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Digital Image Processing

This guide covers advanced contrast processing techniques in digital image processing. It focuses on adjusting brightness and contrast by manipulating pixel value distributions. You'll learn how to lighten or darken images by shifting distributions, stretch the contrast for better visual quality, and understand histogram equalization's role in automatic image enhancement. We discuss the limitations of manual adjustments, the need for human judgment, and the importance of cumulative frequency in creating new mapping functions. Discover how to optimize image contrast effectively while considering aesthetic outcomes.

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Digital Image Processing

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Presentation Transcript

  1. Digital Image Processing Part 2 Contrast processing

  2. Brightness and Contrast • Grey scale and histogram of pixel values

  3. Dark and Light Images

  4. Low Contrast To lighten or darken, shift the distribution left or right To increase contrast, stretch the distribution over a wider range

  5. Good Contrast • Almost full dynamic range used. Could contrast stretch slightly

  6. Point process contrast

  7. Contrast stretch • Histogram towards right so bright • Width narrow so low contrast

  8. Contrast stretch result

  9. Contrast stretch limitations • Subjective so needs human judgment • Best enhancement not always linear • May need to do brightness shift first • Sometimes need an automated method • Can be slow if each point is calculated so use look-up table to speed-up processing

  10. Histogram equalisation • Simple image with up to 10 brightness levels • Plot histogram

  11. Process • Determine the frequency of each pixel level • i.e. distribution as on histogram • Determine the cumulative frequency • How many pixels at level n plus all previous levels • Determine new mapping function • Map old values to new values using the new mapping function

  12. Mapping function

  13. Worked Example • Count the number of pixels at each level and create a frequency column

  14. Cumulative frequency is the sum of the pixels at the current level and all previous levels

  15. Use formula to create new mapping function

  16. New Mapping Function

  17. New Pixel Levels • Old levels (Level) are converted to new levels (F(g)) • New histogram plotted from new distribution (New)

  18. Histogram comparison

  19. New Picture

  20. Advantages and Disadvantages • Does not need human intervention so can be used in systems which need automatic image enhancement • Sometimes it makes a good job but not always • It will improve contrast for imaging systems but may not always produce an image which is pleasing to the eye

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