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Maximum Finder

StreamableKNIME Image Types and Nodes version 1.8.0.201907250605 by University of Konstanz

Find pixels with highest value in their local surroundings, so called maxima. Output of this node is a binary image with the found pixels in white (value 1). When using the option "Output with Tolerance Areas", the output binary image will not only contain one highest value pixel in its area, but also all other pixels which have the same value (affected by "Noise Tolerance"). Otherwise these pixels positions are averaged to one pixel which will be marked in white (value 1).

To find minima instead, you might want to invert the input.

Options

Noise Tolerance
Sets the tolerance for comparison of two pixels. This is useful when an image is affected noise or more extreme values between maxima and minima are desirable.
Suppression
Ensures that two maxima are never closer to each other than the suppression value given. This is achieved by removing one of two found maxima which do not fulfill this criterion. To reduce amount of found maxima, it may be sufficient to raise noise tolerance level instead. Note: Suppression comes at the cost of a little more computation time.
Output with Tolerance Areas
If multiple pixels have the same value (respecting noise tolerance) as a maximum they form a tolerance area and will be output to the resulting binary image if this option is enabled.
Dimension Selection

This component allows the selection of dimensions of interest. If an algorithm cannot, as it only supports fewer dimensions than the number of dimensions of the image, or shouldnot, as one wants to run the algorithm only on subsets of the image, be applied on the complete image, the dimension selection can be used to define the plane/cube/hypercube on which the algorithm is applied. Example 1 with three dimensional Image (X,Y,Time): An algorithm cannot be applied to the complete image, as it only supports two dimensional images. If you select e.g. X,Y then the algorithm will be applied to all X,Y planes individually. Example 2 with three dimensional Image (X,Y,Time): The algorithm can be applied in two, three or even more dimensions. Select the dimensions to define your plane/cube/hypercube on which the algorithm will be applied.

Column Selection

Column Creation Mode

Mode how to handle the selected column. The processed column can be added to a new table, appended to the end of the table, or the old column can be replaced by the new result

Column Suffix
A suffix appended to the column name. If "Append" is not selected, it can be left empty.
Column Selection
Selection of the columns to be processed.

Input Image

Output Ports

Binary image (containing maxima represented as value 1).

Views

Image Viewer
Another, possibly interactive, view on table cells. Displays the selected cells with their associated viewer if it exists. Available views are:
- Histogram Viewer
-- This viewer shows the histogram of the currently selected image.
- BigDataViewer
-- A viewer shown when the user selects an interval of rows and columns in the viewer. This viewer combines all images and labelings in the selected interval to one image by rendering them next to each other. Alternatively, the images and labelings can be layed over each other.
- Missing Value Viewer
-- An empty viewer that is shown when the input cell has no value to display.
- Image Viewer
-- This viewer renders the selected image-cell.
- XML
-- XML tree
- Labeling View
-- View on a labeling/segmentation
- Combined View
-- A viewer shown when the user selects an interval of rows and columns in the viewer. This viewer combines all images and labelings in the selected interval to one image by rendering them next to each other. Alternatively, the images and labelings can be layed over each other.

Installation

To use this node in KNIME, install KNIME Image Processing from the following update site:

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