I'm not really participating in this paper, but I assumed the getting started section would start off a bit more basic. Maybe something like

> One of the main goals of scikit-image is to make it easy for any user to get started quickly---especially users who are already familiar with Python's scientific tools. To that end, the basic image is just a standard NumPy array, which exposes pixel data directly to the user. A new user can simply the load an image from disk (or use one of scikit-image's sample images), process that image with one or more image filters, and quickly display the results:

```python
from skimage import data, io, filter

image = data.coins()  # or any NumPy array!
edges = filter.sobel(image)
io.imshow(edges)
```