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CSE
Fall 2008
Lecture 5
Matlab and the Image Processing
Toolbox (continued)
Today
• Matlab and the Image Processing Toolbox
continued
Assignments
• Lab #1 due Wed. 9/24 by midnight
Matlab overview
• intro.m
Matlab overview – data types
• Data types
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins www.imageprocessingbook.com
Digital Image Processing Using MATLABDigital Image Processing Using MATLAB®®
Matlab overview – data types
• Converting between data types
– Ex: a = uint8(b)
• Double->uint
– Values < 0 mapped to 0
– Values > 255 mapped to 255
– Fractions discarded
• Be aware of this!
Matlab overview - vectors
• 1xN dimensional array is called a row vector
• Index of first element is 1 (not 0)
• Initialize using square brackets
v = [1 3 5 7 9] v = 1 3 5 7 9
v(2) ans = 3
Matlab overview - vectors
• Convert row vector to column vector and
vice versa using transpose operator (‘)
w = v'
w =
1 3 5 7 9
Matlab overview - vectors
• To access blocks of elements, use colon (:)
notation
v(1:3) ans =
1 3 5
v(3:end) ans =
5 7 9
Matlab overview - vectors
• Indexing not restricted to contiguous elements
v(1:2:5) ans =
1 5 9
v(5:-2:1) ans =
9 5 1
Matlab overview - vectors
• Colon by itself returns column vector
v(:)
ans =
1 3 5 7 9
Matlab overview - vectors
• Can index into a vector using a vector
v([1 4 5])
ans =
1 7 9
Matlab overview - matrices
• Can use comparison operators to index
>> A(B==0)
ans =
3 6 9
E = (B==0) E = 0 0 1 0 0 1 0 0 1 whos E Name Size Bytes Class E 3x3 72 double array (logical) Grand total is 9 elements using 72 bytes
Matlab overview - matrices
• Use find function to determine indices of
values satisfying condition
[i,j] = find(B~=0); i' ans =
1 2 3 1 2 3
j' ans =
1 1 1 2 2 2
Matlab overview - matrices
• Use ndims to find dimension
d = ndims(A)
d =
2
Matlab overview - matrices
• Use size to find sizes of dimensions
size(T2) ans =
2 3
size(T2,1) ans =
2
size(T2,2) ans =
3
Matlab overview - matrices
• Can specify dimension for many functions
sum(T2) ans = 5 7 9 sum(T2,1) ans =
5 7 9
sum(T2,2) ans = 6 15
Matlab overview - matrices
• Can recurse to compute over all dimensions
sum(sum(T2))
ans =
21
Matlab overview – standard arrays
- zeros(M,N) -> MxN matrix of zeros of type double
- ones(M,N) -> MxN matrix of ones of type double
- rand(M,N) -> MxN matrix of uniformly distributed random numbers in the interval [0,1]
- randn(M,N) -> MxN matrix of normally (Gaussian) distributed random numbers with mean 0 and variance 1
Matlab overview – standard arrays
A = 5*ones(3,3) A =
5 5 5 5 5 5 5 5 5
B = rand(2,4)
B =
0.9501 0.6068 0.8913 0. 0.2311 0.4860 0.7621 0.
Matlab overview - .m file programming
Operators
• 3 types of operators
– Arithmetic operators that perform numeric
computations
– Relational operators that compare operands
quantitatively
– Logical operators that perform the functions
AND, OR, and NOT
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins www.imageprocessingbook.com
Digital Image Processing Using MATLAB Digital Image Processing Using MATLAB®®
Arithmetic operators I
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins www.imageprocessingbook.com
Digital Image Processing Using MATLABDigital Image Processing Using MATLAB®®
Arithmetic operators II
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins www.imageprocessingbook.com
Digital Image Processing Using MATLAB Digital Image Processing Using MATLAB®®
Relational operators
© 2004 R. C. Gonzalez, R. E. Woods, and S. L. Eddins www.imageprocessingbook.com
Digital Image Processing Using MATLABDigital Image Processing Using MATLAB®®
Flow control statements
• Preallocating arrays: use zeros() for example
Matlab overview - .m file programming
Code optimization – preallocating arrays
f ( ) x = A sin( x / 2 π ) for x = 0,1, … M − 1
f = zeros(M,1); % preallocate the array
for x=1:M f(x) = A * sin((x-1)/(2*pi)); end
for x=1:M f(x) = A * sin((x-1)/(2*pi)); end
or
• sin_no_preallocate.m
• sin_preallocate.m
Matlab overview - .m file programming
Code optimization – preallocating arrays
• Preallocating arrays
– Improves code execution time
– Helps reduce memory fragmentation
Matlab overview - .m file programming
Code optimization – preallocating arrays
• Vectorizing loops: converting for and while
loops to equivalent vector or matrix operations.
Matlab overview - .m file programming
Code optimization – vectorizing loops
f ( ) x = A sin( x / 2 π) for x = 0,1, … M − 1
for x=1:M f(x) = A * sin((x-1)/(2*pi)); end
x = 0:M-1; f = A * sin(x/(2*pi));
or
• sin_loop.m
• sin_vectorize.m
Matlab overview - .m file programming
Code optimization
Matlab overview - .m file programming
Interactive output I
>> A = [1 2; 3 4];
disp(A); 1 2 3 4
sc = 'Digital Image Processing'; disp(sc); Digital Image Processing
- fprintf(1,’format’,argument);
Matlab overview - .m file programming
Interactive output II
x = 5;
fprintf(1,'x = %.5f',x); x = 5.
fprintf(1,'x = %e',x); x = 5.000000e+
- t = input(‘message’, ‘s’)
Matlab overview - .m file programming
Interactive input
t = input('Enter you data: ','s'); Enter you data: 1,2, disp(t) 1,2, class(t) ans = char size(t) ans = 1 5 n=str2num(t) n = 1 2 4 class(n) ans = double size(n) ans = 1 3
Matlab overview - .m file programming
Plotting
