Histogram equalization is a technique for enhancing contrast in images. It transforms the intensities so that the histogram of the output image approximately matches a uniform distribution. The technique maps the intensity levels of the input image to a new range of values based on the probability distribution of the original histogram. This process spreads out the most frequent intensity values, resulting in an image with higher contrast.

1. Intensity Transformation and
Spatial Filtering
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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