ESFotoClix Blog

By now you probably have tinkered with your DSLRs histogram to validate the correctness of your exposures (if not, see the references at the end of this blog entry), and you understand what pushes a histogram to the left or right. It’s the exposure, right? If you have set your camera shutter speed, aperture and ISO correctly, or applied the right metering and exposure compensation, you will capture the right amount of light, and your histogram will be a beautifully centered, non-clipping mound. Right?

As it turns out, though photography is indeed about capturing the light, it turns out other related factors drive your histogram. Even if you shoot RAW, the histogram your camera displays belongs to the thumbnail JPG it produces — not the actual RAW data. You may see clipping, but is the RAW data really clipped? To answer this, we need to understand that the R,G,B histogram is driven by color settings on your camera — how it interprets and converts the RAW data into a final JPG file, or the JPG thumbnail included in the RAW file (NEF for Nikon DSLRs).

This brings us to 4 in-camera settings that affect color rendition, and hence, histogram distribution: White Balance (WB), Sharpness(!), Saturation, and the effective tone curve. In a Nikon D90 and other cameras with equivalent features, the last two are encapsulated in a Picture Control. In a D80, equivalent settings are achieved through the Picture Mode settings. Let’s take each of these in turn, using ViewNX for ease of demonstration, to show how they push and pull your histogram.

First, let’s take a look at the following sample shot, with the in-camera settings intact. As you can see, its histogram may not be the typical “perfect, centered hump” I referenced above, but we see no clipping of highlights, so we’re very happy.

Now, let’s suppose you had applied some really extreme sharpening in-camera. We’ll emulate it here in ViewNX, but something very similar would happen in the JPG’s histogram you would see in the camera’s LCD. As you can see, you would see some clipping in the reds and greens — not because suddenly the scene got brighter, or because Matrix metering blew the exposure, or because you erroneously set the shutter speed one click too slow. All that changed here was sharpening.

Next let’s suppose that instead, you shot the photo with the Vivid Picture control. Again, we see clipping, but this time in the blues. Would you blame Matrix metering, try to apply negative compensation, or beat yourself up for having the blinkies? But again, nothing changed in either the exposure or the scene. Only what the camera is doing to the image has changed.

Now let’s play with White Balance. Taking the Vivid shot, let’s warm up the White Balance to 5800K from the default 5200K for Direct sunlight. As we would expect, the blues recede from the highlights, the reds advance toward the highlights, and we get a better behaved histogram that though still clipping in the highlights (now for the reds), does so minimally and for most practical purpuses, acceptably.

Finally, let’s show what could happen if we take a photo with the wrong White Balance. Going back to the original as-shot photo, let’s suppose we mistakenly used a left-over temperature setting for a previous photo we took earlier in the day (I know this happens to no one but me, but play along for a second). That temperature setting, around 4100 K is too cool for this particular scene, so, sure enough, we get accentuated blues that clip in the highlights.

That’s all very interesting, you may say, but what conclusions can you draw for practical application? Here’s a few suggested take-aways:

1) When judging exposure in-camera, keep in mind that the camera’s color and sharpening settings are influencing the histogram you are reviewing.

2) Setting the right White Balance, or getting as close to “real” as possible in the field is essential if you want to ensure proper exposure. Even if you subscribe to the “I will fix it in PP” strategy for WB, keep in mind that if you get the wrong exposure because the WB you had in the field led you astray, you may get good White Balance in post-processing, but you may not achieve a well exposed image.

3) Even when shooting RAW, if you intend to apply a given Picture Control in post-processing, it is very useful to have that same Picture Control in the camera at the time you shoot and review the histogram so that you can accurately evaluate the exposure.

4) The effects of in-camera sharpening are not as pronounced, but do play a role, and in conjunction with the right/wrong Picture Control or WB setting may also lead you astray. Even if you sharpen in Post-processing with Unsharp Mask, keep in mind that it will shift the histogram. Depending on the situation, you may need to give yourself some headroom to avoid clipping.

5) Finally, if you play with colors in post-processing, such as hue or saturation changes, you may also need to give yourself some headroom to avoid clipping in the final post-processed image.

References for further reading:
Understanding Digital Camera Histograms: Tones and Contrast
Understanding Digital Camera Histograms: Luminance and Color

After our previous discussion on how to employ Spot-metering in the quest for that perfect exposure, someone pointed how, though the Spot-metered image avoids over-exposure in the highlights, the shadow areas are much too dark. Maybe something else is needed. ADL, perhaps? Perhaps, or else we can open the RAW file in ViewNX and apply negative exposure compensation plus shadow protection on the over-exposed file? To demonstrate, here’s the exposure that Matrix Metering rendered 2/3-stops (+0.7EV) above the Spot-metered reading.

Now let’s see what happens to this same RAW file if we apply -0.7EV plus shadow protection of 30. The white flag regains some of its detail, and so does the trunk of that palm tree in the background.

When we compare this against the Spot-metered version, we see similar exposure in the midtones and highlight areas, but the shadows are noticeably more detailed. As a refresher, here’s the Spot-metered version again — you know, the one that avoids over-exposure.

Hmm. Maybe over-exposure isn’t such a bad thing. For a full treatment of this subject, including the relationship of exposure to noise performance and a possible cure for over-exposure phobia, see this article.