Underwater imaging without colour distortions requires RAW capture

Abstract Consumer cameras are not designed to be scientific instruments, yet they are increasingly used in science not just to see, but to measure. This is possible because camera sensors respond approximately linearly to the light they receive, a property that can, in principle, support quantitative measurements of colour. Whether that quantitative measurement potential is preserved depends on what happens to the image after capture. Minimally processed sensor images, commonly known as RAW, retain the approximately linear response needed. Instead of RAW, however, the default output of most cameras is a heavily processed image optimized for visual appearance, compact storage and immediate use, typically saved as a JPEG file. The convenience offered by an in‐camera processed image comes at a scientific cost. RAW capture requires more storage and processing effort but leaves calibration choices open. Processed images reduce those demands at acquisition and in post‐processing but transfer irreversible decisions about colour manipulation from the researcher to the camera. The preservation of RAW sensor data is necessary but not sufficient for quantitative colour measurement. Pixel values must also be calibrated to account for the light conditions under which the image was acquired. Underwater, this calibration is more challenging than in clear air, because light is absorbed and scattered as it travels through water, resulting in effects that depend on both wavelength and distance. Consequently, colour distortions vary across the scene and generally cannot be corrected with a single global colour transformation like white balancing; instead, calibration requires information about the imaging distance. We explain the consequences for quantitative imaging and introduce the 3P Protocol for distortion‐free colour imaging underwater: Preserve RAW sensor data, place a known colour reference in the scene and plan acquisition to control or measure imaging distance. Calibration and reconstruction methods will evolve but cannot recover information discarded at acquisition. Preserving the measurement today keeps image datasets open to the questions and methods of tomorrow.