Image Filters

Purpose

Image filters can help you get more information from your microscopy image through a variety of methods, such as reducing background, enhancing signal or reducing out of focus signal, sharpening edges, filling in small gaps, and other techniques.

The image filters can also be batch-applied to many images at once using the Batch pipeline function in the Batch Pipeline tool (available on the Pipelines ribbon)

Procedure

  1. Open the image that you want filter.

    • If you have more than one image open, select the image that you want filter by clicking it in the Image organizer; the selected image will have a blue highlight. The filter will operate on the selected image.

    • To filter several images or more, you may want to determine appropriate filter settings on one or a few images here, then use the Batch pipeline function in the Batch Pipeline tool to filter multiple images with your preferred settings.

  2. Click Image Filters and select a filter from the dropdown.

    • Select or modify the filtering options.

    • Check the Preview

  3. Click Apply. The image will be displayed with filtering options applied.

  4. or To save the filtered version of the image, go to FileSave As and click Image or Image Stack, depending on if you want to save a single plane image, a single plane of a multiple-plane image, or an image stack (all planes in a multiple-plane image).

    Change the filename and/or the file location in the Save As dialog to avoid overwriting the original image file.

Image-filter descriptions and options

Correct illumination

Use Correct illumination to minimize unexpected counterstain unevenness in fluorescence images caused by tiling artifacts, uneven illumination, and non-uniform staining. This tool is designed for use in color channels with dense fluorescence signals, for example from counterstains like DAPI and fluorescent Nissl that are used for visualization of cytoarchitecture.

Sharpen image (Unsharp mask)

Reduce edge blurriness by enhancing edges using the unsharp mask technique.

Background subtraction

Minimize background in images by estimating and removing background illumination using an adaptive, local adjustment of image contrast.