articles/Lighting/digitalmetering-page3
by Dave Montizambert Published 01/04/2007
A histogram of any image is a bar chart (see image 4 - harpist histogram). The horizontal axis represents the tonal range of the image with the left side of the graph as 0 (zero) and the right side of the graph as 255 in an 8bit per channel image. The vertical axis represents how many pixels there are at each of the 255 tonal values. How high the bars or humps climb represents how many pixels exist at that particular tonal range. No one puts it better than Adobe Evangelist Julieanne Kost; she refers to a histogram as "Piles of Tiles". A digital image is really just a mosaic of square pixels not unlike the tile mosaics of ancient Rome depicting images such as battles etc. Imagine if you will, picking up your monitor with an image open on it and shaking it really hard (don't actually do this...please). If you were to shake it hard enough all of the pixels of your image will fall out onto the floor. Even though this is a mental exercise, be sure to imagine it with a low-resolution image so that you don't have to deal with too many pixels. With a very powerful imaginary loupe and a very small pair of imaginary tweezers, pick up and organise the pixels into stacks. Start by stacking all of the pixels that have a brightness value of 0 (zero) levels - this is assuming that there are any pixels of this value in your image. Next do the same with all the pixels that have a brightness value of 1 level, once again if any exist in the image. Do this same procedure for all levels of brightness starting from 0 (zero) and ending with 255 levels. The stacks of pixels should be side-by-side making a line. If any of the 0 to 255 brightness levels are not represented in the image, then be sure to leave a space in the line for that value. Once you have finished, assuming you were patient enough to spend several months sorting and stacking several million pixels, put your head down on level with the line of pixel stacks so that you have a broad-side view, what you see will be a histogram of your image.
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