Multiscale Pyramids

Multiscale image pyramids are a fundamental concept in OME-NGFF that enable efficient visualization and analysis of large images.

Why Pyramids?

Modern microscopy produces images that can be gigabytes or even terabytes in size. Loading an entire image at full resolution is:

  • Slow: Transferring large amounts of data takes time

  • Memory-intensive: May exceed available RAM

  • Unnecessary: When viewing zoomed out, full resolution is wasteful

How Pyramids Work

A pyramid stores the same image at multiple resolution levels:

Level 0: 4096 x 4096  (full resolution)
Level 1: 2048 x 2048  (2x downsampled)
Level 2: 1024 x 1024  (4x downsampled)
Level 3:  512 x  512  (8x downsampled)

Viewers load only the resolution level appropriate for the current zoom level, enabling smooth navigation of arbitrarily large images.

Downsampling Methods

Different downsampling methods are appropriate for different data types:

Method

Use Case

ome_zarr.scale.Methods.resize

Fast skimage-based resizing

ome_zarr.scale.Methods.nearest

Categorical data (labels, segmentations)

ome_zarr.scale.Methods.zoom

Downsampling using the scipy zoom function

ome_zarr.scale.Methods.local_mean

Local averaging for smoother results

See ome_zarr.scale.Methods for all available options and more details.

Resources