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Published byGriffin McKinney Modified over 9 years ago
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Logarithmic Image Processing (LIP) By Ben Weisenbeck Oiki Wong
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Introduction Q: Why LIP? A: Contrast Stretching and Image Sharpening simultaneously Q: Why not histogram equalization? A: A flat histogram often times are not what is needed to enhance certain features within the image.
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Key Things α governs the contrast of the image β governs the sharpness of the image
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Main Idea Tune the parameters until you get what you want. But first, know what each parameter does! α governs the contrast of the image: α >1 Brings out bright areas α <1 Brings out dark areas α < 0 Negative Transformation β governs the sharpness of the image: β >1 Sharpening β <1 Blurring n x n window also governs the sharpness of the image Bigger is not always better
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Examples of Histogram Equalization isn’t the answer
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Graphical User Interface
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Enhancing Dark Details
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Enhancing Bright Details
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Color Enrichment Our result shows that the algorithm can also create color enrichment to a certain degree. This is something that histogram equalization fails to perform. The color in the words “U.S AIR FORCE” stands out much more in the enhanced image. Also note that the shadow in the mountain is “deeper” than the original.
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Color Enrichment Histogram Equalization creates an illusion that the flight was in bad weather!
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Window Sizing LIP with 3x3 windowLIP with 9x9 window
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Noise F(ij)=B(i,j)+noise
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Summary Parameters Parameters α controls the contrast α controls the contrast enhancement β controls the sharpness of the image. β controls the sharpness of the image. Larger Window size => sharper edges Larger Window size => sharper edges Superior to Histogram Equalization Superior to Histogram Equalization Black and White images Black and White images Color images Color images Noisy Images Noisy Images
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Conclusion Advantages Advantages Simultaneous enhancement of contrast and sharpness Simultaneous enhancement of contrast and sharpness Fine-tuned control over image enhancement Fine-tuned control over image enhancement Disadvantage Disadvantage Parameter values must be carefully selected and adjusted to obtain desirable results Parameter values must be carefully selected and adjusted to obtain desirable results
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Questions?
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