Histogram Pt 1.pdf - Photography Monthly

[Technique]
Helpful
histograms
Part one: If your DSLR offers histograms, there’s no excuse for
taking a duff exposure. Ian Farrell explains how they work and
why they’re your greatest ally in the search for perfect pictures
When you shoot a digital
photograph, how do you tell if the
result is properly exposed or not?
You probably look at the image
on your camera’s viewing screen.
While this can tell you if your subject had their
eyes closed, or whether you composed the shot
properly, it’s not actually a very good way of
assessing exposure.
Camera viewing screens are crude devices, of
lower quality than the average computer monitor.
Look at a picture on the screen in bright sunlight
and it can look too dark; look at the same image
in dim light and it can appear too light. Thankfully,
there’s a far more accurate means of assessing
exposure in-camera: using the histogram.
Although it looks a bit complicated, a histogram
is actually a very easy way of telling, at a glance, if
you have a properly exposed picture or not, and –
most importantly – whether there are any blown
highlights or clipped shadows. Almost all cameras
can show one, and it’s good practice to get into
the habit of looking at yours regularly.
Put simply, a histogram is a graph showing how
brightness is distributed within an image. To make
one, your camera looks at the various brightness
levels in a photograph and assigns each one a
numerical value from 0 to 255, with absolute black
being 0 and pure white being 255. It then plots on
a bar chart how many pixels of each brightness
level are in the picture: pure black on the left, pure
white on the right, with all the other values ranged
in between. The shape of this graph can be
likened to the unique ‘fingerprint’ of a scene,
allowing you to tell whether your
picture is well exposed or not.
Let’s consider an average scene
containing a broad range of tones. If
this is photographed with the correct
aperture and shutter speed settings
then the resulting histogram will have
information distributed broadly across it,
perhaps with a peak in the middle. If it’s
underexposed, the peak will shift left
towards the darker end of the scale (towards 0,
pure black), indicating an overall darkening of the
picture. You may also see a bunching up of the
histogram on the exteme left, and a gap on the
right-hand side indicating a lack of light tones.
On the other hand, if the scene is overexposed,
you’ll see a histogram biased towards the right of
the graph, possibly running off the bright end of
the scale (past 255, pure white), with no
information at the dark end.
“
Make a habit of looking at the
histogram, be a better photographer
”
This is, in simple terms, how a histogram can
tell you if a scene is correctly exposed. In reality a
histogram is only useful if it’s viewed in the
context of the photograph you’re taking: you have
to use a bit of common sense.
Instead of an average subject, let’s say we’re
photographing something low-key (dominated by
dark and black tones). A black cat in a coal cellar
would be a good example. The correctly exposed
result here would be any photograph where the
majority of pixels were dark, so you would expect
to see a histogram biased towards the left-hand
side of the scale. If the peak was in the middle
then you’d see a grey cat in a grey coal cellar.
HIGH-KEY HISTOGRAM
ABOVE In an image comprising light,
white tones such as this high-key
gerbera picture, your histogram will
peak towards the right-hand side of
the graph. You can safely expect the
white backdrop to correctly record
as a ‘blown’ highlight.
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[Technique]
HIGHLIGHTS & SHADOWS
SHADOWS
Darker tones – solid
black and shadows
– are represented in
this area of the
histogram. Absolute
black (brightness
value 0) will show
no detail, whereas
single digital tones
will retain some.
MID-TONES
The majority of the average image will consist of brightness in the
middle part of the histogram, therefore it’s not uncommon for there
to be several peaks in this area.
HIGHLIGHTS
Bright parts of a
photo correspond to
information at this
end of the
histogram. Be
warned that
information beyond
this point (255),
blown highlights,
can’t be recovered.
This can sometimes happen, even with today’s
modern autoexposure systems. Likewise, if you’re
shooting something high-key (ie. an image
dominated by whites and light tones) you’d expect
to see a histogram shifted to the right-hand side
as an indication of correct exposure.
