NATIONAL CHENG KUNG UNIVERSITY Inst. of Manufacturing Information & Systems DIGITAL IMAGE PROCESSING AND SOFTWARE IMPLEMENTATION HOMEWORK 1 Professor name: Chen, Shang-Liang Student name: Nguyen Van Thanh Student ID: P96007019 Class: P9-009 Image Processing and Software Implementation Time: [4] 2 4
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Digital Image Processing Using Matlab: Basic transformations, filters, operators
Negative transformation Log transformation Power-law transformation Piecewise-linear transformation Histogram equalization Subtraction Smoothing Linear Filters Order-Statistics Filters The Laplacian The Gradient
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NATIONAL CHENG KUNG UNIVERSITY
Inst. of Manufacturing Information & Systems
DIGITAL IMAGE PROCESSING AND SOFTWARE
IMPLEMENTATION
HOMEWORK 1
Professor name: Chen, Shang-Liang
Student name: Nguyen Van Thanh
Student ID: P96007019
Class: P9-009 Image Processing and Software Implementation
Time: [4] 2 4
1
Table of Contents PROBLEM ................................................................................................................................................................. 2
3.7.2 The Laplacian ............................................................................................................................................ 17
3.7.3 The Gradient ............................................................................................................................................. 19
(g15), figure, imshow (g35), figure; h = imread ('Fig3.36(a).jpg'); h15 = imfilter (h, w15, 'conv', 'replicate', 'same'); [m, n] = size (h15); for i = 1:m for j = 1:n if ((h15 (i,j)>=0) & (h15 (i,j)<128)) g (i,j) = 0; else g(i,j) = 255; end end end imshow(h15), figure, imshow(g);
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Fig. 3.35 (a) Original image, of size 500 x 500 pixels. (b) – (f) Result of
smoothing with square averaging filter masks of size n = 3, 5, 9, 15,
and 35 respectively.
a b
c d
e f
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3.6.2 Order-Statistics Filters
The commands,
>> f = imread('Fig3.37(a).jpg'); w3 = 1/(3.^2)*ones(3); g3 = imfilter(f, w3, 'conv', 'replicate', 'same'); g = medfilt2(g3); imshow(g3), figure, imshow(g);
a b c Fig. 3.36 (a) Original image. (b) Image processed by a 15 x 15 averaging mask.
(c) Result of thresholding (b)
Fig. 3.37 (a) X – ray image of circuit board corrupted by salt – and –
pepper noise. (b) Noise reduction with a 3 x 3 averaging mask. (c)
Noise reduction with a 3 x 3 median filter
a b c
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3.7.2 The Laplacian
The Laplacian for image enhancement is as follows: