detected in the first pass.

This technique works well to prevent spurious deblending by SExtractor in images in which there is significant substructure. However, when dealing with crowded fields (such as clusters of galaxies) the largest problem in catalog generation is excessive blending of sources, particularly in the central region. To remedy this, we use a modified version of this hot/cold technique. Our method consists of a primary SExtractor run to detect only the brightest objects. In a lensing field, especially in a lensing cluster, these bright objects will tend to be the lenses. Making use of the RMS maps generated during this SExtractor run, we mask out the bright objects by setting the pixel values to background noise, and thus simulate an emptier field.

We then run SExtractor on the masked image, using a much lower detection threshold, to create a catalog of background objects. Since shape estimation including both flexion and shear have a minimum of 10 degrees of freedom, we require at least 10 connected pixels above the detection threshold, though in reality, we are unlikely to be able to get a reliable measurement from an image with fewer than 15 included pixels. We then discard all 