What is a histogram: how to prevent poor exposures

    | Photography for Beginners | 30/09/2010 09:47am
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    What is a histogram? Histograms can be your biggest asset once you get your head round what they are. In this primer we explain how to use your camera histogram to get the best exposure

    Your camera histogram is a much more accurate way of judging whether a shot needs a bit more, or less, exposure. But it’s not just used for judging exposure: the shape and position of the histogram’s graph can also tell you about the contrast of the lighting in a scene. Below we’ve tackled some of the frequently asked questions about histograms to get you started using these helpful graphs to avoid poor exposures.

    What is a histogram?

    What is a histogram and why do I need to use one?

    In short, the histogram is a type of graph that you can call up on your digital camera’s rear LCD in order to judge the tonal distribution of the images you take. The histogram offers a way of plotting the exposure of a digital image; by looking at the graph, you can see whether a shot is too bright or too dark.

    The histogram’s horizontal axis shows pixel brightness, ranging from pure black on the left to pure white on the right, with the full range of mid-tones in between. Its vertical axis shows the number of pixels at a particular brightness level.


    How do I view the camera histogram?

    You usually look at the histogram after you have taken the picture, when reviewing the shot on screen. Look at your instruction manual to find out how you get this graph shown on the LCD (and to check your digital camera has this facility).

    On Canon DSLRs, for instance, press the Play button, then use the Info or Disp button to call up this display option. On Nikon DSLRs you can use the up arrow on the joypad during playback to toggle through the display options.


    What is a histogram showing me exactly?

    The graph shows the brightness of all the pixels in the image. The brightness is plotted along the x-axis, or bottom line, and the number of pixels is plotted along the y-axis, or vertical line.

    To keep things simple, the numbers and units are not shown on the graph. All you need to remember about your histogram is that the left-hand side shows the darkest tones, the right-hand side shows the brightest tones and the central part of the graph shows the midtones.


    What shape should I aim for on my histogram?

    The shape of the graph is highly dependent on what you are taking pictures of. If you are shooting snowy scenes, for example, the histogram should peak towards the right side of the graph because of all the bright tones.

    For normal subjects, with an average distribution of different tones, the ideal graph rises gradually from the far left outside, peaks somewhere in the middle, then falls away gradually until it has fallen to zero at the far right-hand side, as you can see in the histogram inset below.

    As evidenced in this shot of a red kite, the histogram should correspond with the tones of your scene; a dark scene should have a histogram with a bell shape on the left, a light scene should have a histogram with a bell shape on the right. For daylight scenes, try to expose the scene as far to the right of the graph as possible without clipping the highlights.


    How can I tell if the exposure is wrong in my shot?

    The telltale sign is if the graph is stacked up to the left or the right on your histogram. If there is a peak at the extreme left-hand side of the graph, this shows that there are lots of pixels that are recording as the darkest value black available. This suggests that your shot is probably under-exposed.

    In this photo of a red kite in flight, too little light has reached the sensor, caused either by too fast a shutter speed or the aperture not being wide enough. This shot’s histogram is pushed all the way to the left, a situation known as ‘clipping’. If printed, the clipped areas will appear black, and all shadow detail will be lost.

    Similarly, if the histogram looks as if it’s pushed hard to the right of the graph area, it’s likely that the shot is over-exposed.

    This shot of the same red kite is overexposed, as too much light has reached the sensor. Notice how the histogram reveals that the tonal distribution is pushed all the way to the right, and that the highlights are ‘clipped’. In the printed shot, areas of the scene that should reveal detail will appear pure white, with no detail.


    How do I change the shape of the graph?

    The simplest way to do this is to take another picture of the same subject using a different amount of exposure. Take the shot with less light and the subsequent graph will have shifted to the left.

    Shoot with more light, and the graph will move to the right. Use the +/- exposure compensation control to do this; a plus value moves the histogram to the right, a negative value shifts the graph left.


    What if the histogram is stacked to the left and the right?

    This shows you that the scene you are photographing has both very bright highlights and very dark shadows. It is a sign of a high-contrast scene where the camera is going to find it impossible to find an exposure that captures detail and tone in all parts of the scene.

    Sometimes, you can get round the problem by changing the lighting (so you are not shooting into the sun, for instance, or by coming back later in the day), or by using an ND grad filter to reduce the brightness of the sky. If you have to shoot, it is usually best to adjust the exposure so the graph moves to the left, because it is easier to rescue the shadows than the highlights at the editing stage.


    Is the histogram always right?

    It’s the picture that counts, not the histogram – so look at the image too. The graph itself is based on the tones that would be captured by a JPEG, so if you are shooting raw your image will capture more detail in the shadows and highlights than the graph actually shows.


    Posted on Thursday, September 30th, 2010 at 9:47 am under Photography for Beginners.

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