Sigma Filter

This filter is based on the algorithm described in the following paper: Lee, Jong-Sen (1983), "Digital image smoothing and the sigma filter", Computer vision, graphics, and image processing 24 (2): 255-269, CODEN: CVGPDB, ISSN 0734-189X From the website: "The filter smooths an image by taking an average over the neighboring pixels, but only includes those pixels that have a value not deviating from the current pixel by more than a given range. The range is defined by the standard deviation of the pixel values within the neighborhood ("Use Pixels Within ... Sigmas"). If the number of pixels in this range is too low (less than "Minimum Pixel Fraction"), averaging over all neighboring pixels is performed. With the "Outlier Aware" option, averaging over all neighboring pixels excludes the center pixel. Thus, outliers having a value very different from the surrounding are not included in the average and, thus, completely eliminated." (detail see: http://fiji.sc/wiki/index.php/Sigma_Filter)

Options

Span

The Window Span parameter determines the span of the window in one direction. The resulting window size is given by: span*2+1 in each dimension.

Sigma Factor

Factor to scale sigma. It modifies the size of the interval.

Pixel Fraction

The minimum fraction of pixels which have to be in range. Otherwise the mean of all values inside the window is calculated.

Outlier Detection

Extends the option "Pixel Fraction" by leaving out the center pixel if the fraction of pixels is below the minimum.

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.

Out of Bounds Selection

The 'OutOfBounds Strategy' is used when an algorithm needs access to pixels which lie outside of an image (for example convolutions). The strategy determines how an image is extended, for examples see here

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.

Views

Image Viewer

Another, possibly interactive, view on table cells. Displays the selected cells with their associated viewer if it exists. Available views are:
- 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.
- XML
-- XML tree
- Histogram Viewer
-- This viewer shows the histogram of the currently selected image.
- Image Viewer
-- This viewer renders the selected image-cell.
- Missing Value Viewer
-- An empty viewer that is shown when the input cell has no value to display.
- 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.

Workflows

• 01_Spot_DetectionKNIME Hub
• 01_Spot_Detection modif KNIME Forum
• 12_StreamingKNIME Hub
• Akhtar_et_al_Bacterial_FISH_Example_WorkflowKNIME Hub

Links

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Developers