Histogram equalization is a method for adjusting image intensities to enhance contrast by equalizing the histogram of the input image. It transforms the intensities so that the histogram of the output image approximately matches a uniform distribution. The technique maps the intensity levels in the input image to a new range of values based on the probability distribution function of the original histogram to flatten and widen it, resulting in an increased contrast in the output image.

1. Intensity Transformation and
Spatial Filtering
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11:30 am

2. Histogram Processing
• Intensity levels in the range [0, L-1]
• Discrete function h(rk)=nk
• Histogram Normalization
• p(rk)=nk/MN
• Horizontal axis – intensity values rk
• Vertical axis - h(rk)=nk
• or p(rk)=nk/MN
• Four Basic image types Histogram

3. Histogram Equalization
• T(r) is monotonically increasing
function
• 0 ≤ T(r) ≤ L – 1
• Using Inverse formulation
r=T-1(s)
• T(r) is strictly monotonically
increasing function

4. Histogram Equalization

5. Histogram Equalization

6. Histogram Equalization

7. Histogram Equalization

8. Histogram Equalization

9. Histogram Equalization
• Example