Clipping and dynamic range
As well as telling you about the tones in an
image, a histogram can also provide information
about what’s missing. If you’ve ever shot a
landscape photograph only to find the sky
registering as completely white, then you have
recorded what is usually known as a ‘blown’ or
‘clipped’ highlight – a part of the picture that’s so
bright that its assigned value in the histogram
goes beyond 255.
Highlights of this type lie out of range of the
sensor’s sensitivity, so to record any detail you’d
have to reduce the exposure. If you aren’t sure
whether you’ve clipped a highlight or not, take a
look at the histogram on the camera’s LCD. If you
see the information running off the right end of
the scale then you can rescue these overexposed
areas by dialling in some negative exposure
compensation on your camera and re-shooting.
Similarly, black, featureless areas – ‘clipped
shadows’ – can be identified by the histogram
crashing off the left-hand side of the scale. If you
see this, a spot of positive exposure compensation
will help bring things back into range.
It’s not always this simple though; often
applying negative exposure compensation to
rescue highlights means that shadows then
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[Technique]
COMBINED IMAGE
TWO ORIGINAL EXPOSURES
ABOVE Sometimes the range of contrast in a scene is too great for your sensor to record
without clipping shadows or highlights. In this situation, take two pictures – one under-, the
other overexposed, and combine them using High Dynamic Range software.
become underexposed, and vice versa. There’s
also that awful situation, usually found in highcontrast
situations, where both the highlights and
shadows are featureless, and the histogram
information pours off both ends of the scale. In
this case you’re struggling with a dynamic-range
problem where the contrast in the scene is
greater than the number of brightness levels your
camera can record in one go. In photographic
terms this is about five or six stops; if a scene has
more contrast than this, then you’re in trouble.
Incidentally, the human eye can see around 20
stops of dynamic range, which is why it’s hard to
spot this problem before you take the shot.
Solving this dynamic-range problem is not easy.
If the amount of shadow and highlight clipping is
relatively small, engage your camera’s dynamicrange
expansion feature, if it has it. (Nikon call this
feature D-Lighting; Canon, Highlight Priority; Sony,
Dynamic Range Optimisation). Here the camera
will compress brightness levels outside the 0-255
range so they fit within the range of the
histogram. If this doesn’t work, try taking the shot
three times, at exposure compensations of -2, 0
and +2. You can then combine these frames using
High Dynamic Range software, such as
Photomatix or Adobe Photoshop.
So: reviewing your histograms in-camera can
help detect exposure problems, such as under- or
overexposure, highlight or shadow clipping or
dynamic range issues. Sadly, it won’t correct these
problems for you, but it will alert you to them,
which is half the battle. Find out how to show the
histogram display on your camera (consult your
DSLR’s user manual) and make sure that looking
at it becomes habit. You’ll become a better
photographer as a result. ■
NEXT MONTH: Fixing exposures and using
histograms in Photoshop while editing your images.
KNOW-HOW
Histograms
for RGB
So far we’ve only encountered
histograms that show ‘brightness
levels’, which are really an
amalgamation of all three colour
channels: red, green and blue (RGB).
In black & white images these levels
equate to shades of grey. In colour
photography, though, many cameras
now give the option of showing
histograms for the individual red,
green and blue channels.
Individual colour channel
histograms can be useful for showing
which colour is responsible for a
blown highlight or clipped shadow, as
ABOVE The red, green and blue graphs here show highlights and shadows in a colour image.
well as for confirming that colour
balance is accurate. Take a picture of
a grey card and you’ll see a sharp
peak in the normal histogram
corresponding to this one brightness
level. Switch over to the three-colour
RGB histogram and you should see
the three graphs aligned neatly over
the top of each other exactly – if
your camera’s white-balance is OK.
For coloured areas (such as the
sky) one colour may be separated
from the other two (the blue
histogram, in this example).
LOW-KEY HISTOGRAM
ABOVE In a low-key image you might expect the histogram to look like
this – with shadow details lost off the left-hand side of the graph. This is
correct for an exposure where the mood is supposed to be dark.
ALAN CAMPBELL
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