Histogram Choices in Photoshop

The basic function of the histogram is not hard to understand. It plots the tonal range of an image in a graph, going from pure black on the left to pure white on the right. The numerical data of the image is always shown in 8-bit form. In other words, the graph always shows 256 tonal levels even if the image has more (e.g. 16-bit with 65,536 levels). For the sake of consistency and practicality, this makes sense.

Histograms become more confusing when you bump into their various forms. Look at the drop-down menu in Photoshop CC and you’ll see six histogram choices. These are: RGB, red, green, blue, luminosity and colors. Perhaps a histogram refresher course wouldn’t go amiss.

The RGB Histogram

The RGB histogram unifies all three of the red, green, and blue histograms. That means it gives the sum total of all three RGB values at every one of its 256 levels. This is useful in that it shows you when colour is being “clipped” (i.e. badly exposed causing loss of detail).

What the RGB histogram doesn’t do is show you which colours are being clipped.  That means it can’t give you vital information about exposure and luminance. All three channels must be clipped before highlights are blown or shadows blocked. In the screenshot above, you can see there is clipping to the left of the graph, but you’ve no way of telling whether it reflects one, two or three colours. There is a lack of nuance.

Red, Green and Blue Histograms

In case you hadn’t guessed it, red, green and blue histograms represent separate RGB colours: the primary colours of light. The good thing about viewing these channels discretely is that you can clearly see which colour channels are being clipped. Clipping can cause smooth tonal transitions to appear as harsh, unnatural “banding”.

If there is enough data in one or two channels, it’s possible to recover highlight or shadow detail even when a single channel is clipped. Note there is a distinction between luminance clipping, which causes complete loss of shadow or highlight detail, and saturation clipping, which loses detail in only one colour channel.

Red flowers as a subject are especially prone to saturation clipping. When that happens, you’ll end up with red blobs rather than anything horticultural. The luminosity histogram on the back of many old or cheap cameras would not warn you of this. You’d need either an RGB histogram or, better still, the separate red, green and blue histograms.

When viewed as a group, red, green and blue histograms give an indication of colour casts. Theoretically neutral areas of an image, such as white or grey clouds, would peak in the same place if the overall hue (or white balance) was unbiased.

All pixels in a black and white RGB image have the same red, green, and blue values (between 0 and 255). This means all histograms look the same when you have a black and white image open.

The Luminosity Histogram

The luminosity histogram focuses on overall exposure, so it tells you when all three RGB channels are clipped but won’t tell you when they’re clipped individually. At least it won’t do so very clearly. It effectively treats all images as if they were black and white.

Notably, the luminosity histogram is weighted to take human perception of brightness into account. Thus, green, being the brightest perceived colour, has a 59% weighting while red gets 30% and blue 11%. Any pixel containing pure red, green or blue data will register at a corresponding place along the graph. For instance, a green pixel with 0,255,0 RGB values would appear just over half way.

Only when pixels contain all three colours at their brighter, more saturated values does the data creep towards the right-hand side of the histogram. Eventually, when all three RGB values are at “255”, the pixel is pure white and contains no detail. Conversely, any area with 0,0,0 values is pure black, and again no detail can be retrieved.

When your intended photographic subject contains a single colour, the luminosity histogram has obvious shortcomings. You might notice a spike at a particular point along the graph to indicate clipping, but it’d be hard to decipher its exact meaning.

luminosity histogram, histograms, brightness, luminance histogram
This illustrates the positions of pure red, green and blue pixels on a luminosity histogram. From left to right it shows blue (RGB 0,0,255) at 11%, red (RGB 255,0,0) at 30% and green (RGB 0,255,0) at 59%.
The Colors Histogram

Aside from being a useful choice in Photoshop, the colors histogram appears in Lightroom. It shows all the individual red, green and blue channels together, so you can see exactly which, if any, are being clipped.

Areas containing all three primary colours appear as grey in the colors histogram. Thus, if highlights were completely blown you’d see grey banked up to the right of the graph. If only one colour is overexposed, you’ll see that colour banked up to the right, and so on.

If you see cyan, magenta or yellow in the colors histogram, you know that the corresponding area is absent of red, green or blue, respectively. Cyan represents a mixture of green and blue, magenta is red and blue, and yellow is red and green.

By creating an artificial image of pure red, blue and green, the colors histogram is duped into flagging up luminance clipping (i.e. as if the image contained an area of pure white). Unlike the luminosity histogram, it doesn’t weight colour channels according to their perceived brightness. However, it does offer the most complete data for editing.
Which to Use?

If you have only one histogram open, the colors histogram offers the most info and is surely the best choice.

Should you have room in your Photoshop workspace, the “All Channels View” shows all three RGB channels separately plus the histogram of your choice on top. The weighted luminosity histogram might be useful in that set-up, since it provides alternative data.

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