GPU accelerated image processing for everyone

This reference contains all methods currently available in CLIJ, CLIJ2 and CLIJx for processing binary images.. 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)

**Categories:** Binary, Filter, Labels, Math, Matrices, Measurements, Neighbors, Projections, Transformations

[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

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.

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]

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 !

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 |.

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.

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

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.

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.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image.

Computes a binary image with pixel values 0 and 1 containing the binary dilation of a given input image.

Generates a distance map from a binary image.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image.

Computes a binary image with pixel values 0 and 1 containing the binary erosion of a given input image.

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

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

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

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

Computes the negative value of all pixels in a given image.

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.

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

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 a masked image by applying a binary mask to an image.

Computes a masked image by applying a binary 2D mask to an image stack.

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

Determines the mean intensity in a masked image.

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.

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

Erodes a binary image until just its skeleton is left.

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

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 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.

Computes a binary image with pixel values 0 and 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.

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

Takes a binary image, labels connected components and dilates the regions using a octagon shape until they touch.

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.