* The '''Log detector''' applies a plain LoG segmentation on the image. All calculations are made in the Fourier space, which makes it optimal for intermediate spot sizes, between ≈5 and ≈20 pixels in diameter.
* The '''Dog detector''' uses the [http://en.wikipedia.org/wiki/Blob_detection#The_difference_of_Gaussians_approach difference of Gaussians] approach to approximate a LoG filter by the difference of 2 Gaussians. Calculations are made in the direct space, and it is optimal for small spot sizes, below ≈5 pixels.
* The '''
Downsmapled LoG detector''' uses the LoG detector, but downsizes the image by an integer factor before filtering. This makes it optimal for large spot sizes, above ≈20 pixels in diameter, at the cost of localization precision.
In our case, let us just use the '''Dog detector'''.