The ETTR Myth

Expose To The Right

ETTR is an acronym for Expose To The Right.   Some folks have promoted it as a replacement for traditional exposure metering.   The premise is that you can validate camera metering by simply reading the histogram in the camera’s preview window.

Unfortunately, it is based on some basic misunderstandings about digital photographic technology.   The first misunderstanding is the premise that each bit level in a digitally encoded image represents an exposure stop.   The second misunderstanding is the premise that all digital cameras capture light in a perfectly linear fashion.   The third misunderstanding is the premise that the histogram represents the raw image data captured by the camera.   I will briefly address each of these.

Any correlation between exposure stops and digital bit levels can only be accidental at best.   The total exposure range in a scene or an image is commonly known as the dynamic range.   The capture dynamic range of digital cameras is wider than most folks assumes and usually equal to or better than film or paper, but it is less than what can be encountered in nature.   It can be defined in terms of exposure stops, decibels, or tone density.   It is a function of the optics and sensor electronics in the camera.   The few cases where an accurate range is provided by the vendors, it varies from 8 to 12 f/stops, or 48 to 72 dB.

The image data is converted from analog measurements by the analog/digital (A/D) circuits early in the capture.   This can wind up as an 8-bit, 12-bit, 14-bit, or even 16-bit digital value depending on the camera and it’s user settings.   It is simply a number that has been digitized.   Any correlation between bits or bit depth and exposure levels is pure speculation, end of subject.

Second, the digital capture of light is not strictly linear.   It is true that the silicon sensor itself will capture light in a very linear fashion.   But this ignores reciprocity at the toe and heel of the extremes, the quantum efficiency of the substrate, heat, and most importantly it ignores the optical filters in front of the sensor.   If the color filter array were linear it would be impossible to reconstruct colors.   And these are not the only optical filters in your camera.

In addition to the effects of ISO settings, sensors are subject to ambient heat and heat buildup.   It is well known that long exposures can introduce noise and color shifts, even at low ISO settings.   So, the A/D circuits have gain controls based on the current ISO setting.   Most A/D circuits also include limited noise compensation based on the ISO setting and sometimes based on shutter settings (heat buildup).

Some A/D circuits perform additional compensation based on the color temperature of the ambient light.   The Nikon D2X is an example of this.   Many cameras are now designed specifically to support an extended range of highlights.   An early example of this was the Kodak Pro SLR/n with ERI (Extended Range Imaging).   The effect of this was that the raw values were slightly altered, but the JPG images included extra metadata that only the Kodak DCS software would see.   The point is that there are many steps in the pipeline that can introduce non-linearity.

If you capture an image of a gray scale chart that fits within the dynamic range of the camera, at the right exposure, you can create a linear graph of the raw data.   But if you underexpose or overexpose this same image, the graph will probably not be linear and it is unlikely that software will be able to restore true linearity.   End of subject.

Finally, the image in the preview window has been color rendered and re-sampled down to a small size.   This is the data shown in the histogram.   There is no practical way to map all of the raw data in an image into a histogram that you could use effectively in the preview window.   The camera can capture all colors in the spectrum, but the rendered image is limited to the gamut of an RGB color space.   So, in addition to exposure clipping the histogram will include gamut clipping.   This is also true for the blinking highlight and shadow tools.   They might imply an exposure problem when none exists.   Out of gamut colors will contain RGB values at zero and 255.

The photographic design point is, has been, and will continue to be based on the middle gray tone.   This is the basis of the sunny daylight f/16 rule.   It is the reference point for all exposure metering systems.   It is also ingrained into the CIE color matching functions and all color order systems.

That said, all electro-mechanical components have high and low design limits.   Approaching them is like driving on the shoulder of the road, inviting an accident.   But every rule has its exceptions.   They prove the rule.   Exposure metering is no different.   That is why we have the zone system and why so much has been written about photographic lighting techniques.   It does not mean that your meters are defective or obsolete.

The current frontier in digital technology is the goal to expand the dynamic range in our images.   This is true for cameras, monitors, projectors, papers, and inks.   ETTR is like measuring a roadbed with a micrometer.   But only sampling the shoulders. Unfortunately, the shoulders are where the hazards are.

If you typically shoot JPG format, the histogram will accurately represent the image data.   But clipping can still be from either gamut or exposure limits.   Adjusting exposure to compensate for gamut is not a good idea.   If you typically shoot RAW format, the camera’s histogram is based on an approximation of what the final rendered image might look like.   There is a significant amount of latitude provided by the RAW image editor.   This is probably why you are shooting RAW in the first place.

Histograms are good things

I am not saying that histograms are bad.   They are part of a wonderful toolkit of digital image processing tools.   I am saying ETTR is not a replacement for exposure metering.   If you understand what the tone and color range of the scene is, you can evaluate the histogram much better.   And if you master traditional photographic metering, you will capture it more accurately more often.

Here is a suggested procedure for intelligent use of the histogram in your camera.   First, start with traditional photographic exposure techniques.   Then review both the histogram and the blinking highlights and shadows in the preview window.

If you see highlights or shadows only in saturated color areas of the image, your exposure is probably just fine.   Shoot raw if you want to explore a larger color space for the image.   If you are shooting JPG, you can optionally try changing the contrast, saturation, or color spaces the camera offers.   In any case clipped colors will simply be at the gamut limit.   The risks are banding and blocking in color tones.

If the highlight and shadow clipping is all in black and white areas of the image, you need to evaluate the dynamic range of the scene and your image objectives.   This can indicate an exposure or contrast change.   If all of the clipping is from very small spectral reflections, you may not want to change anything.   Changing exposure enough to eliminate spectral highlights might ruin the rest of the image.   If you are shooting something critical like jewelry, these highlights might indicate you need to scrim (block) some of the light.   A backlit scene might indicate you need to add some fill flash.

If the histogram seems narrow (fails to reach the edges), you are probably shooting a low contrast scene.   Deal with it as such.   If this is intended as a low-key image, you may not want the histogram crowding the right at all.   A common technique with high-key photography is to add some light to the background.   You may want to add enough light to a white background to purposely push the highlights.   This is not new with digital.   Background lights have been in use for a long time.

After properly evaluating the scene and the image tools you can intelligently decide if you want to change exposure to preserve some particular range of the image tones.   Ansel Adams would have done this.   The digital revolution has also fostered exciting new tools.   The challenge to the consumers is to learn how to use them rationally and effectively.

I hope you enjoyed this article.   If you have any comments, or suggestions, I would welcome your input.   Please send me an  Email.   Read more about Linear Gamma and Linear Capture or Tones and Zones.

Rags Gardner
Rags Int., Inc.
204 Trailwood Drive
Euless, TX 76039
(817) 267-2554
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November 19, 2007

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