The Maximum Homogeneity Neighborhood Node lays 8 different
areas around one Pixel and applies a measurement of homogeneity which
is then processed in some sort of weight. Then, it calculates each
areas mean-value and combines both mean-value and weight to the new
pixel value, so that the most homogeneous areas take the most part in
the new value of the pixel and areas that lay over edges are not
taken into account. Via a parameter you can regulate the influence of
The Parameter to determine the influence of the
weights via weights^lambda. For lambda = 0 the filter becomes a
simple mean filter which filters the most noise but preserves no
edges. For lambda -> infinity only the most homogeneous area is
taken to get the new Pixel-Value thus Edges are most preserved but
the denoising is not as strong.
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. So the bigger it gets, the more noise is
filtered out but the less details are preserved.
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 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
A suffix appended to the column name. If "Append" is not selected, it can be left empty.
Selection of the columns to be processed.
Images to Filter
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. - Image Viewer -- This viewer renders the selected image-cell. - 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. - Missing Value Viewer -- An empty viewer that is shown when the input cell has no value to display. - XML -- XML tree
To use this node in KNIME, install KNIME Image Types and Nodes from the following update site:
Wait a sec! You want to explore and install nodes even faster? We highly recommend our
NodePit for KNIME
extension for your KNIME Analytics Platform.
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well?
Do you think, the search results could be improved or something is missing?
Then please get in touch! Alternatively, you can send us an email to email@example.com,
follow @NodePit on Twitter,
or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.