image.decompose - Function

Separate a complex image into individual components

Synopsis
decompose(region, mask, simple, threshold, ncontour, minrange, naxis, fit, maxrms, maxretry, maxiter, convcriteria)

Arguments

region	in
		Allowed:	Region tool
		Default:	unset
mask	in
		Allowed:	Boolean LEL expression or mask region
		Default:	unset
simple	in	Skip contour deblending and scan for local maxima
		Allowed:	T or F
		Default:	F
threshold	in	Value of minimum contour
		Allowed:	Positive Float
		Default:	unset
ncontour	in	Number of contours to use in deblending
		Allowed:	Int of 2 or greater
		Default:	11
minrange	in	Minimum number of closed contours in a component
		Allowed:	Positive Integer
		Default:	1
naxis	in	Max number of perpendicular steps between contiguous pixels
		Allowed:	1, 2, or 3
		Default:	2
fit	in	Fit to the components after deblending?
		Allowed:	T or F
		Default:	T
maxrms	in	Maximum RMS of fit residuals to not retry fit
		Allowed:	Positive Float
		Default:	unset
maxretry	in	Maximum number of times to retry the fit
		Allowed:	Non-negative Integer
		Default:	unset
maxiter	in	Maximum number of iterations allowed in a single fit
		Allowed:	Positive Integer
		Default:	256
convcriteria	in	Criterion to establish convergence
		Allowed:	Positive Float
		Default:	0.0001

Returns
Nothing useful yet - component list is printed to screen

Description
The function decompose is an image decomposition tool that performs several tasks, with the end result being that a strongly blended image is separated into components - both in the sense that it determines the parameters for each parameter (assuming a Gaussian model) and that is physically assigns each pixel in the image to an individual object. The products of these two operations are called the component list and the component map, respectively. The fitting process (which determines the component list) and the pixel-decomposition process (which determines the component map) are designed to work cooperatively to increase the efficiency and accuracy of both. The algorithm between the decomposition is based on the function clfind described in Williams et al 1994, which uses a contouring procedure whereby a closed contour designates a separate component. The program first separates the image into clearly distint 'regions' of blended emission, then contours each region to determine the areas constituting each component and passes this information on to the fitter, which determines the component list.

The contour deblending can optionally be replaced with a simpler local maximum scan, and the fitting can be replaced with a moment-based estimation method to speed up calculations on very large images or if either primary method causes trouble, but in general this will impede the accuracy of the fit.

The function works with both two and three dimensional images.

Example

- im := imagemaketestimage()
- im.decompose(threshold=2.5, maxrms=1.0)

Next: image.deconvolvecomponentlist - Function Up: image - Tool Previous: image.coordmeasures - Function Contents Index

	Package	general
	Module	images
	Tool	image