Histograms

A histogram is a graphical representation of the tonal distribution in an image. It shows the frequency of each pixel intensity level from 0 (black) to 255 (white) on the horizontal axis and the number of pixels at each intensity level on the vertical axis.

Histograms are essential for photography and image processing as they provide valuable information about an image’s exposure and overall tonal balance[1]. Understanding histograms can help photographers make better exposure decisions and achieve the desired artistic effects.

Histograms display the distribution of brightness levels in an image. The left side of the histogram represents shadows and dark tones, while the right side represents highlights and bright tones. The middle portion represents mid-tones.

Histogram Categories
  • Luminance Histogram: This is the most common type of histogram and represents the distribution of pixel intensities in a grayscale image. It shows the tonal distribution from 0 (black) to 255 (white), with the number of pixels at each intensity level.
  • RGB Histogram: An RGB histogram displays the distribution of pixel intensities for each color channel (red, green, and blue) in a color image. It shows three separate histograms, one for each channel.
  • Combined RGB Histogram: This histogram combines the RGB histograms into a single graph, displaying the overall distribution of pixel intensities across all color channels.
  • Channel-Specific Histograms: In addition to RGB histograms, some software provides separate histograms for each color channel. For example, you might have a histogram for the red channel, green channel, and blue channel individually.
  • Hue Histogram: A hue histogram represents the distribution of hues in an image, particularly in the case of images in the HSL (Hue, Saturation, Lightness) color space. It shows the frequency of different colors in the image.
  • Saturation Histogram: The saturation histogram displays the distribution of color saturation levels in an image, showing how many pixels have strong or weak color saturation.
  • Custom Histograms: Some software allows users to create custom histograms based on specific color ranges or other image attributes. For instance, you might create a histogram that shows the distribution of pixel intensities within a certain range only.

A well-exposed image usually has a histogram that spreads across the entire tonal range, with no significant gaps on the left or right extremes. Underexposed images tend to have a histogram shifted toward the left, while overexposed images have a histogram shifted toward the right.

Clipping occurs when pixel information is lost due to overexposure or underexposure. Overexposed areas result in blown-out highlights (clipping on the right side of the histogram), while underexposed areas lead to crushed shadows (clipping on the left side of the histogram).

To avoid this, photographers may use the histogram to adjust exposure settings. Histograms can take various shapes, such as bell-shaped, U-shaped, or even multi-peaked. The shape indicates the contrast and tonal distribution of the image.

A bell-shaped histogram signifies a balanced tonal distribution, while a U-shaped histogram suggests a high-contrast image with many dark and bright areas. Many digital cameras allow you to view histograms on the LCD screen while reviewing images.

This feature helps photographers assess exposure and make necessary adjustments in real time. Histograms are also valuable during post-processing. Histogram adjustments can be made using photo editing software to enhance the brightness, contrast, and overall tonal balance of an image.

Histogram Shapes
  • Bell-shaped Histogram: This type of histogram forms a smooth curve resembling a bell. It indicates a balanced tonal distribution with a good range of shadows, mid-tones, and highlights. The image has adequate contrast and neither appears too dark nor too bright. An example of a bell-shaped histogram is a well-exposed landscape with a mix of shadows, mid-tones, and highlights.
  • U-shaped Histogram: The U-shaped histogram exhibits more prominent shadows and highlights with fewer mid-tones. This shape suggests a high-contrast image with distinct dark and bright areas. It can be seen in images with strong lighting conditions or high-contrast subjects like silhouettes against a bright sky.
  • Multi-peaked Histogram: A multi-peaked histogram displays more than one peak, indicating the presence of multiple distinct tonal groups in the image. Each peak corresponds to different objects or regions with distinct tonal values. This shape can be seen in images with various subjects, such as a landscape with both dark foreground elements and bright mountain peaks.
  • Flat Histogram: A flat histogram has minimal variation in pixel intensities, resulting in a lack of contrast and tonal range. This shape may indicate an image that lacks highlights and shadows, often appearing dull and lacking visual interest. It can be seen in low-contrast scenes with even lighting, such as an overcast sky.
  • Skewed Histogram: A skewed histogram is asymmetric, with a longer tail extending towards either the shadows (left skew) or the highlights (right skew). A left-skewed histogram suggests underexposure with more dark tones, while a right-skewed histogram indicates overexposure with more bright tones.

