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What are Histograms used for?

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From editing software to modern-day digital cameras, Histograms are almost everywhere. Understanding how this function works can bring visible improvements in your photography. This article will discuss what histograms are, how understanding these can improve footages and reduce the amount of post-production work, and the impact of histograms on exposure.

What is the Histogram?

In simple terms, histograms are a graphical representation of different light levels in images. These tonal values or light levels are from black to white (from 0% brightness to 100% brightness). The very left side of the histogram graph shows the Shadows, which are dark tones.

As these tones move towards the right side, they start getting lighter. In the middle, Midtones are displayed, which are neither very dark nor light. On the right side, highlights are displayed, which are very lighter tones. The purpose of these graphs is to help the photographer to evaluate the exposure in the footage.

Butterfly photo histogram

Photographers usually overlook the feature of the histogram. These simple graphs can be a major help in choosing the perfect exposure for the images, especially when you’re using the digital camera in manual mode. Understanding these graphs is pretty simple, but it is better to understand their components first for a complete grasp of this.

How is the histogram graph made?

A histogram plots the number of pixels for each tonal value in the image. Each image is made up of an innumerable number of pixels. Each of these pixels has a specific value that shows its color. The brightness or darkness of the pixel is derived from this value.

Butterfly image histogram

A histogram evaluates the number of pixels for each brightness in your image and arranges them in a graph. These pixels are arranged in the graph going from 0% brightness to 100% brightness (from left to right). From 0% to 100%, there are 256 levels of brightness, so technically, at 100% brightness, the brightness level is 256.

The image is first converted into a greyscale, then all pixels in it are analyzed and arranged as per their brightness information, making a histogram chart.

A graph more towards the right or left isn’t necessarily a bad thing. Sometimes it is because of the effect you want to create or filter you are using. It can also be because of shooting situations. For example, in outdoor shooting, mainly under the sun, Histograms are mostly towards the right.

Formby sandy beach in England with histogram

In this case, it doesn’t mean that there is some issue with the exposure. Similarly, in night photography, such as shooting stars, histogram values are mainly plotted towards the left side.

Reading a Histogram

A histogram graph with most of the values towards the left shows that the image is underexposed, whereas one with most of the pixels plotted on the right side shows that the image is overexposed. For an image with balanced brightness and darkness, a peak-shaped graph is plotted in the meridional area.

You can analyze the color tones of your image, exposure, and pixels of specific tone by the height of the histogram on a chart.

Color Channels (RGB Histograms)

If you notice a histogram, you will find three other luminance histograms within the major histogram. These three histograms, red, blue, and green, are the colored part of the color channels graph. These represent the distribution of the pixels for the specific channel.

The point where all three meets are represented as grey or white diagrams. Yellow, cyan, and magenta appear where two of the channels overlap. Overlap of red and green produces yellow color, an overlap of green and blue results in cyan color display in the graph, and red and blue make the magenta color.

The color channels help understand the color temperature (warmness and coolness) of the image.

Highlights and Shadows

Good and balanced exposure is one of the primary factors to get a good image. Understanding shadows and highlights clipping in a histogram allows you to find out the problematic areas of the image in terms of exposure.

Both in highlights and shadow clippings, details are absent. In highlights, pixels are overly blasted with brightness, completely white, and on the right side of the histogram. On the other hand, there is no brightness at all in the shadows area, and pixels are plotted on the extreme left side of the graph.

Scotland mountains scenery against sun with histogram

With this information, photographers can get a complete insight into manual exposure settings and the exposure in their surroundings.

Fixing Highlights and Shadows

Both shadows and highlights can be fixed by fixing the exposure settings. In using manual settings, exposure settings can be fixed by altering the values of the exposure triangle (ISO, Shutter Speed, and Aperture).

In manual mode, the photographer sets exposure himself, but in Programmed Auto (P), Shutter-Priority Auto (S), and Aperture Priority Auto (P), the digital camera sets the exposure value itself. These values usually work, but in the end, digital cameras are mere devices. Shooting with these three auto modes, there can still be issues of exposure.

If you do not prefer setting exposure via manual mode, you can directly fix it using the exposure compensation (EV) setting/button.

Some digital cameras have a dedicated button “+/-” button for it; otherwise, you can find it in the menu. Increasing EV value makes the image brighter and decreasing it makes the image darker. Using + to increase EV will make images brighter and save shadow details. – will decrease the brightness and save the highlight details.

Low Contrast and High Contrast

In a High Contrast Histogram, the value of pixels is at both the left and right extreme. In these histograms, mid-key pixels are usually very less than high and low-key pixels. Such images usually have a striking contrast in tones and have a strong visual impact.

Buenavista del Norte Tenerife with histogram graph

In Low Contrast Histograms, all RBG and greyscale peaks are mostly in the center. The extreme sides of the histogram do not have pixels at all or very few of them. These are mostly for the images with most mid-key pixels. These images do not have highlights and shadows, but they also don’t have any strong visual impact.

What is an Ideal Histogram for an Image?

As mentioned before, an overexposed histogram or an underexposed histogram isn’t necessarily bad. Many factors (such as exposure triangle settings, shooting conditions, photographer’s requirements, filters and effects, et cetera) decide what an ideal exposure for a certain image is. Besides, a histogram displays the information of pixels and their tonal values.

It can help identify the exposure problems, but it is not the standard for good or bad exposure.

But ideally, a perfect histogram is in which pixels are spread throughout the graph from extreme to mid-tones. Ideal histograms show that there is a perfect exposure balance in the image.

Get Best Results using Histograms

By now, you must understand the importance of a histogram to get an image with a balanced exposure. Understanding histograms and the factors associated with them can help you take your photography to the next level.

If your digital camera allows you to preview the histogram before shooting, you can use it for your benefit. Histograms show more accurate colors compared to the LCD screen. Bright or low light in the surroundings, quality of LCD screen, battery level of the camera can depict colors of images, unlike the actual color.

Whereas histograms show more detailed information about colors than a human eye can also analyze, it is much more accurate than analyzing exposure with the naked eye.

The photos I used are mine, and you can get them for free from my gallery. Free full rights too  🙂 Enjoy!

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