1. MATLAB Image Processing Toolbox

2. Presented By Muhammad ikram ul haq BCS-F07-M032 5th Semester

3. Introduction • Collection of functions (MATLAB files) that supports a wide range of image processing operations • Documentation • www.mathworks.com

4. Read an Image • Read in an image • Validates the graphic format (bmp, hdf, jpeg, pcx, png, tiff, xwd) • Store it in an array clear, close all I = imread(‘pout.tif`); [X, map] = imread(‘pout.tif’);

5. Display an Image imshow(I)

6. Check the Image in Memory • < Name, Size, Bytes, Class > whos Name Size Bytes Class ans 291x240 69840 uint8 array Grand total is 69840 elements using 69840 bytes

7. Histogram Equalization • Histogram: distribution of intensities figure, imhist(I) • Equalize Image (contrast) I2 = histeq(I); figure, imshow(I2) figure, imhist(I2)

8. Histogram Equalization (cont.)

9. Histogram Equalization (cont.)

10. Write the Image • Validates the extension • Writes the image to disk imwrite(I2, ’pout2.png’); imwrite(I2, ‘pout2.png’, ‘BitDepth’, 4);

11. Morphological Opening • Remove objects that cannot completely contain a structuring element • Estimate background illumination clear, close all I = imread(‘rice.tif’); imshow(I) background = imopen(I, strel(‘disk’, 15)); imshow(background)

12. Morphological Opening (cont.)

13. Subtract Images • Create a more uniform background I2 = imsubtract(I, background); figure, imshow(I2)

14. Adjust the Image Contrast • stretchlim computes [low hight] to be mapped into [bottom top] I3 = imadjust(I2, stretchlim(I2), [0 1]); figure, imshow(I3)

15. Apply Thresholdingto the Image • Create a binary thresholded image • Compute a threshold to convert the intensity image to binary • Perform thresholding creating a logical matrix (binary image) level = graythresh(I3); bw = im2bw(I3, level); figure, imshow(bw)

16. Apply Thresholdingto the Image (cont.)

17. Storage Classes • double (64-bit), uint8 (8-bit), and uint16 (16-bit) • Converting (rescale or offset) double im2double (automatic rescale and offsetting) RGB2 = im2uint8(RGB1); im2uint16 imapprox (reduce number of colors: indexed images)

18. Image Types • Index • Data matrix (uint8, uint16, double) • Colormap matrix (m x 3 array of double [0 1]) • Intensity (black = 0, white = ) • Binary (0, 1) B = logical(uint8(round(A))); (logical flag on) B = +A; (logical flag off) • RGB (m x n x 3 of truecolor)

19. dither gray2ind grayslice im2bw ind2gray ind2rgb mat2gray rgb2gray rgb2ind Converting Image Types

20. Multiframe Image Arrays • Same size, #planes, colormap • Store separate images into one multiframe array A = cat(4, A1, A2, A3, A4, A5) • Extract frames from a multiframe array FRM3 = MULTI(:, :, :, 3) • Display a frame imshow(MULTI(:, :, :, 7))

21. imabsdiff imadd imcomplement imdivide imlincomb immultiply imsubtract Image Arithmetic

22. Adding Images I = imread(‘rice.tif’); J = imread(‘cameraman.tif’); K = imadd(I, J); imshow(K) • Brighten an image results saturation RGB = imread(‘flowers.tif’); RGB2 = imadd(RGB, 50); subplot(1, 2, 1); imshow(RGB); subplot(1, 2, 2); imshow(RGB2);

23. Adding Images (cont.)

24. Adding Images (cont.)

25. Subtracting Images • Background of a scene rice = imread(‘rice.tif’); background = imopen(rice, strel(‘disk’, 15)); rice2 = imsubtract(rice, background); imshow(rice), figure, imshow(rice2); • Negative values imabsdiff

26. Subtracting Images (cont.)

27. Multiplying Images • Scaling: multiply by a constant • (brightens >1, darkens <1) • Preserves relative contrast I = imread(‘moon.tif’); J = immultiply(I, 1.2); imshow(I); figure, imshow(J)

28. Multiplying Images (cont.)

29. Dividing Images (Ratioing) I = imread(‘rice.tif’); background = imopen(I, strel(‘disk’, 15)); Ip = imdivide(I, background); imshow(Ip, []) • Linear combination only truncates the final result K = imlincomb(.5, I, .5, I2);

30. Dividing Images (cont.)

31. Pixel Coordinates Discrete unit (integer) (r, c)  = (1, 1) Spatial Coordinates Continuous unit (x, y) = (0.5, 0.5) Coordinate Systems 123

32. Non-default Spatial Coordinate System A = magic(5); x = [19.5 23.5]; y = [8.0 12.0]; image(A, ‘xData’, x, ‘yData’, y), axis image, colormap(jet(25))

33. Spatial Transformations • Map pixel locations in an input image to new locations in an output image • Resizing • Rotation • Cropping

34. Resizing Images • Change the size of an image I = imread(‘ic.tif’); J = imresize(I, 1.25); K = imresize(I, [100 150]); figure, imshow(J) figure, imshow(K)

35. Resizing Images (cont.)

36. Rotating Images • Rotate an image by an angle in degrees I = imread(‘ic.tif’); J = imrotate(I, 35, ‘bilinear’); imshow(I) figure, imshow(J)

37. Rotating Images (cont.)

38. Cropping Images • Extract a rectangular portion of an image imshow ic.tif I = imcrop;

39. Ending Question