StreamableKNIME Image Types and Nodes version 126.96.36.199906150520 by University of Konstanz
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 weights.
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.
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
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
To use this node in KNIME, install KNIME Image Types and Nodes from the following update site:
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