vortexfit: Vortex transform.

In mlpeck/zernike: Zernike Polynomials and Fringe Analysis tools

Vortex transform.

Description

Fringe analysis by Vortex aka Spiral Quadrature transform.

Usage

vortexfit(
  imagedata,
  cp = NULL,
  filter = NULL,
  fw.o = 10,
  options = psfit_options()
)

Arguments

imagedata	matrix containing the interferogram data
cp	list with circle parameters describing interferogram location. Defaults to NULL
filter	size of filter to remove background
fw.o	size of gaussian blur to smooth orientation estimate
options	A list with general fitting and display options. See psfit_options().

Details

Implements the Vortex or spiral phase quadrature transform method of Larkin et al. (2001) https://doi.org/10.1364/JOSAA.18.001862 including the fringe orientation estimation approach in Larkin (2005) https://doi.org/10.1364/OPEX.13.008097. Thanks to Steve Koehler for ideas on implementation details.

Value

a list with wavefront estimates, wrapped phase, modulation, etc. The return has S3 class 'wf_zfit' with plot, print, summary, and report methods.

Warning

This routine is offered as is with no license, as it may be in violation of one or more US and international patents.

See Also

This is one of two routines provided for analysis of single interferograms, along with fftfit(). This may be suitable for interferograms with closed fringes.

Examples

require(zernike)
fpath <- file.path(find.package(package="zernike"), "psidata")
fname <- "Image197.jpg"
img <- load.images(file.path(fpath, fname))

# parameters for this run

source(file.path(fpath, "parameters.txt"))

# target SA coefficients for numerical null.

sa.t <- sconic(diam,roc,lambda=wavelength)
zopt <- psfit_options()
zopt$satarget <- sa.t

# display an interferogram

if (tolower(.Platform$OS.type) == "windows") windows() else x11()
image(1:nrow(img), 1:ncol(img), img, col=grey256, asp=1,
 xlab="X", ylab="Y", useRaster=TRUE)
mtext("Sample Interferogram")

if (tolower(.Platform$OS.type) == "windows") windows() else x11()
vfit <- vortexfit(img, filter=15, fw.o=10, options=zopt)

# do "classical FFT" based fit and compare results

dev.set(dev.next())
ftfit <- fftfit(img, cp=vfit$cp, sl=c(32, 0), filter=15, options=zopt)

plotn(ftfit, vfit, labels=c("fft", "vortex"))

mlpeck/zernike documentation built on Dec. 29, 2024, 7:41 p.m.