Image Enhancement via Adaptive Unsharp Masking

1. Image Enhancement via Adaptive Unsharp Masking By Isha Jha

2. What is Unsharp Masking? • Want to emphasize high frequency contents of an image. • Z(n,m) is a high pass filtered version of image • l controls the level of contrast enhancement • Disadvantages: Noise in smooth regions Overshoot artifacts

3. Objective • Increasing dynamics in smooth areas amplifies noise – so no emphasis • High contrast areas already have high local dynamics – Require low enhancement to avoid overshoot • Medium contrast areas require most enhancement

4. Solution • Use Adaptive Unsharp Masking- l varies according to predefined rules Z

5. Algorithm • Measure of Local Dynamics g(.)

6. Algorithm cont… • b – positive convergence parameter • m – step size

7. Schematic

8. Results

9. Results cont…

10. Measuring Quality of Enhancement • Desired Behavior given by • e(n,m)=gd(n,m)-gy(n,m) • Look at e2 • Cost Function

11. Conclusion • The adaptive approach prevents highlighting of noise in smooth areas • In areas with high contrast it produces medium enhancement to avoid artifacts • Highest enhancement in regions with medium contrast