Read the full white paper (PDF)
White paper by Norman Koren (Imatest LLC) — May 29, 2026
Overview
This white paper is a concise, practical guide to camera image quality testing — with an emphasis on machine vision — built around metrics derived from information theory, which predict real-world camera performance better than traditional metrics such as sharpness (MTF) or noise alone.
It introduces Information Capacity (C) as the key performance metric, derived from sharpness, noise, and signal amplitude, and C4, the information capacity measured directly from 4:1-contrast slanted edges (the maximum information per pixel for an object with 4:1 contrast). From C4 and object size it develops the ideal-observer signal-to-noise ratio (SNRi) and Object Detection Error Probability (ODEP), and presents the new Information-based Dynamic Range (InfoDR) test chart and its plot of C4 versus illumination for characterizing camera performance across a wide range of light levels, including low light and dynamic range.
Along the way it reviews the underlying imaging concepts (raw conversion and demosaicing, gamma and tonal response, color spaces, MTF/SFR and slanted-edge charts, noise, and lighting), walks through spatial (slanted-edge) and tonal camera characterization with the relevant Imatest charts — including the 36-patch Dynamic Range (DR36), Contrast Resolution, and InfoDR charts — and covers the Photon Transfer Curve and the Simatest camera/ISP simulator.
It closes with color, uniformity (light falloff) and defect (blemish) measurements, and a discussion of problematic images and misleading results, including obsolete test charts, oversharpening, bilateral filtering and texture loss, and tone mapping.