1. Lecture 10
Image sharpening

2. Comparison between the difference operators

3. Enhancement with second derivatives
Laplacian: 1 -4
Laplacian mask

4. Enhancement using laplacian
Original image
Blurred image
Laplacian output
Scaled Laplacian image

5. How to enhance the profile?

6. Sharpening with Laplacian

7. Image sharpening with Laplacian
Blurred image

8. Laplacian kernels 1 -4 -1 4 1 -8 -1 8

9. Unsharp masking

10. Gradient for enhancement
Gradient of f(x,y):
Gradient magnitude:

11. Gradient kernels
Some of the gradient kernels are: -1 1 1 -1

12. Detecting discontinuities using gradient

13. Gradient magnitude of a profile+ -

14. Gradient kernels 1 -1 2 -2 -1 -2 1 2 Sobel gradient masks-1 2 -2 -1 -2 1 2
Sobel gradient masks
Gradients are used for edge detection rather then sharpening