is not rotated around the center, it is rotated around the coordinate origin.

Rotates a given input image by 90 degrees clockwise.

Rotates a given input image by 90 degrees counter-clockwise.

Rotates a given input image by 90 degrees counter-clockwise. For that, X and Y axis of an image stack are flipped. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Rotates a given input image by 90 degrees clockwise. For that, X and Y axis of an image stack are flipped. This operation is similar to ImageJs ‘Reslice [/]’ method but offers less flexibility such as interpolation.

Pulls an image from the GPU memory and saves it as TIF to disc.

DEPRECATED: CLIJ scale() is **deprecated**. Use scale2D or scale3D instead!

Scales an image with a given factor.

Scales an image with a given factor.

Sets all pixel values x of a given image X to a constant value v.

Sets all pixel values x of a given column in X to a constant value v.

Sets all pixel values at the image border to a given value.

Sets all pixels in an image which are not zero to the index of the pixel.

Sets all pixel values x of a given plane in X to a constant value v.

Sets all pixel values to their X coordinate

Sets all pixel values to their Y coordinate

Sets all pixel values to their Z coordinate

Fills an image or image stack with uniformly distributed random numbers between given minimum and maximum values.

Sets all pixel values x of a given row in X to a constant value v.

Sets all pixel values a of a given image A to a constant value v in case its coordinates x == y.

Sets all pixel values a of a given image A to a constant value v in case its coordinates x > y.

Sets all pixel values a of a given image A to a constant value v in case its coordinates x < y.

Determine the shortest distance from a distance matrix.

Visualises two 2D images as one RGB image.

Visualises a single 2D image.

Visualises three 2D images as one RGB image

Erodes a binary image until just its skeleton is left.

Determines if two images A and B smaller pixel wise.

Determines if two images A and B smaller pixel wise.

Determines if two images A and B smaller or equal pixel wise.

Determines if two images A and B smaller or equal pixel wise.

Convolve the image with the Sobel kernel.

Determines the overlap of two binary images using the Sorensen-Dice coefficent.

Transforms a spots image as resulting from maximum/minimum detection in an image where every column contains d pixels (with d = dimensionality of the original image) with the coordinates of the maxima/minima.

Stack to tiles.

Determines the standard deviation of all pixels in an image.

Determines the standard deviation of all pixels in an image which have non-zero value in a corresponding mask image.

Takes a touch matrix and a vector of values to determine the standard deviation value among touching neighbors for every object.

Determines the standard deviation projection of an image stack along Z.

Starts acquistion of images from a webcam.

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of background and labelled objects in a label map and corresponding pixels in the original image.

Determines image size (bounding box), area (in pixels/voxels), min, max and mean intensity of all pixels in the original image.

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of labelled objects in a label map and corresponding pixels in the original image.

Stops continous acquistion from a webcam.

Measures time and outputs delay to last call.

Applies Gaussian blur to the input image and subtracts the result from the original image.

Applies Gaussian blur to the input image and subtracts the result from the original image.

Subtracts one image X from a scalar s pixel wise.

Subtracts one image X from another image Y pixel wise.

Sums all pixels slice by slice and returns them in an array.

Determines the sum of all pixels in a given image. It will be stored in a new row of ImageJs Results table in the column ‘Sum’.

Determines the sum intensity projection of an image along Z.

Determines the sum intensity projection of an image along Z.

Determines the sum projection of an image along Z.

Fuses #n# image stacks using Tenengrads algorithm.

Computes a binary image with pixel values 0 and 1. All pixel values x of a given input image with value larger or equal to a given threshold t will be set to 1.

The automatic thresholder utilizes the Default threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Huang threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the IJ_IsoData threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Intermodes threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the IsoData threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Li threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the MaxEntropy threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Mean threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the MinError threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Minimum threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Moments threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Otsu threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Percentile threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the RenyiEntropy threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Shanbhag threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Triangle threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

The automatic thresholder utilizes the Yen threshold method implemented in ImageJ using a histogram determined on the GPU to create binary images as similar as possible to ImageJ ‘Apply Threshold’ method.

Applies a top-hat filter for background subtraction to the input image.

Applies a minimum filter with kernel size 3x3 n times to an image iteratively.

Applies a minimum filter with kernel size 3x3 n times to an image iteratively.

Applies a top-hat filter for background subtraction to the input image.

Converts a touch matrix in an adjacency matrix

Takes a pointlist with dimensions n*d with n point coordinates in d dimensions and a touch matrix of size n*n to draw lines from all points to points if the corresponding pixel in the touch matrix is 1.

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

Trains a Weka model using functionality of Fijis Trainable Weka Segmentation plugin.

Translate an image stack in X and Y.

Translate an image stack in X, Y and Z.

Measures center of mass of thresholded objects in the two input images and translates the second image so that it better fits to the first image.

Applies 2D translation registration to every pair of t, t+1 slices of a 2D+t image stack.

Transpose X and Y axes of an image.

Transpose X and Z axes of an image.

Transpose Y and Z axes of an image.

Determines the variance of all pixels in an image.

Determines the variance in an image, but only in pixels which have non-zero values in another binary mask image.

Takes a binary image and dilates the regions using a octagon shape until they touch.

Apply a binary watershed to a binary image and introduces black pixels between objects.

Takes a point list image representing n points (n*2 for 2D points, n*3 for 3D points) and a corresponding touch matrix , sized (n+1)*(n+1), and exports them in VTK format.

Takes an image with three/four rows (2D: height = 3; 3D: height = 4): x, y [, z] and v and target image.

Takes a point list image representing n points (n*2 for 2D points, n*3 for 3D points) and exports them in XYZ format.