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DREAM PLAN IDEA IMPLEMENTATION 1. 2 3 Introduction to Image Processing Dr. Kourosh Kiani

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Presentation on theme: "DREAM PLAN IDEA IMPLEMENTATION 1. 2 3 Introduction to Image Processing Dr. Kourosh Kiani"— Presentation transcript:

1 DREAM PLAN IDEA IMPLEMENTATION 1

2 2

3 3 Introduction to Image Processing Dr. Kourosh Kiani Web: Present to: Amirkabir University of Technology (Tehran Polytechnic) & Semnan University

4 Lecture 04 4

5 Algebraic operations used for images are commonly viewed in two groups; mathematical and logical operations. Image adding, subtracting, dividing and multiplying operations constitute mathematical processing and “AND, OR, NOT” etc. operations forms logical operations. SIMPLE ALGEBRAIC OPERATIONS in IMAGES

6 ……… …a4a3 …a2a1 ……… …b4b3 …b2b1 a4 +b4 a3 +b3 a2 +b2 a1 +b1 + = ……… …a4a3 …a2a1 a4 +10 a3 +10 a2 +10 a = 10

7

8 Reduce noise (increase SNR) averaging, smoothing =

9 I = imread(‘rice.tif’); J = imread(‘cameraman.tif’); K = imadd(I, J); imshow(K) Or i=imread('rice.png'); j=imread('cameraman.tif'); k=i+j; imshow(k);

10 I = imread('kourosh.jpg'); figure(1); imshow(I); I2 = imadd(I, 70); figure(2); imshow(I2); + 70 =

11 Image Averaging  Consider a noisy image g(x,y) formed by the addition of noise  (x,y) to an original image f(x,y) g(x,y) = f(x,y) +  (x,y)

12 Image Averaging  If noise has zero mean and is uncorrelated then it can be shown that = image formed by averaging K different noisy images

13 Image Averaging  Then = variances of g and   Then if K increase, it indicates that the variability (noise) of the pixel at each location (x,y) decreases.

14  Average multiple images (frames) of the same scene together  Useful for removing noise =

15 X = Y = Z = X = uint8([ ; ]); Y = uint8([ ; ]); Z = imsubtract(X,Y) Image Subtracting

16 rice = imread('rice.png'); figure (1) imshow(rice); background = imopen(rice, strel('disk', 15)); figure (2) imshow(background); rice2 = imsubtract(rice, background); figure (3) imshow(rice2); - =

17 - 70 = I = imread('kourosh.jpg'); J = imsubtract(I,70); Figure(1), imshow(I), Figure(2), imshow(J) Image Subtracting

18 _ = Digital subtraction angiography (DSA) Image Subtracting

19 Digital subtraction angiography (DSA) Image Subtracting

20 X = Y = Z = X = uint8([ ; ]); Y = uint8([ 5 5 5; ]); Z = immultiply(X,Y) Image Multiplying

21 I = imread('moon.tif'); figure(1) imshow(I) J = immultiply(I,0.5); figure(2) imshow(J) * 0.5 =

22 X = Y = Z = X = uint8([ ; ]) Y = uint8([ 5 5 5; ]) Z = imdivide(X,Y) Image Dividing

23 I = imread('rice.png'); figure(1), imshow(I); background = imopen(I,strel('disk',15)); figure(2), imshow(background); Ip = imdivide(I,background); figure(3), imshow(Ip, []); ÷ =

24 Image Dividing ÷ 2 = I = imread('rice.png'); J = imdivide(I,2); figure(1), imshow(I) figure(2), imshow(J)

25 Questions? Discussion? Suggestions ?

26 26


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