Your camera’s histogram display can be used to help you deal with subjects outside the sensor’s normal responses.
This article follows on from our feature on using the histogram display to ensure correct exposures. Here we’ll take a closer look at what histograms can reveal about the tones and colours in images and how they can be used to calibrate exposures so you end up with the correct balance of tones and image colours.
First we’ll look at tonal distribution and how it is reflected in the brightness histogram. As outlined previously, a histogram shows the density of pixels at each level in the 0 to 255 range for a JPEG file. (Raw files are not used for histogram data.)
When a shot is correctly exposed, the histogram should fall within the 0 to 255 range. The displayed graph will show peaks in areas where there are a lot of pixels and troughs where the pixel ‘density’ is relatively low. Depending on the tonal balance, the graphs can look quite different, as shown in the illustration on this page.
Two images that are correctly exposed but have different tonal balances. In the top image, the graph peaks near the middle of the range, with a slight bias toward darker tones. This image would require minimal post-capture editing. With the low-contrast scene below it, there’s a peak near the highlights end, which reflects the large area of sky. The lower and wider peak towards the shadow end results from the band of trees and bushes across the middle of the scene.
It’s easy to be tricked by a brightness histogram if the image appears to have been correctly exposed when you check it on the monitor screen. When following the ETTR (expose to the right) rule, it pays to check the overall tonal balance and make sure highlights don’t get blown out. That can be tricky, as shown in the second illustration in which blown-out highlights are circled in red.
This shot is an example of what can happen when the ETTR rule is followed slavishly in a predominantly light-toned subject. The histogram is biased towards the right hand end of the histogram, indicating a general lightness in the overall tonal range. However, the white line along the right hand edge indicates the brightest areas contain pixels where no detail is recorded. Interestingly, even in an 8-bit JPEG, the histogram shows room for expansion into the shadow area at the left hand end indicating the overall brightness range was within the sensor’s tonal capacity.
Some photographers who make extensive use of ETTR rely on post-capture editing where editing software is used to bring out shadow details. The assumption is that as long as you’ve recorded detail in the highlights, the shadows can take care of themselves. There are several ways to bring out shadow details, among them use of the Levels and Curves adjustments, black point adjustments or tweaking the mid-range in the exposure scale while pulling down the highlights slider. How well they work depends on the amount of data recorded and its tonal range.
The latest sensors may provide ‘exploitable’ shadow detail in shots with normal brightness ranges, but it can be risky. Suppose we now look at an image with a wider brightness range. Metering the scene in multi-pattern mode takes in the entire frame and aims to record a balance between highlights and shadows. The histogram indicates the highlights are, once again, blown out. This time the histogram shows there’s a little room to bring up shadow detail.
The top picture shows the JPEG image with its histogram indicating potential clipping at both ends of the brightness range. Below it is a frame grab from the raw file recorded simultaneously, showing it open in Adobe Camera Raw, our preferred raw file processor. The bottom image shows how these adjustments are reflected in the resulting image.
Being able to pull up the shadows to obtain a usable image depends on the data being recorded. The picture on page above shows a scene with a brightness range that exceeds the sensor’s capabilities. Both highlights and shadows are clipped, as shown.
Clipped highlights and shadows can be seen in the brightness histogram for this shot, which has a wider brightness range than the sensor can record in a JPEG file.
Some photographers might think that recording this scene as a raw file could provide enough data, at least in the shadows to even out the brightness range, as long as the highlights aren’t clipped. Nevertheless, there’s a risk of noise showing up in the deepest shadows, so it’s not an ideal solution. Noise-affected shadows will stand out against the normally smooth appearance of the rest of the picture.
A better solution in such cases is to shoot HDR pairs and combine them with editing software. Many cameras can do this automatically, although most will record a large number of shots before combining them to produce a JPEG image.
A better alternative – which requires much less recorded data and can yield a high-quality TIFF file – is to take two shots in your camera’s raw format, adjusting the exposure to record details at each end of the tonal scale. With all but the widest brightness ranges, this should be possible with two exposures that encompass a brightness range from -2 to +2EV (four stops).
Start by exposing to the right, checking the histogram to ensure highlights are not clipped. Then expose to the left (ETTL), again checking there’s no clipping in the shadows. You should end up with a pair of shots that look like those shown in the illustration below.
Separate shots that capture highlight and shadow details can be combined in most image editor to preserve details at both ends of the tonal scale.
You may need a third exposure if you have to adjust the exposure value by more than four stops between the ETTR and ETTL exposures. For a wider range, a third exposure at the metered value (using multi-pattern metering) should help with the blend.
Using RGB histograms
While brightness histograms can be useful for determining exposure levels, they’re not much use if you want to identify anomalies in colour reproduction. RGB histograms will show you three separate histograms, one each for the R, G and B channels, often with an additional brightness histogram.
RGB histograms display separate graphs for the red, green and blue channels as well as a brightness histogram representing a combination of all three colour channels.
Some cameras use only the green channel when producing the brightness histogram display. The justification is that green represents the mid-point in the visible spectrum so, if that channel is correctly exposed, the red and blue channels should fall into line.
You can check whether that’s the case with your camera by opening an image in Photoshop and using the Levels control to display the histogram. Compare the RGB graph to the green channel graph; if they match, the camera ignores the red and blue channels. Do this with a couple of different images to confirm (or refute) your initial findings.
Close similarities between the RGB and green histograms suggest this camera takes most of the data for its brightness histogram from the green channel.
This strategy can be problematic because any colour other than green can be overexposed and you wouldn’t know about it if you relied solely on the brightness histogram. That means you could end up with an unwanted colour cast.
At the same time, you need to be able to recognise when a colour cast could be desirable so you don’t remove it inadvertently. For example, the warm cast of sunset shots is desirable; so desirable that the in-camera filter modes actually add it to the designated shot.
The red channel shows the shift to the right that characterises a colour cast. The thin line rising up the right hand edge indicates over-saturation in the red channel as well as some highlight and shadow clipping in the RGB histogram.
RGB histograms also provide a quick way to check white balance before you shoot by pointing the camera at a neutral grey card (or similar flat surface). If the graphs all peak in the same place, the colour balance is neutral. If any channel peaks too far to the right it indicates a colour cast.
Article by Margaret Brown – see Margaret’s photography pocket guides
