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Image Enhancement via Adaptive Unsharp Masking
By Isha Jha
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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
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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
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Solution -1 4 Use Adaptive Unsharp Masking- l varies according to predefined rules Z
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Algorithm Measure of Local Dynamics g(.)
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Algorithm cont… b – positive convergence parameter m – step size
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Schematic
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Results
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Results cont…
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Measuring Quality of Enhancement
Desired Behavior given by e(n,m)=gd(n,m)-gy(n,m) Look at e2 Cost Function
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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
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