Histograms

Many SLR digital cameras have a histogram function, which lets the photographer view graph along side the image on the LCD screen.

A histogram is a means of breaking down the colours and tones in an image into data that can be read as a graph - when incorporated with a digital camera, the advantage is that it can tell us if the exposure has recorded the visual information that we intended and that no information has been clipped or lost.

It can tell us if we have lost detail or data in both the high lights and shadows - this loss of information is called clipping. In situations where there is contrasty lighting, it can be impossible to record all the information from the deepest shadow to the the lightest highlight.

Mouse over		The graph depicts the distribution of pixel values across the tonal range from black to white, and the relative number of times each tone is recorded which is referenced by the height of the line. Digital cameras and scanners assign brightness, contrast, and black or RGB (Red Green, Blue) colour values to each image pixel. A pure white is represented with a value of 0 (levels of colour); A PURE BLACK EQUALS 255. Inspecting the histogram of a digital image is a good way to quickly evaluate the tonal range quality and highlight and shadow details. In this situation the tonal values recorded fall within the latitude of the sensor and all the information is recorded.
		In this situation the exposure is not great enough to record all the tonal values of the scene and the darker tones have fallen off the graph. So if you review an image in the LCD screen with the histogram and it shows this you know you have lost information.
		In this situation the exposure is too great enough to record all the tonal values of the scene and the lighter tones have been clipped. So if you review an image in the LCD screen with the histogram and it shows this you know you have lost information.
		However in some situations where the subject has a great tonal contrast range it is impossible to recorded all the information an the information might fall of the graph at both ends. In this case you will need to consider what is the most important aspect of the image.

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