1. Lecture # 19 Image Processing II

3. 2 Classes of Digital Filters Global filters transform each pixel uniformly according to the function regardless of its location in the image Local filters transform a pixel depending upon its relation to surrounding ones

4. Global Filters: REVIEW Brightness and Contrast control Histogram thresholding Histogram stretching or equalization Color corrections Inversions

5. Local Filters  Blurring Sharpening Unsharp Masking Edge and line detection Noise filters

6. Blurring Algorithm For (every pixel in column x) {For (every pixel in row y of column x) { average image[x,y] with it ’ s neighbors; }

7. Blurring Average each pixel with its neighbors by : multiplying each pixel and its neighbors by 1: = - add multiplied pixels and divide by 9 - store result in a new array The new array contains a blurred image. 111 111 111

8. Gaussian Blur Multiply neighbors by less than middle

9. Blur Demo Photoshop –Filter->Blur->Blur –Filter->Blur->Gaussian Blur

10. Local Filters Blurring  Sharpening  Unsharp Masking Edge and line detection Noise filters

11. Subtract neighboring pixels by : multiplying each pixel and its neighbors by: = - add multiplied pixels - store result in a new array The new array contains a sharpened image. Sharpening 00 00 +5

12. Unsharp Masking Unsharp masking also sharpens an image The Algorithm: 1. call the original (unblurred) image A 2. blur the image (call it B) 3. subtract B from the unblurred image (let C = A-B) 4. Multiply C by some number, k (k > 1) 5. Sharpened Image = A + kC

13. Sharpen/Unsharp mask Photoshop –Filter->Sharpen->Sharpen –Filter->Sharpen->Unsharp mask

14. Local Filters Blurring Sharpening Unsharp Masking  Edge and line detection Noise filters

15. Edge and Line Detection Multiply each pixel and its neighbors by the following corresponding patterns (numbers) - add results - clip to 255 - result = “ Edge ” image 0 +1 0 0 +1 0 0 +1 0 Gets Gets Vertical Edges Horizontal Edges

16. Edge Detection edge detection is often used to recognized objects of interest in the image

17. Edge Detection Photoshop –Filter->Stylize->Find Edges

18. Local Filters Blurring Sharpening Unsharp Masking Edge and line detection  Noise filters

19. Noise Filters A median filter takes away “ salt & pepper ” noise (speckles)

20. Noise Filter Photoshop –Filter->Noise->Median Filter

21. Kernel Filtering 111 111 111 Blur 00 00 +5 Sharpen 0 +1 0 0 +1 0 0 +1 0 Edges Apply same algorithm at every pixel using different kernel values

22. Image Editing

23.  Selection Tools Painting Tools Cut & Paste Cloning Layers and Blending

24. Selection Tools Lasso Tool - manually draw outline (free hand) - manually outline (line segments) - magnetic lasso (semi-automated) Magic Wand DEMOS Tool Bar

25. Image Editing Selection Tools  Painting Tools Cut & Paste Cloning Layers and Blending

26. Painting Tools Airbrush Tool Paint Bucket Tool Paintbrush Tool Pencil Tool DEMOS

27. Image Editing Selection Tools Painting Tools  Cut & Paste Cloning Layers and Blending

28. Cut & Paste Word Processors - cut & paste strings of characters (1D arrays) Image Editing - cut & paste pixels (2D arrays) - replace old pixels with new pixels

29. Image Editing Selection Tools Painting Tools Cut & Paste  Cloning Layers and Blending

30. Cloning Copy pixels from one part of an image - to another part of an image... Interactively DEMO

31. Image Editing Selection Tools Painting Tools Cut & Paste Cloning  Layers and Blending

32. Can create arbitrary number of layers for - animation - special effects in movies - morphing Layers and Blending Layer 1 Layer 2 Layer n

33. The idea: Blended image =.3 x +.7 x is a weighted combination (sum) of two or more other images. Blending

34. Example Blend.3 x+.7 x = Bearastronaut

35. The idea: Create another image where the value of pixels is the weighting term for a blend operation: Masking

36. Summary Digital Images and pixels Digitize a picture by –Sampling –Quantization Color Models –RGB, CMYK, and HSB Storage Formats –.gif,.jpg,.png,.bmp

37. Summary Global Filters –Contrast & Brightness Control –Thresholding –Histogram stretching & equalization –Color corrections –Inversion

38. Summary Local filters –Blurring –Sharpening –Unsharp Masking –Edge and line detection –Noise filters

39. Summary Image Editing –Selection Tools –Painting Tools –Cut & Paste –Cloning –Layers and Blending