  Deep optical images are often crowded with overlapping objects. This is
especially true in the cores of galaxy clusters, where images of dozens of
galaxies may lie atop one another. Accurate measurements of cluster properties
require deblending algorithms designed to automatically extract a list of
individual objects and decide what fraction of the light in each pixel comes
from each object. We present new software called the Gradient And INterpolation
based deblender (GAIN) as a secondary deblender to improve deblending the
images of cluster cores. This software relies on using image intensity gradient
and using an image interpolation technique usually used to correct flawed
terrestrial digital images. We test this software on Dark Energy Survey coadd
images. GAIN helps extracting unbiased photometry measurement for blended
sources. It also helps improving detection completeness while introducing only
a modest amount of spurious detections. For example, when applied to deep
images simulated with high level of deblending difficulties, this software
improves detection completeness from 91% to 97% for sources above the 10?
limiting magnitude at 25.3 mag. We expect this software to be a useful tool for
cluster population measurements.
