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The SWIFT BAT Software Guide Version 6.3 30 ... - HEASARC - Nasa

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D.2. <strong>BAT</strong>CELLDETECT 105<br />

D.2 <strong>BAT</strong>CELLDETECT<br />

D.2.1 NAME<br />

batcelldetect - perform source detection using the sliding cell method<br />

D.2.2 USAGE<br />

batcelldetect infile outfile snrthresh<br />

D.2.3 DESCRIPTION<br />

batcelldetect performs source detection on a sky image. <strong>The</strong> sliding cell method is used to locate<br />

regions of the image which are significantly different from the background.<br />

This tool is more appropriate for coded aperture imaging because: (1) it assumes Gaussian<br />

fluctuations, not Poissonian; (2) it measures the local background; and (3) it measures the local<br />

background standard deviation. A source is detected at a pixel if that pixel’s value exceeds the<br />

background by more than “snrthresh” times the background standard deviation. Users can increase<br />

the significance of a detection and reduce false detections by requiring more than one adjacent pixel<br />

exceed the threshold, using the “nadjpix” parameter. <strong>The</strong> “nullborder” and “bkgpcodethresh”<br />

parameters can also be used to exclude false positives near the edge of the image.<br />

<strong>The</strong> background value is estimated by using a sliding window. <strong>The</strong> shape of the window is<br />

either circular or square, and the radius (or half-width) is specified by the bkgradius parameter.<br />

In determining the background, a circular region at the center of the window is excluded, whose<br />

radius is the srcradius parameter. Thus, the background does not include contamination from the<br />

source region.<br />

In a single iteration, the sliding cell algorithm is less sensitive in a region around bright sources,<br />

because the background standard deviation becomes biased. To avoid this, the algorithm can be<br />

run in multiple iterations. After each iteration, the detected pixels are removed, and thus the bias<br />

can be significantly reduced.<br />

A second stage fits a point spread function to regions of the image where sources are detected.<br />

For new sources, this aids in refining the centroid of the source position, as well as in estimating<br />

uncertainties.<br />

<strong>The</strong> default output is a catalog list of detected sources, plus various statistics about them. <strong>The</strong><br />

output flux column is either COUNTS or RATE, depending on the input image units. <strong>The</strong> tool can<br />

optionally output the background map, the background fluctuation map, and a significance map.<br />

IMPORTANT NOTE: if the keepbadsources parameter is ‘YES’, then the output catalog<br />

may contain some sources which failed processing for one reason or another. Information on the<br />

success or failure on a source-by-source basis is recorded in the DETECT STATUS column.<br />

<strong>The</strong> user can also supply an input catalog. Sources in the input catalog, which are within the<br />

field of view of the image, are assumed to be fixed at their known positions, and fitted during

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