![]() The Saturated pixels and Normalize options are ignored whenĮqualize Histogram is checked. Hold the alt key down to use the standard histogram equalization algorithm. Modified algorithm that takes the square root of the histogram values. Histogram equalization are applied to all slices in the stack.Ĭheck Equalize histogram to enhance the image using histogram equalization.Ĭreate a selection and the equalization will be based on the histogram of the selection. If this option is enabled, normalization and Note that normalization of RGB images is not supported. The maximum range is 0-255 for 8-bit images and 0-65535 for 16-bit images. The range is equal to the maximum range for the data type, or 0-1.0 for float images. Zero to prevent a few outlying pixel from causing the histogram stretch to not work as intended.Ĭheck Normalize and ImageJ will recalculate the pixel values of the image so Increasing this value increases contrast. Saturated pixels determines the number of pixels in the image that are allowed This command does not alter pixel values as long as the Normalize andĮqualize histogram options are not enabled. Macro demonstrates how to add particles found by Find Maxima to the ROI Manager.Įnhances image contrast by using either histogram stretching or histogram equalization.īoth methods are described in detail in the Macro runs it on all the images in a stack and creates a second stack containing the output images. "Exclude Edge Maxima" applies to the maximum, not to the particle.įind Maxima does not work on stacks, but the Particles touching the edge if "Exclude Edge Maxima" is selected. Note that "Segmented Particles" will usually result in In the output image does not depend on the "Output Type" selected. The number of particles (as obtained by "Analyze Particles") The "Black Background" option in Process>Binary>Options. Output is a binary image, with foreground 255 and background 0, using an inverted or normal LUT depending on "Output Type", the area below the lower threshold is considered a background. The upper threshold of the image is ignored. "Above Lower Threshold" - (This option appears for thresholded images only.)įinds maxima above the lower threshold only.Check Light Background if the image background is brighter than the objects you want to find,Īs it is in the Cell Colony image in the illustration above.The edge of the image (edge of the selection does not matter). "Exclude Edge Maxima" - Excludes maxima if the area within the noise tolerance surrounding a maximum touches."Count" - Displays the number of maxima in the Results window."Display Point selection" - Displays a multi-point selection with a point at each maximum.Process>Binary>Watershed, which uses the Euclidian distance map). The image by a watershed algorithm applied to the values of the image (in contrast to "Segmented Particles" - Assumes that each maximum belongs to a particle and segments."Maxima Within Tolerance" - all points within the "Noise Tolerance" for each maximum."Single Points" - results in one single point per maximum.Only one maximum within this area is accepted. For accepting a maximum, this area must not containĪny point with a value higher at than the maximum. In other words, a threshold is set at the maximum value minus noise tolerance and theĬontiguous area around the maximum above the threshold is analyzed. (calibrated units for calibrated images). "Noise Tolerance" - Maxima are ignored if they do not stand out from the surroundings by more than this value.ThisĬommand is based on a plugin contributed by Michael Schmid.Ī dialog box is displayed with the following options: Unweighted average of the colors depending on the Edit>Options>Conversions settings. ![]() With the maxima, or one segmented particle per maximum, marked.įor RGB images, maxima of luminance are selected, with the luminance defined as weighted or The final image is produced by combining the two derivatives using the square root of the sum of the squares.ĭetermines the local maxima in an image and creates a binary (mask-like) image of the same size Two 3x3 convolution kernels (show below) are used to generate vertical and horizontal derivatives. Uses a Sobel edge detector to highlight sharp changes in intensity in the active image or selection. This filter uses the following weighting factors to replace each pixel with a weighted average of the 3x3 neighborhood. Increases contrast and accentuates detail in the image or selection, but may also accentuate noise. This filter replaces each pixel with the average of its 3x3 neighborhood. Home | contents | previous | next Process Menuīlurs the active image or selection.
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