Image histograms is a crucial tool for digital photographers, in their analysis of exposure. For those who don't know what a photo histogram is, it is a graph that shows how bright and how dark your images are through a break down of pixels. The left side of a photo histogram represents dark pixels, hence a histogram with "tall bars," especially on the extreme left end of the diagram indicate an underexposed image. The right side, on the other hand, represents bright pixels, so the opposite rule applies. In these extreme cases of underexposure and overexposure you must use manual settings to compensate for the error. These graphs are useful because often times the image you see on your monitor can misrepresent the actual image, and a histogram actually tells us if our images are correctly exposed. So what does an ideal histogram look like?
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| Copyright Geoff Lawrence |
This histogram shows a balance between dark and bright pixels with no pure white or black pixels (this can be concluded because of the absence of bars on either of the diagrams edges or ends) thus, it could be considered a correctly exposed image. The following are examples of incorrectly exposed images because of the uneven balance on the graph of bright and dark pixels. Another noticeable problem is the presence of the bars on the extreme ends of the graph.
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| Copyright Geoff Lawrence |
But of course like every established rule in photography it can and should be broken. Dark images and bright images can be artistic, and histograms do not represent the value of a given image, so its up to you to utilize the histogram properly.
If your skilled at photo editing software, such as Photoshop or Aperture you can get the best of both highlights and shadows through the photo blend technique or various other adjustment options. To read more about all of this visit:
http://www.photoxels.com/tutorial_histogram.html
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