The Histogram – How to Use It

In this article, I want to talk about the histogram: what it’s for, how to read it correctly, and how it can help you.

What is a Histogram in Photography?

A histogram is a graphical representation of the brightness values of a digital photo. It helps you determine whether your image is properly exposed—whether it’s too bright or too dark—something you can’t accurately judge just by looking at your camera display or even a monitor. A histogram won’t tell you if your photo is good, but it will tell you if it’s exposed correctly.

Histogram vs. Camera Display

Your camera display can be misleading. Sometimes it looks too bright, sometimes too dark. In direct sunlight you can hardly see it at all, while at night everything looks brighter than it really is. The display should only be used to check composition, never exposure. For evaluating brightness and exposure, you should always rely on the histogram.

How to Read a Histogram

Here’s an example of a histogram:

On the left side are the dark tones, on the right the bright tones. The taller the bars, the more pixels of that brightness exist in the image. From left to right, a histogram shows shadows, then dark tones, midtones, highlights, and finally pure whites.

In this example, the tones are well distributed, with a large “mountain” in the middle that tapers off evenly toward the edges—indicating many midtones in the image.

At the far left is pure black, at the far right pure white. In this photo, there are no pure blacks and no pure whites, which is good. If the histogram is cut off at either end, that means detail is lost in those areas (clipped blacks or clipped whites). Once those details are gone, you can’t recover them in editing. Ideally, a correctly exposed image will have little or no clipping at either end.

To illustrate, here’s a modified version of the photo:

Underexposed: Too dark. The histogram is cut off on the left side, showing clipped blacks.

Overexposed: Too bright. The histogram is cut off on the right side, showing clipped whites (for example in the sky).

A Few More Examples

The curve doesn’t always need to be centered—it depends on the subject.

A darker photo may have most of its tones on the left, but as long as it’s not clipped, it’s still fine.

A brighter photo may lean to the right, but as long as there’s no pure white clipping, detail remains intact.

JPEG vs. RAW Files

To understand how histograms differ between formats, you need to know how the files are structured:

• JPEGs are finished images. The camera processes them internally, and the histogram reflects this finished state. That means limited editing flexibility—if you brighten a dark JPEG, noise and quality issues appear quickly.
• RAW files are undeveloped “digital negatives.” They store unprocessed data, usually with higher bit depth (up to 16-bit per pixel), preserving far more detail and editing latitude.

When you view a RAW file, your camera or software shows you a small embedded JPEG preview. That preview also generates the histogram you see on the camera, but the RAW itself still contains extra data.

So even if the histogram of a RAW image shows clipping, you usually have one or two stops of latitude to recover highlights or shadows in post-processing.

The RGB Histogram

In addition to the standard luminance histogram, cameras and editing software also offer an RGB histogram, which shows brightness for each color channel (red, green, blue). Since all colors are made from these three, you can use it to identify clipping in specific channels. For example, a bright blue sky may push the blue channel to the far right. One clipped channel can sometimes be acceptable, but ideally not more than one.

The Histogram in Practice

As mentioned earlier, the goal is proper exposure. A histogram shows whether an image is too dark or too bright. Generally, it’s easier to recover detail from slightly underexposed areas than from blown-out highlights. That’s why avoiding overexposure is critical.

Enable the “highlight warning” on your camera (often shown as blinking highlights on the display). Overexposed areas will also be reflected in the histogram. With RAW you may still recover some detail, but with JPEG you won’t.

If you can’t avoid clipping, your subject might have too much dynamic range for the camera. In landscape photography, for example, neutral density gradient filters can help balance exposure. Another solution is bracketing multiple exposures and merging them later into an HDR image. HDR is controversial, some love the look, others dislike it, but used carefully, it can handle challenging light conditions while still looking natural.

Final Thoughts

For me, the histogram is an indispensable tool for both shooting and editing. The sooner you get comfortable with it, the sooner you’ll consistently produce technically better photographs.