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Image Filtering

Image Filtering. Problem!. Noise is a problem, even in images!. Gaussian Noise. Salt and Pepper Noise. What to do?. Try to think of ways to remove the noise!. Gaussian Noise. Salt and Pepper Noise. Smoothing. The most obvious and easy way to remove the noise is by averaging.

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Image Filtering

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  1. Image Filtering

  2. Problem! • Noise is a problem, even in images! Gaussian Noise Salt and Pepper Noise

  3. What to do? • Try to think of ways to remove the noise! Gaussian Noise Salt and Pepper Noise

  4. Smoothing • The most obvious and easy way to remove the noise is by averaging. • We can average pixels of a specific neighborhood by convolution with an averaging filter.

  5. Smoothing • Convolution is a simple mathematical operation.

  6. Smoothing • Smoothing using 3x3 mean filter. Gaussian Noise Salt and Pepper Noise

  7. Gaussian Filter • Gaussian filter is more natural!

  8. Gaussian Filter • Gaussian mask with σ=1.

  9. Gaussian Filter • Gaussian filter is more natural! Gaussian Noise Gaussian 5x5 Filter

  10. Median Filter • Median filter operation.

  11. Median Filter • Removing Salt and Pepper Noise using Median Filtering. Salt and Pepper Noise 3x3 Median Filter

  12. Edge Detection • Finding the edges of images is a very useful tool. • How do we find the edges in images?

  13. Edge Detection • Yes you’re right, derivatives!!

  14. Edge Detection • We use image filtering to find edges. • There are many masks: Prewitt, Sobel, Roberts Roberts Sobel Prewitt

  15. Edge Detection • The gradient magnitude and gradient angle can be calculated as follows:

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