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Understanding bit depth

From: Shooting and Processing High Dynamic Range Photographs (HDR)

Video: Understanding bit depth

Whether you create a digital image by scanning from a piece of film, taking a picture with a digital camera, painting in a painting program, or capturing an image with a digital video camera, however you do it, you are creating a grid of pixels and each pixel has an individual color. Every color is represented by a number. So all red pixels might be represented by the 4, while all purple pixels might be represented by the 5. The total number of colors that you can represent depends on the range of numbers that you have to work with.

Understanding bit depth

Whether you create a digital image by scanning from a piece of film, taking a picture with a digital camera, painting in a painting program, or capturing an image with a digital video camera, however you do it, you are creating a grid of pixels and each pixel has an individual color. Every color is represented by a number. So all red pixels might be represented by the 4, while all purple pixels might be represented by the 5. The total number of colors that you can represent depends on the range of numbers that you have to work with.

If we have only 64 colors to work with, then I look like this. Whereas, if we have 8 colors to work with, I look like this. 4 colors, 2 colors, 256 colors, millions of colors. The process of reducing the number of colors that we have to work with is called Posterizing and the range of numbers that we have to represent the color of a pixel is called bit depth. A computer can only store and manipulate 0s and 1s.

A single 0 or 1 is referred to as a bit and we group bits together into bytes to create larger numbers. Now we usually count using a base 10 system, most likely because we have 10 fingers. If I limit myself to only two digits when counting in base 10, and I don't mean digit as in a finger, but digit as in the 1s or 10s digit in number, with two digits I can count from 0 to 99. If I give myself a third digit, I can count from 0 to 999.

A fourth gets me to 9999 and so on. Computers count in binary or Base 2 system and it works the same way. If you add another digit you can count higher. In Base 2 with 8 digits or bits, I can count from 0 to 255. With 9 bits I can count from 0 to 512 and so on. Therefore, if I say that I'm going to store 8 bits of data for every pixel in an image, then I'm storing a number between 0 and 255 and that number represents the color of 1 pixel in the grid of pixels that makes up my image.

In other words, I can have 255 different colors in my image, 256 if you count black, which is 0. We say that such an image has a bit depth of 8-bits. Now, this is not a measure of dynamic range. The darkest and lightest colors can be anything I want them to be, but with 8 its per pixel I get only 256 slots between the darkest and lightest. If I go to a higher bit depth, say 10 or 12 bits per pixel, I get a tremendously greater range of numbers to work with and therefore a much greater number of colors.

Now, your camera probably captures 10 to 14 bits of color per pixel. The JPEG format only allows 8 bits of color per pixel. So if you are shooting in JPEG mode, then the camera throws out a fair amount of color data before it saves the file. I am talking about all this now because later some of our HDR processes are going to involve creating images with a very high bit depth, 32 bits per pixel, which allows us to store lots and lots of colors and tones, and then we are going to crunch those big numbers down to 16 or 8 bit numbers and that crunching down step, that change a bit depth, is a critical part of certain HDR methods.

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This video is part of

Image for Shooting and Processing High Dynamic Range Photographs (HDR)
 
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  1. 6m 46s
    1. Welcome
      2m 0s
    2. What you need for this course
      2m 37s
    3. Using the exercise files
      2m 9s
  2. 24m 55s
    1. Dynamic range defined
      4m 31s
    2. Understanding bit depth
      3m 37s
    3. Image sensor and shadows
      2m 38s
    4. Three methods for capturing more dynamic range
      3m 56s
    5. HDR shooting and processing
      4m 40s
    6. Single-shot HDR
      2m 43s
    7. When to use HDR
      2m 50s
  3. 19m 59s
    1. Finding HDR subject matter
      4m 38s
    2. Shooting HDR
      9m 45s
    3. Workflow and organization
      5m 36s
  4. 17m 52s
    1. Using gradient masks to improve dynamic range
      3m 56s
    2. More dynamic range masking
      8m 57s
    3. Masking with brushes
      4m 59s
  5. 1h 35m
    1. Creating an HDR image in Photoshop
      12m 15s
    2. Creating an HDR image in Photomatix
      22m 5s
    3. Creating an HDR in HDR Efex
      11m 47s
    4. Merging in Photoshop and processing elsewhere
      3m 51s
    5. Using Tone Compressor in Photomatix
      4m 25s
    6. Using Exposure Fusion in Photomatix
      7m 35s
    7. Single-shot HDR images in Photomatix
      4m 18s
    8. Single-shot HDR images in HDR Efex
      1m 3s
    9. Single-shot HDR images in Photoshop
      5m 32s
    10. Ghosting and Photoshop
      2m 51s
    11. Ghosting and HDR Efex
      2m 47s
    12. Ghosting and Photomatix
      6m 36s
    13. Batch processing in Photomatix
      10m 51s
  6. 2h 9m
    1. Reducing noise and correcting chromatic aberrations
      13m 33s
    2. Finishing an image
      8m 42s
    3. Handling HDR images that are "flat"
      13m 37s
    4. Combining HDR and LDR
      19m 40s
    5. Selective editing with HDR Efex Pro
      9m 42s
    6. HDR that doesn't look like HDR
      12m 42s
    7. Tone mapping troubles to watch for
      6m 46s
    8. Why use HDR for black-and-white images?
      5m 26s
    9. Black-and-white HDR
      12m 39s
    10. Panoramic HDR
      12m 3s
    11. HDR time lapse
      4m 24s
    12. Processing the trestle image
      10m 1s
  7. 37s
    1. Goodbye
      37s

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