In addition to the standard luminance histogram, some cameras and software provide RGB histograms, which display the distribution of red, green, and blue color channels separately. RGB histograms can help identify color imbalances and channel-specific issues in an image. In post-processing software, histograms are often associated with tools or adjustments called “Levels.” The Levels tool allows you to modify the tonal range of an image by adjusting the black point, white point, and mid-tones. By using the Levels adjustment, you can effectively redistribute the pixel values in the image to achieve better tonal balance, contrast, and overall exposure. The Levels adjustment typically displays a histogram representing the distribution of pixel values in the image.

It consists of a graph with a horizontal axis ranging from 0 (black) to 255 (white) and a vertical axis representing the number of pixels at each intensity level. The graph displays a mountain-like shape, where the peaks and valleys correspond to the tonal distribution of shadows, mid-tones, and highlights in the image.

The leftmost slider in the Levels adjustment controls the black point. Dragging this slider to the right will darken the shadows in the image, effectively clipping the darkest tones to black. Adjusting the black point can help increase contrast and make the shadows richer.

The rightmost slider in the Levels adjustment controls the white point. Dragging this slider to the left will brighten the highlights in the image, effectively clipping the brightest tones to white. Adjusting the white point can help increase contrast and make the highlights more pronounced. The middle slider in the Levels adjustment controls the mid-tones.

Moving this slider left or right will adjust the mid-tone values in the image. Dragging it to the left darkens the mid-tones while dragging it to the right brightens them. By adjusting these sliders, you can stretch or compress the tonal range of the image to optimize the contrast and exposure.

The histogram updates in real-time to show the changes you make, making it easier to visualize the adjustments you apply. It’s worth noting that other adjustments in post-processing software, such as Curves[2] or Brightness/Contrast, also work based on similar principles of modifying the tonal range.

However, the Levels adjustment is particularly associated with histograms due to the graphical representation of tonal values it provides. Remember that there’s no one “correct” histogram shape; it depends on the artistic intent and the dynamic range of the scene. For example, a high-key image may have a histogram that skews toward the right, while a low-key image may have a histogram that skews toward the left. Understanding histograms empowers photographers to make informed decisions to achieve the desired creative vision in their photographs.

Pro Mode on my Samsung Galaxy S20 allows you to display the histogram while taking photos.

Footnotes
  1. Tonal balance in photography refers to the distribution of tones across the entire tonal range, from shadows to highlights, in a way that creates a visually harmonious and well-exposed image. Achieving proper tonal balance ensures that no part of the image appears too dark (underexposed) or too bright (overexposed), resulting in a balanced representation of colors and details. An image with good tonal balance exhibits a smooth transition from shadows to highlights, with a wide range of tones contributing to the overall visual appeal. Photographers can use histogram analysis and post-processing techniques, such as level adjustments, to optimize tonal balance and enhance the overall quality of their photographs. [Back]
  2. Curves in photographic software, such as Adobe Photoshop, are a powerful tool used for precise tonal adjustments in images. The Curves adjustment allows photographers to modify the tonal distribution by manipulating control points on a graph. The graph displays a diagonal line representing the original tonal values, and users can add control points to adjust specific tonal ranges. By dragging these points, photographers can brighten or darken shadows, mid-tones, and highlights individually, providing greater control over the image’s contrast and tonal balance. Curves offer a versatile and flexible way to fine-tune exposure and achieve creative enhancements in post-processing. [Back]
Further Reading
Sources

Author: Doyle

I was born in Atlanta, moved to Alpharetta at 4, lived there for 53 years and moved to Decatur in 2016. I've worked at such places as Richway, North Fulton Medical Center, Management Science America (Computer Tech/Project Manager) and Stacy's Compounding Pharmacy (Pharmacy Tech).

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