Unlike artificial light sources, which can be calibrated to meet a desired luminous effect regardless of latitude, climate, or time of day, daylight is a dynamic light source, which produces variable shadow patterns and fluctuating levels of brightness. While we know that perceptual impacts of daylight such as contrast and temporal variability are important factors in architectural design, we are left with an imbalanced set of performance indicators – and few, if any, which address the positive visual and temporal qualities of daylight from an occupant point-of-view. If visual characteristics of daylight, such as contrast and spatial compositions, can be objectively measured, we can contribute to a more holistic analysis of daylit architecture with metrics that complement existing illumination and comfort-based performance criteria. Using image processing techniques, this paper will propose a proof-of-concept methodology for quantifying contrast-based visual effects within renderings of daylit architecture. Two new metrics will be proposed; Annual Spatial Contrast and Annual Luminance Variability. Using 56 time step instances (taken symmetrically from across the day and year) this paper will introduce a method for quantifying local contrast values within a set of rendered images and plot those instances over time to visualize hourly and seasonal fluctuations in contrast composition. Using the same 56 instances, this paper will also introduce a method for quantifying variations in luminance (brightness) between instances to measure fluctuations in brightness. This paper pre-validates each of the proposed methods by calculating annual spatial contrast and annual luminance variability across ten abstract digital models and comparing those results to the authors’ own intuitive ranking.