Index: trunk/psphot/src/psphotSignificanceImage.c
===================================================================
--- trunk/psphot/src/psphotSignificanceImage.c	(revision 21366)
+++ trunk/psphot/src/psphotSignificanceImage.c	(revision 21407)
@@ -72,38 +72,9 @@
     }
 
-    // We have an input image with PSF size sigma_r.  We have smoothed it with a kernel of size
-    // sigma_s.  The result is an image with PSF size sigma_o: sigma_o^2 = sigma_r^2 +
-    // sigma_s^2.  Ideally, we are choosing sigma_s = sigma_r, in which case sigma_o^2 = 2
-    // sigma_s^2.  If we do not know the input image PSF size (initial detection stage), then
-    // we are assuming that sigma_r = sigma_s.
-
-    // Build the significance image on top of smooth_im.  We need to correct the ratio im/wt by
-    // 2 factors: 1) the relationship the peak value and the integrated flux, and 2) the
-    // relationship between the per-pixel variance (var_i) and the total variance included in
-    // the flux measurement (effective area).  These latter correction comes from: flux = Io *
-    // 2\pi\sigma_o^2 and total variance = var_i * 4\pi\sigma_o^2, thus (S/N)^2 = flux^2 / var
-    // = (Io/var_i) \pi sigma_o^2
-
-    // in fact, because of the smoothing and the resulting correlated errors, the per-pixel
-    // variance is a bit smaller than the value predicted here.  The total variance should be
-    // \alpha 4\pi(\sigma_r_^2 + \sigma_s^2) where \alpha approaches 1 for \sigma_s / \sigma_r
-    // << 1, and \alpha approaches 0.5 for \sigma_s / \sigma_r >> 1, with a value of 0.7
-    // (actually 1/1.5) for \sigma_s = \sigma_r
-
-    // if the smoothing kernel size is known to be the psf size (\sigma_s = \sigma_r), then we
-    // can use the scaling factor of 1/1.5; otherwise, we want to be conservative and use \alpha
-    // = 0.5.  Thus, for the guess smoothing kernel, (S/N)^2 = 3.0 (Io/var_i) \pi sigma_s^2 for
-    // the guess case and (S/N)^2 = 2.0 (Io/var_i) \pi sigma_s^2 for the known case
-
-    // XXX hmm, somehow the simulations are coming up with 4pi, not 3pi (as if \alpha is 1/2.0,
-    // not 1/1.5 for sigma_s = sigma_r...
-
-    float factor = guess ? 4.0 * M_PI * PS_SQR(SIGMA_SMTH) : 4.0 * M_PI * PS_SQR(SIGMA_SMTH);
-
-    // Correct the correction factor for the covariance produced by the (potentially multiple) smoothing
+    // Calculate correction factor for the covariance produced by the (potentially multiple) smoothing
     psKernel *kernel = psImageSmoothKernel(SIGMA_SMTH, NSIGMA_SMTH); // Kernel used for smoothing
     psKernel *covar = psImageCovarianceCalculate(kernel, readout->covariance); // Covariance matrix
     psFree(kernel);
-    factor /= psImageCovarianceFactor(covar);
+    float factor = 1.0 / psImageCovarianceFactor(covar);
     psFree(covar);