title: Inherent bias in correlation averaged images.
abstract: The correlation averaging algorithm frequently used to enhance micrographs of repeating structures contains an inherent bias that favours images with larger pixel values or positive noise levels. This bias not only skews the composite image toward higher pixel values, but also distorts the image by increasing the value of high-valued pixels more than that of low-valued pixels. These errors are especially important in scanning probe microscopy images where the pixel value reflects a distinct height. A similar algorithm that uses a structure function in place of the correlation function eliminates this bias.
authors.affiliation: Department of Physics, University of California, Santa Barbara 93106, USA.
authors.forename: J T
authors.initials: JT
authors.lastname: Woodward
authors.forename: C
authors.initials: C
authors.lastname: Kono
authors.forename: L L
authors.initials: LL
authors.lastname: Madsen
authors.forename: J A
authors.initials: JA
authors.lastname: Zasadzinski
mesh_terms: D015982:Bias; D007091:Image Processing, Computer-Assisted; D018625:Microscopy, Atomic Force; D016252:Microscopy, Scanning Tunneling