Reproduce Napari visualizations

I would like to generate static images files from NGFF/SpatialData datasets and presets stored in their NGFF Omero metadata, so that one can preview datasets without opening them interactively in Napari.

This combines the idea that SpatialData's data model resembles Napari's, and that datasets can store visualization presets for a reasonable default visualization.

For this, we still need some basic rendering properties:

• blending: additive | opaque…
  Typically, images contain multiple channel, and their visualization is different depending on the microscopy illumination type. Several fluorescence channels can be visualized in a single image by additive blending. However, currently spatialdata-plot "overwrites" pixels of channels underneath.
• color:
  Napari allows to provide a color name for maximum intensity values and generates a corresponding color map.
• contrast_limits (Napari) or window (Omero):
  Typically, the value range of images can differ greatly, and in order to avoid reading all pixels to compute limits, Omero stores absolute limits in the metadata. However, spatialdata-plot currently supports only Matplotlib's relative limits pmin/pmax (as quantiles_for_norm).

Start by reviewing the existing spatialdata-plot rendering path and the NGFF Omero metadata described in the issue. Determine how visualization presets are currently read, then define acceptance checks for additive or opaque blending, Napari-style colors, and absolute contrast limits or windows. Done means static previews reproduce the requested preset properties without opening Napari interactively.