Undoubtedly in the innovation of digital photography changed the world of photography forever. Gone were the days of analogue photography. Darkrooms turned into storage space, and photographers could now take a vast number of photos at no extra cost.
Digitization in photography also brought on a plethora of new technology, photo editing software and tools for photographers to be able to use. One of these was the histogram.
The histogram is found in almost any modern image editing software and digital cameras. Yet it still intimidates many amateur photographers. The reason is that for starters, the mountain-like shape of the graph coated by a range of different colours can be a nightmare on its own to look at with no prior experience or knowledge of histograms. While they may seem complicated, they’re pretty easy to use. All you need is just a basic understanding of how they work.
Previous to digital photography, the film had to be developed before it could be known for sure whether the images had a good quality of exposure. These days, cameras are designed to focus on exposure on the scene as a whole. However, there are instances where the exposure may not suit most of the image; histograms were introduced into cameras to fix this very problem.
What is a histogram?
It’s a graphical representation of the tonal values of your image. Simply put, its purpose is to show you the distribution of tones in your photograph. Dark tones are displayed on the left of the histogram, signifying 0% brightness. As you move to the right, the tones get lighter until they turn white, indicating 100% brightness on the right. In the middle, we have mid-tones, which are neither dark nor light.
Why use the histogram?
An important reason to use a histogram is to evaluate your photo to check for ‘clipping.’ The term ‘clipping’ is used to describe whether there is a region that is either overexposed or underexposed, to the point where the sensor does not pick any detail. Overexposed photos are those that are too bright (white). In the case of an overexposed photograph, there will be a significant rise on the right of your histogram touching the side of this graph. This indicates that a portion of your photo is completely white and without detail and that there are blown out highlights, which can be a big problem.
It can also happen with the left side of your histogram, which may mean that your photo is underexposed. Your image may be too dark, with too many shadows and black tones. That being said, black areas in your print may not be a problem if, for example, you’re shooting, a night shot. But where possible you should try to avoid large areas in photos which are completely black.
Clipping is challenging to catch with the naked eye, and the process is hugely simplified with a histogram. Understanding histograms will help you capture more balanced images. Sometimes an image may look fine on camera on a small LCD screen, but once uploaded to a computer, it can appear to be too dark or too bright.
How do you read a histogram?
Some cameras show you the histogram before you take a shot (called a “Live View”) while others display it afterwards. Consult your camera manual to figure out how to display the histogram. Remember that the scale goes from left to right, dark to bright. The taller the peak, the more pixels of that brightness there are in the image. If there is a great deal of contrast in your photo, there will be fewer pixels appearing in the middle of your graph. How high your peaks are shows the number of pixels in that particular tone.
The reason many photographers prefer to use the histogram while out in the field is that they have a chance to take another shot. For instance, if the photographer finds the exposure is off, and there is an area that is blown out, it will have no detail at all. Even though editing software is pretty powerful these days, in extreme cases, you won’t be able to fix this in post-production. The colours on the graph are essential as well; if a tone is too bright, it may cause the picture to be too saturated and lose detail. There are generally five different colours on a histogram: black, white, red, blue, and green. The black and white graphs are meant to showcase the tones of your photograph, while the red, blue, and green are intended to display the brightness of those colour channels. You can find histograms in editing programs like Adobe Photoshop and Lightroom, and while they may look different, they function just the same way as the histogram on your camera.
The perfect histogram
Many people wonder what the ‘perfect histogram’ looks like. There is no such thing. There is, however, an ideal histogram, which has pixels spread throughout the axes with many mid-tones. The reason this type of histogram is considered superior is that it allows flexibility when it comes to processing the image. Since you have tons of information captured in the photograph, you’re able to generously decrease or increase shadows and highlights before you see any kind of decrease in quality. It also means that there are no clipped highlights or shadows.
The ambiguity of the histogram arises by the fact that it is open to interpretation—some artists like spikes of solid black or vibrant tones. It’s up to the photographer to decide what works. While you can undeniably benefit from a histogram to correct your exposure, it must also be taken with a pinch of salt. Just because your photo is inclined towards a specific tone, doesn’t mean that it is incorrectly exposed. Some artists stylistically choose to break the histogram rules purposely, which is completely fine. The histogram’s job is to show you what’s going on so that you can consciously see when your photograph is the exception to the rule.
Histograms are useful for photographers of every level. Not only are they not overly complicated, but they also contain necessary information about your shot that can help you get the most of your photography. Getting more familiar with histograms will change the game and help you shoot and edit your photos better. The days before histograms are history so make sure you put your new knowledge to work!
Photo credits: Kav Dadfar – All rights reserved. No usage without permission.