UW-Madison ECE 533 - Image Enhancement via Adaptive Unsharp Masking

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Image Enhancement via Adaptive Unsharp MaskingWhat is Unsharp Masking?ObjectiveSolutionAlgorithmAlgorithm cont…SchematicResultsResults cont…Measuring Quality of EnhancementConclusionImage Enhancement via Adaptive Unsharp MaskingBy Isha JhaWhat is Unsharp Masking?Want to emphasize high frequency contents of an image.Z(n,m) is a high pass filtered version of image controls the level of contrast enhancementDisadvantages: Noise in smooth regions Overshoot artifactsObjective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 enhancementSolutionUse Adaptive Unsharp Masking-  varies according to predefined rules0 -1 0-1 4 -10 -1 -1ZAlgorithmMeasure of Local Dynamics g(.)Algorithm cont… – positive convergence parameter – step sizeSchematicResultsResults cont…Measuring Quality of EnhancementDesired Behavior given bye(n,m)=gd(n,m)-gy(n,m)Look at e2 Cost FunctionConclusion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


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UW-Madison ECE 533 - Image Enhancement via Adaptive Unsharp Masking

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