Exposing to the Right

Old Stone Bridge, Ashuelot River, Keene New Hampshire

Getting Exposure Right in the Digital Camera

Last week I began the discussion of exposure control in digital photography and more specifically about the use of the histogram to nail the optimal exposure every time. Much of that discussion focused on the importance of adjusting exposure to avoid the extremes. To avoid overexposure, positioning the histogram against the right side and clipping the highlights or underexposure, pushing the histogram against the left side and loosing detail in the shadows, but there is more to optimal exposure than avoiding the extremes.


Technically if the histogram is safely enclosed within the graph without piling up on the right or left then you might expect that the  Goldilocks Rule would apply, since it is neither too bright or too dark and all tonal levels are recorded. But unlike Goldilocks, every position within the graph is not “just right”. It is here that the “Expose To The Right” (ETTR) rule applies.
 

ETTR
Exposing to the right is an approach designed to get the most from the digital sensor in terms of tonal range, noise reduction and color quality. In practice it means slightly overexposing images, shifting the histogram to the right where digital light sensors work more efficiently.

The Physics
Digital image sensors are linear devices that translate the incident light into an electrical signal which is directly proportional to the intensity of the light. The greater the light, the greater is the portion of the sensor's tonal range that is dedicated to that part of the image.

Low Contrast : Histogram in the Middle

But f stops are not linear, but logarithmic. Every time you drop by one stop you are cutting the light in half and, remarkably, what this means is that the brightest stop on a digital sensor uses one half of the total tonal information. The next stop down gets only one half of what is left and so on until the darkest tones are recorded with a much smaller amount of tonal information. The result is that dark regions are much more susceptible to noise, loss of detail, and posterization in post processing. Digital sensor noise is actually higher in the bright tones, but since there is so much more information (signal) at this end of the range, the high signal to noise ratio (S/N ratio) obscures any noise. Noise can be significantly more intrusive at the dark end of the range, where the smaller signal is susceptible to being overpowered by the noise.

Anytime I start talking about the interaction between linear and

Exposure Right Shifted, ETTR, Not Pretty

logarithmic scales, I know I am in trouble, so let's get to the simple, practical application. Since there is more tonal information available at the bright (right) end of the scale, by increasing the exposure, the darker regions are moved into a portion of the scale that can better record detail with a more favorable S/N ratio. Again the resulting image on the LCD will not be the most attractive, but it will give you the highest quality information to take home to your editing software. This is a real test of your ability to trust the histogram and I have struggled to avoid the natural tendency to "improve" the resulting overbright, washed out image by lowering the exposure to get the prettiest LCD rendering.

An Example

Left Shifted Exposure

Exposed toward Right

 






As an example, here are two exposures taken of the classic old stone bridge in Keene New Hampshire. The first was underexposed, but looked better on the LCD screen. The dark tones are recorded on the far left of the histogram. The second was "exposed to the right", appearing overexposed and washed out on the screen, but the histogram showed that the dark tones were shifted to the right, on a more favorable portion of the scale, and that the highlights were not clipped. The two images looked very different on the LCD screen, but I then processed each in Camera Raw and Photoshop to get the best results. The two images were adjusted to look grossly the same, but examination of the detail, especially in the shadows, shows that the brighter image has smoother tonal range and less noise. ETTR does work!

Detail Comparis

A Few Caveats for ETTR:

First, to get the tonal benefits from ETTR, images must be shot in RAW, with the proper brightness brought back in the RAW converter. In addition to having a much smaller native tonal range (only 256 at 8 bits), JPG images are processed in camera. Their tonal range is "baked in" before the picture ever reaches the computer, leaving little margin for salvaging the over exposed images.

Secondly , as you increase the exposure it is important to avoid going too far, clipping or blowing out the important highlight tones. As I discussed last week, you must trust the histogram and avoid piling up against the right side. Most cameras have an additional visual aid to help avoid clipping. The "blinkys", the flashing lights on the LCD image are there to identify areas of blown highlights. Annoying but very helpful.

Finally, although ETTR has become the conventional wisdom for digital exposure, there is still some controversy about it's value. No surprise, we are photographers, we must debate! Digital sensors are constantly changing and improving. Only experimentation will tell you how valuable this technique will be for you.

So give ETTR a try. The biggest hurtle is to get over the strong desire to make the LCD image look it's best, but here again, in the digital world, getting it right IN the camera means something different than getting it looking it's best directly FROM the camera.

Check out Part One of Getting Exposure Right in the Digital Camera