Controlled illumination is a powerful tool for solving scene recognition problems. Binary and high frequency illumination primitives are projected into the scene to spatially encode or probe the optical environment. Recently, computer vision researchers have shown that orthogonal functions and computational techniques from the signal processing framework can be mapped directly into the scene using projector-camera systems. These scene-space signal processing algorithms are achieved with illumination-encoded functions as primitives and computations derived from surface reflection models. Some examples of this new optical approach include convolution filtering and aliasing-canceling filterbanks. In this paper we present a digital projector calibration method and an orthographic light field system. The calibrated system produces a light field structure matching the usual sampling geometry of image processing, well-suited to scene-space algorithms. The result is superior filtering and resolution performance due to higher accuracy optical representation. We evaluate our results by comparing processor-based filtering with a scene-space algorithm.