Implementation of camera systems in automotive applications continues to increase in number and to expand in functionality. From exterior surround view camera systems with multiple cameras and thermal imaging systems for night vision to in-cabin cameras for driver and passenger monitoring, improving image quality remains an important element to achieving optimal performance and functionality. Automobiles operate in countless types of illumination and environmental conditions, which necessitates numerous fundamental assessment protocols to consider when measuring and optimizing image quality for such aspects as ADAS and autonomous vehicle performance. This talk will provide insights into image quality methodologies and considerations for benchmarking visible and IR camera systems relevant to the automotive industry. Measurements of image quality factors including dynamic range, stray light, and sharpness will be described with regard to the differentiations between image quality improvements for machine vision purposes versus human vision interpretation.