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Image Enhancement by Spatial Domain Filtering

Image Enhancement by Spatial Domain Filtering. 2D FIR filtering Mask filtering: convolution of the image with a 2D mask Applications to image enhancement: Smoothing: low pass Sharpening: high pass. Data-dependent nonlinear filters Local histogram Order statistic filters Medium filter.

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Image Enhancement by Spatial Domain Filtering

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  1. Image Enhancement by Spatial Domain Filtering

  2. 2D FIR filtering Mask filtering: convolution of the image with a 2D mask Applications to image enhancement: Smoothing: low pass Sharpening: high pass Data-dependent nonlinear filters Local histogram Order statistic filters Medium filter Spatial Filtering

  3. Smoothing Linear Filters Normalization of coefficient to ensure 0 ≤ g(m,n) ≤ L-1

  4. High boosting filter: A ≥ 1 Derivative filter: Use derivatives to approximate high pass filters. Usually 2nd derivatives are preferred. The most common one is the Laplacian operator. Laplacian operator: Sharpening Linear Filters

  5. Laplacian Filter for Image Enhancement

  6. Gradient filters Roberts cross-gradient operator Sobel operator

  7. Calculate a local statistics and then replace the center pixel value with the calculated statistics. Medium filter Useful in removing impulsive noise (salt-and-pepper noise) without smoothing the rest of the image. Local Statistic Filters

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