Multi-Scale Feature Pyramid

Build a multi-scale feature pyramid from an image using PyTorch.

Feature pyramids enable detection of objects at different scales. Each level of the pyramid is a downsampled version of the previous level.

Construction:

1. Start with original image at level 0
2. Each subsequent level: apply Gaussian blur then downsample by factor 2
3. Typically 4-6 levels depending on image size

Gaussian blur before downsampling prevents aliasing (Nyquist criterion).

The pyramid enables coarse-to-fine processing:

• Top levels (small): Detect large structures
• Bottom levels (large): Detect fine details

Used in SIFT, HOG, and modern CNNs (FPN - Feature Pyramid Networks).