Phone automation during image capture and storage degrades feature and color information.

A High-contrast image of an array of 20 µm diameter pinholes in chrome taken with an iPhone 4 and 20×/0.40 NA objective. B Phone auto-focus changes effective magnification for samples held at different distances from the objective lens, resulting in changes to apparent feature size. C Saturation in individual color channels due to auto-exposure and gain causes loss of color contrast in sparse, bright samples. D Built-in white-balance of the iPhone 4 is insufficient to overcome variable illumination conditions, resulting in a shift of the apparent color profile of samples such as this blood smear, as quantified in E and F for a region of interest illuminated with a white LED or halogen lamp, respectively. G Sharpening algorithms cause patterns of artificial ringing and haloing around high contrast structures such as this chrome-on-glass resolution target. H Intensity profiles at edges show phone-specific deviations from the expected theoretical monotonic profile obtained from an incoherently illuminated sample using a scientific camera and no image processing. The measured profiles are normalized, with 0 corresponding to the intensity in chrome far from an edge and 1 corresponding to the intensity in a clear region far from an edge.