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The Transiting Exoplanet Survey Satellite (TESS) will observe$\sim$150~million stars brighter than $T_{\rm mag} \approx 16$, withphotometric precision from 60~ppm to 3~percent, enabling an array of exoplanetand stellar astrophysics investigations.While light curves will be provided for$\sim$400,000 targets observed at 2-min cadence, observations of most starswill only be provided as full-frame images (FFIs) at 30~min cadence. The TESSimage scale of $\sim21$''/pix is highly susceptible to crowding, blending, andsource confusion, and the highly spatially variable point spread function (PSF)will challenge traditional techniques, such as aperture and Gaussian-kernel PSFphotometry. We use official "End-to-End~6" TESS simulated FFIs to demonstrate adifference image analysis pipeline, using a $\delta$-function kernel,thatachieves the mission specification noise floor of 60~ppm~hr$^{-1/2}$. We showthat the pipeline performance does not depend on position across the field, andonly $\sim$2\% of stars appear to exhibit residual systematics at the level of$\sim$5~ppt. We also demonstrate recoverability of planet transits, eclipsingbinaries, and other variables. We provide the pipeline as an open-source toolat https://github.com/ryanoelkers/DIA in both IDL and PYTHON. We intend toextract light curves for all point sources in the \textit{TESS} FFIs as soon asthey become publicly available, and will provide the light curves through theFiltergraph data visualization service. An example data portal based on thesimulated FFIs is available for inspection at https://filtergraph.com/tess_ffi.

Precision Light Curves from TESS Full-Frame Images: A Difference Imaging Approach