ColorStyler offers various types of histograms. Basically histograms don't show anything you can't see in the image itself if you know where to look and look really closely. But histograms have the advantage that they are more structured than the image itself, so they let you recognize image problems easier.
A histogram is a statistical display of an image parameter, e.g. brightness, hues or saturation. It shows the distribution of certain pixel values in an image. These values usually range from 0 to 255 in a 8bit image. The range of these values is displayed from left to right in the histogram, so the value 0 is displayed at the outer left and the value 255 is displayed on the outer right side. The amount of each value is displayed from bottom to top, so the height of the curve represents the number of pixels that have a certain value. If more pixels have a certain value, the histogram curve will be higher at that point.
In ColorStyler the histogram curve is separated into three areas: the shadows on the left side (with values from 0 to 85), the midtones in the middle (with values from 86 to 170) and the highlights on the right side (with values from 171 to 255). ColorStyler displays all three areas equally wide, although some people may argue that the midtones are twice as wide as the shadows and the highlights. But usually it is more useful to define the three areas equally wide.
The left combo box lets you choose the histogram type. The different types are discussed below.
The Zoom check box scales the histogram vertically. This can make the peaks higher and reveal valleys that were not there before. This is especially useful if there is one extremely high peak, which makes all other values appear very small.
The No Gaps check box makes gaps in the histogram curve dissappear. It does not change the image itself, but simply improves the histogram view. These gaps can appear when the tonal values are stretched by an image processing operation, but they usually do not indicate image damage.
ColorStyler lets you display the histograms in four different styles with the combo box located on the right side. "Filled" creates the standard histogram type that is known from many graphics applications. The "Gradient" option draws a color gradient from left to right. The colors of this gradient are different from histogram to histogram. The "Line" option draws a line and leaves the area underneath empty. "Dot" plots the histogram values as dots, which may make some histogram values less readable, but helps you to recognize a general trend more easily.
You can use the RGB histogram to see if there are blown highlights or cutoff shadows in an image. Blown highlights can be identified by a high spike on the right side whereas cutoff shadows are represented by a high spike on the left side. The higher and wider the spike is, the more information was cut off.
If there is a large slope on the left or right side and not just a thin spike, then tonal values of the photo are already cut off. If the cut off is on the left side in the shadows, then it is often not really visible in the image itself. Another bad sign might be that the middle part of the curve is quite flat or extremely low. If such histograms are produced by an adjustment in ColorStyler, you may correct the setting, unless you want that look.
The RGB histogram also shows an image's darkest value (the end point of the curve at the left) and brightest value (the end point of the curve at the right) in an image. Both are also called black point and white point. The range between both points is called dynamic or tonal range and determines the contrast of the image. The optimal contrast is achieved if the curve starts at the outer left and ends at the outer right. If this isn't the case, the image may not have a good contrast. If the curve starts more towards the middle, it also means that the image is too bright. If it ends more in the middle, then the image is too dark.
Nevertheless there are always exceptions to the rule. For example, a photo of a snow landscape and an overexposed photo have a similar histogram, but the snow photo is fine while the overexposed photo needs to be fixed. On the other hand a photo with a black sky and stars or the moon looks on the histogram as if it is underexposed, although this isn't the case. Another example is a photo taken on a foggy day. If you increase the contrast too much, the result will look terrible and won't give the viewer the impression of fog anymore. A good rule is to always investigate the contents of the image and to not trust the histogram completely.
Small gaps tend do show up in the RGB Histogram
more often than in other histogram types. They are only a sign that an image
was processed and are usually nothing to worry about.
Intensity, Luminosity and Lightness Histograms
The Intensity, Luminosity and Lightness histograms are very similar for many images. They often let you better judge the brightness distribution in an image, but they are not suitable to judge blown highlights or cutoff shadows. If the image contains more shadows, the hill is more on the left side. If it contains more highlights, the hill is located on the right side. If it is well balanced, the hill or hills are usually in the middle of the histogram.
If there are two peaks, one on the outer left side in the shadows and one on the outer right side in the highlights, it may mean that the photo was taken under difficult light conditions and may exhibit unusually high image contrast. If there are peaks on both the outer left and right side, the image contrast is usually too extreme.
Red, Green, Blue, Cyan, Magenta and Yellow
These histograms can be used to recognize color casts or other color problems. For example if the Blue Histogram contains a curve that is only located in the shadows, it means that there are as good as no light blue areas in the image. This can mean that the color blue was suppressed in the image and that the image has a yellow color cast.
The Hue histogram lets you see if some hues are missing. If some hues are dominant in the image, it can mean - but not necessarily - that there is a color cast. A close-up photo for example is usually missing some hues even if it doesn't have a color cast.
The Saturation histogram lets you see if there is a problem with the saturation in the image. For example if there is nothing in the left part, the image may be oversaturated or if there is nothing on the right side, the image is probably undersaturated. However, images with a lot of white and dark areas may appear undersaturated according to the histogram, but as pure white and black have no saturation, the image saturation may still be fine.
The Colors histogram is similar to the RGB histogram, so it also lets you see if there are blown or cutoff areas. Additionally it shows which hues are dominant in the shadows, midtones and highlights.
Black and White Histograms
The left part of Black histogram and the right part of the White histogram are similar to the RGB histogram. Both histograms should fill the whole value range from left to right. The above Black histogram indicates that the image is too "black" and too much "white" at the right end of the histogram is missing. The above White histogram also has a small gap at the right end, which means that the white values aren't fully used.
If there is a large gap at the right or left end of the histogram, it means that the contrast of the image is bad. Spikes at the outer left or right indicate cutoff shadows and blown highlights.