Name

scfnpl - calculate the normalized self-correlation function of an image using padding with zeroes, multiplication in Fourier space, and normalization of the result by the actual number of pixels used for calculating the ccf coefficients.

Usage

Input

image
input image (real)
center
if set to True (default), the origin of the result is at the center; if set to False, the origin is at (0,0), the option is much faster, but the result is difficult to use

Output

output
self-correlation function of the input image. Real. The origin of the self-correlation function (term ccf(0,0,0)) is located at (int[n/2], int[n/2], int[n/2]) in 3D, (int[n/2], int[n/2]) in 2D, and at int[n/2] in 1D.

Method

Reference

van Heel, M., Schatz, M., Orlova, E., 1992. Correlation functions revisited. Ultramicroscopy 46, 307-316.

Author / Maintainer

Pawel A. Penczek

Keywords

category 1
FUNDAMENTALS
category 2
FOURIER

Files

fundamentals.py

Maturity

stable
works for most people, has been tested; test cases/examples available.

Bugs

None. It is perfect.

scfnpl (last edited 2013-07-01 13:12:42 by localhost)