How to statistically quantify the coverage of features in the data?
To visualize the features, why don't you just do scatter plots? I assume that if you do feature extraction, you know where in the image the features are found. If different features have different "sizes", i.e. some features are point features, whereas others take up e.g. a 5x5 window (and are non-overlapping), you may want to adjust the size of your symbols for the scatter plot to visually improve the relative amount of coverage. 

If you want to quantify the coverage, then you're looking at two independent measures


Density: To this end, you can simply divide the number of features by the image size.
Homogeneity: I've seen Ripley's K used to great success when looking at whether data is homogeneously distributed, or whether it is clustered.