2. ???

3. Eyes Brain (Inside) Conclusion: Ideally Suited for Image Processing

4. May Look Ideally Suited for Image Processing……But They’re Not

5. Filtering Images Creates new image Each pixel is based on the corresponding pixel and its neighbors in the old image Filters can be used to clean images “Noisy” Picture Average Filter: Each pixel in new image will be the average (mean) of a region of pixels in the old image. Cleaned Picture Median Filter: Each pixel in new image will be the median of a region of pixels in the old image.

6. Feature Detection What are features? A feature is something that catches our eye in an image

7. Laplacian Filter Laplacian filter is a filter looking like this: The Laplacian filter detects points (or areas) that are different from their surrounding. Us humans see the world Through Laplacian filter

8. Feature detection in action narrow filter small features wide filter large features

9. The Problem of Scale The computer can easily fill in small gaps in the image to clean up noise. There are problems with larger gaps. Solution: Work on different scales. Filter Picture With Larger Bad PieceJust Filtering is Not Effective!

10. Gaussian Pyramids G 0 = Original Image G N, N > 0 = Reduced Image G0G0 G1G1 G2G2 … Expand Low DetailMuch Higher Detail

11. Using Filters As Pyramids Filters can accomplish the same blurring as Gaussian pyramids. Gaussian filters create this blurring effect by emphasizing the corresponding pixel’s neighbors more than the corresponding pixel Apply Large, Strong Gaussian Filter Lower Detail Apply Small, Weak Gaussian Filter

12. Approximations G 0 s of similar images = quite different G N s of similar images are closer than G 0 s Find G N s with Large N Very Slightly SimilarSlightly More Similar

13. Image Completion Method for Image Completion –Repeat with N from a large number to 0 Obtain a filtered version of G N, enlarged to the original size (Using filters or a Gaussian pyramid) Reintroduce the good pixels from the incomplete image Incomplete Image Mask (Marks Valid Pixels) Complete Image

14. Another Example Can you see the Einstein in 100 random lines? Incomplete Image Mask (Marks Valid Pixels) Complete Image

15. Limitations This method does not work as well on drawings because drawings can have more unpredictable changes in color. Incomplete Image Mask (Marks Valid Pixels) Complete Image

16. Resizing Images Our task was making images smaller. Why? One reason is to transmit the image over the internet faster.

17. But how do you resize an image? There a few methods to resize images and to reduce their number of pixels: The simplest reduce method is to use the ‘uniform grid’

18. Adaptive Sub-sampling To keep more pixels where details are finer Using Feature Detection to sample (take) more pixels near features Non-uniform grid

22. No questions please