Histogram in Photoshop Explained!!

The histogram is one of the most important and powerful tools for the editor and with a few moments reading, you’ll understand a few simple tips can make you a much more powerful image editor, as well as helping you shoot better photographs in the first place. So what are you waiting for? Read on!

In digital cameras, we all talk about settings like brightness, exposure, contrast, and white balance very frequently. But still, if we are questioned about what all these settings actually mean and how they are different from each other, we may end up confusing ourselves. To bring our confusions to an end, we have histograms. They provide the simplest mechanism to make us understand, observe, differentiate and tune these settings.

Histograms are nothing really all that complex. What they represent are the distribution of tones throughout the image—a simple algebraic graph.

The horizontal line represents the various values in your image. The leftmost side stands for pure blacks and dark shadows. The right side are your highlights, and pure whites. The values between the two fall much the way you might imagine them, with dark tones transitioning to mid tones, then on unto brighter and brighter highlights.

The vertical axis represents how much of any corresponding value, whether light or dark, appears in the image. Higher peaks represent high concentrations of that particular value. Digital images don’t have unlimited tones. They only have 256 (that’s 8-bits of information). On a Histogram, black is 0 and white is 255. The dark tones all have low values and the bright tones have high values.

Now let us learn how we can get an idea of this picture’s brightness, exposure, contrast, and white balance through the histogram.

Brightness

• If all the pixels stack upon the pile of level 255 (highest), it means the image is purely white, i.e. image brightness is maximum.

• If all the pixels stack upon the pile of level 0 (lowest), it means the image is purely black, i.e. image brightness is zero.

• If more pixels stack upon the piles representing higher gray levels, it means overall brightness of image is high.

• If more pixels stack upon the piles representing lower gray levels, it means overall brightness of image is less.

Exposure

• If there are lots of pixels stacked upon the piles of level 0 and near 0, it means it’s an underexposed image. Such a histogram indicates clipped shadows.

• If there are lots of pixels stacked upon the pile of level 255 and near 255, it means the image is overexposed. Such a histogram indicates clipped highlights.

The last two histograms for exposure show that lots of image data is at the boundaries of gray levels, which means that there is much data which camera could not capture and clipped to 0 or 255 levels. This means that the dynamic range of the actual scene is beyond the dynamic range (0 to 255) of the camera. But please NOTE that this point holds valid provided there is not much pure black or pure white actually in the scene. For example, if we shoot a purely black wall, there will be lots of gray level 0 pixels and thus we cannot call this picture underexposed. The same will be the case when shooting a purely white wall and we won’t call that picture overexposed.

Contrast

• If the image has both clipped shadows and clipped highlights, the image has too much contrast.

• If the dynamic range of image does not cover the complete 0 to 255 levels and majorly contains midtones, the image has too little contrast.

• The concept explained above is generalized to colored pictures by having separate gray level histograms for red, green, and blue pixel data.

White balance

Finally, let us learn how to relate histograms with the image’s white balance. Take a gray card or some neutral color object. You can see a spike in the red, green, and blue histograms when you shoot this gray card. If the spike in all the three histograms is at the same place, then the image is neutral. Otherwise, you will need to adjust the white balance of the image. For example, if the blue channel is much towards highlights, then the scene is too bluish and you should adjust the white balance accordingly.

So we see that proper understanding and use of histograms in photography makes our lives much easier.

Some examples to show how much histogram is important

Now, the thing is many people ignore the histogram while editing or even while capturing photos. Histograms are great tools for photography because they allow you to do two key things. First of all, a histogram tool on a DSLR will allow you to see how balanced the composition you’re shooting is before you shoot it. Is it too heavy on the darks, or are the darks lost in the composition? Are the whites too bright—all the detail washed out of them? An in-camera histogram can give you a rough idea of how your image will take or has taken.

In addition to this, histograms can tell you what’s wrong with an image, as well. Sometimes, a potentially great shot gets exposed wrong, and you don’t have the time to bracket or recreate the moment. By looking at your photo’s histogram in an image editor after the fact, you can find out how to best bring your ruined exposures back from the brink, and get a decent, or possibly even a great image out what might have originally been a poor one.

So, one should never neglact the histogram.