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Histogram

Compare an image's tonal range to the digital tonal range


In order to better understand what a histogram is, lets first take a look at tables and charts in general using tuxedo rentals as an example.
 

Tuxedo Color Rental Income
Black 500
Dark Gray 8,500
Gray 3,000
Light Gray 7,000
White 1,500

Table 1.  A table showing rentals by color

 

Bar chart
Figure 1.  The same data plotted as a spreadsheet bar chart

 

Histogram
Figure 2.  With so many bars, they get jammed together

 

Photoshop histogram
Figure 3.  A Photoshop histogram.  Mid tone is in the center of the X axis

Table 1 shows tuxedo rentals by color in tabular form.  This information can also be shown graphically.  Figure 1 shows the same data plotted as a vertical bar chart.  The advantage of the bar chart in Figure 1 over Table 1 is the bar chart tells us very quickly which colors have the most rentals, the least rentals and in between.

Assume that we are a much larger renter of tuxedos.  In fact, we offer our clients over 250 shades and styles of black, gray, off-white and white.  If we created a chart of all these shades of black, gray and white, it would be a very wide chart indeed if we tried to label each color.  If instead, we plotted this information in a chart without the labels with the darker shades on the left and the lighter shades on the right, we would get something like Figure 2.  Even though Figure 2 is not as precise as Table 1, it does give us an idea that most people prefer darker tuxedos over the medium gray tuxedos.  It also appears that light gray tuxedos are also popular.  In a chart like Figure 2, the creator of the chart assumes that people know what the X and Y axis mean.  In this case, the X axis is shades of black, gray and white with black on the left and white on the right.  The Y axis is quantity.

 

Adobe Photoshop Histograms

Now, lets switch gears and think about digital images.  On the Light is Information page, we learned that light is composed of color and lightness.  If we were able to chart this information we would be able to see where our information is clustering.  Well, the good news is this information is charted for us in Photoshop and this chart is called the histogram.  A sample histogram is shown in Figure 3.

A histogram for digital images is also a vertical bar chart, and like Figure 2 above, the X and Y axis are not labeled because it is assumed we know what the X and Y axis represent.  First, lets discuss what the histogram is charting.

A histogram plots the number of pixels along the tonal scale.  The X axis is the digital tonal scale with solid black on the left, solid white on the right, mid tone in the middle and all the shades of luminance in-between.  The Y axis is relative quantity.  The higher we got up the Y axis, the greater the number of pixels in a given tone.  Because the tonal scale ranges from 0 to 255, the individual vertical bars that show the relative number of pixels in a given tone are jammed together so tightly that it forms one solid, curving mass, as seen in Figure 3.

Examining Figure 3, we can tell the following.  There is no to very little solid blacks and solid whites.  The number of pixels darker than mid tone is greater than the number of pixels brighter than mid tone.  The number of pixels in the mid tones is far less than either the number of darker pixels or the number of lighter pixels.  Does this mean the image was improperly exposed?  No.  We would not be able to tell if this were an improper exposure unless we saw the image that produced it and we knew what the photographer was trying to accomplish.  From an exposure perspective, what we can tell about this histogram is that neither highlights nor shadows were clipped.  So we would assume we should be able to see detail in most of the image.  In addition, because the curve formed by the mass of histogram bars has no gaps, we would expect to see smooth gradations between tones in the image.
 

Example

Figure 4 is an image with its actual histogram.  From the histogram we can tell there are no solid whites, most of the image is darker than mid tone and there is some slight clipping of blacks.  But when we look at the image, the clipped blacks are in the deep shadows of the trees, so this is not a problem.

Trees and shrubs Figure 4A.  The image ...

Histogram Figure 4B.  ... and its histogram

Clipping

When an image is over or under exposed, its histogram will show a concentration of pixels to the left if under exposed and to the right when over exposed.  When the concentration is bunched up against the edge of the histogram, we know that significant detail has been lost in the image.  This loss of detail is referred to as clipping.  Figure 5 below shows the same image with major loss of detail.  This is reflected in the image's histogram.

Underexposure Figure 5.  Over/under exposure ...

Histogram for underexposure ... appears as clipping in a histogram

Gaps

Gaps is the term used to describe the situation where an image's tonal range is missing small sections.  Gaps appear in a histogram as small vertical slits, as seen on the left in Figure 6.  Gaps are not necessarily bad.  However, if there are enough gaps and they are wide enough, the image will show signs of banding, especially in broad areas such as sky and water.  An example of banding can be seen on the right in Figure 6.  The green arrow in the example marks the boundary where the transition between top and bottom is not as smooth as could be.

Tip

Because of the difference in a printer's and a monitor's ability to display tonal gradations, it is possible for banding to appear in a print even if not visible on a monitor.  This is one reason why prints should be closely examined.

 

 

Histogram gaps Figure 6.  Gaps

Banding


The Photoshop Histogram panel

Channel histograms
Figure 7.

If we look at the Channel drop down box in Figure 7, we will see RGB.  This means the histogram is plotting the tonal information of the composite color channels.  In Photoshop CS, we can use the histogram panel menu (see yellow arrow in Figure 7) and select the All Channels View.  In this view, we will see four histograms for a RGB image.  The top histogram is the composite histogram.  The histograms below the composite are for the individual color channels.

As we work on an image, we will want to refresh the histogram.  This is done by clicking the Refresh icon Refresh icon. This icon is circled in Figure 7.