Tone mapping

Tone mapping is a technique used in image processing and computer graphics to map one set of colors to another to approximate the appearance of high-dynamic-range images in a medium that has a more limited dynamic range. Print-outs, CRT or LCD monitors, and projectors all have a limited dynamic range that is inadequate to reproduce the full range of light intensities present in natural scenes. Tone mapping addresses the problem of strong contrast reduction from the scene radiance to the displayable range while preserving the image details and color appearance important to appreciate the original scene content.

Inverse tone mapping is the inverse technique that allows to expand the luminance range, mapping a low dynamic range image into a higher dynamic range image.[1] It is notably used to upscale SDR videos to HDR videos.[2]

The introduction of film-based photography created issues since capturing the enormous dynamic range of lighting from the real world on a chemically limited negative was very difficult. Early film developers attempted to remedy this issue by designing the film stocks and the print development systems that gave a desired S-shaped tone curve with slightly enhanced contrast (about 15%) in the middle range and gradually compressed highlights and shadows [1]. The advent of the Zone System, which bases exposure on the desired shadow tones along with varying the length of time spent in the chemical developer (thus controlling highlight tones) extended the tonal range of black and white (and later, color) negative film from its native range of about seven stops to about ten. Photographers have also used dodging and burning to overcome the limitations of the print process [2].

The advent of digital photography gave hope for better solutions to this problem. One of the earliest algorithms employed by Land and McCann in 1971 was Retinex, inspired by theories of lightness perception [3].This method is inspired by the eye’s biological mechanisms of adaptation when lighting conditions are an issue. Gamut mapping algorithms were also extensively studied in the context of color printing. Computational models such as CIECAM02 or iCAM were used to predict color appearance. Despite this, if algorithms could not sufficiently map tones and colors, a skilled artist was still needed, as is the case with cinematographic movie post-processing.

Computer graphic techniques capable of rendering high-contrast scenes shifted the focus from color to luminance as the main limiting factor of display devices. Several tone mapping operators were developed to map high dynamic range (HDR) images to standard displays. More recently, this work has branched away from utilizing luminance to extend image contrast and towards other methods such as user-assisted image reproduction. Currently, image reproduction has shifted towards display-driven solutions since displays now possess advanced image processing algorithms that help adapt rendering of the image to viewing conditions, save power, up-scale color gamut and dynamic range.

The goals of tone mapping can be differently stated depending on the particular application. In some cases producing just aesthetically pleasing images is the main goal, while other applications might emphasize reproducing as many image details as possible, or maximizing the image contrast. The goal in realistic rendering applications might be to obtain a perceptual match between a real scene and a displayed image even though the display device is not able to reproduce the full range of luminance values.

Tone mapped high-dynamic-range (HDR) image of St. Kentigerns Roman Catholic Church in Blackpool, Lancashire, England, UK
Tone mapped HDR image of Dundas Square; Tone mapping was done as post-processing technique, using Photomatix photographic software.
Tone mapped High dynamic range image example showing stained glass windows in south alcove of Old St Paul's, Wellington, New Zealand.
The six individual exposures used to create the previous image. In the low exposure images, the room is dark and unclear, but the details of the windows are visible. In the high exposure images, the windows are bright and unclear, but the details of the room are revealed.