Home Assignment 4
Due on March 25, 2013
Exercise 1
In MATLAB, load the image liftingbody.png (variable f).
1. Simulate a motion blur lter of length 15 at an angle of 45 degrees using the MATLAB
function fspecial. Subsequently, apply the blur to the origin
Home Assignment 4
Due on February 13, 2012
Exercise 1
Load the Cameraman image using f = imread(cameraman.tif). Scale
the image intensity so that f [n, m] [0, 1] for all n and m. Using L = 4 bits
precision:
1. Perform a uniform quantization of the image t
Home Assignment 2
Due on January 27, 2011
Exercise 1
Consider an N M image f [n, m] with 0 n N 1 and 0 m M 1.
Let f be a lexicographically ordered (column stacked) version of f [n, m].
Note that in MATLAB, column stacking can be simply implemented using
t
Home Assignment
3
Due on February 6, 2012
Exercise 1
Consider an image f (x, y ) with Fourier spectrum F (u, v ) shown in Figure 1.
Figure 1: Fourier spectrum of f (x, y ).
1. Find a sampling scheme which will result in the minimum sampling
density for f
Home Assignment
6
Due on March 5th , 2012
Question 1
Load the cameraman image in MATLAB and assign it to the variable f. Contaminate the
image with zero mean additive white Gaussian noise (AWGN) of standard deviation 20 using
the command g=f+20*randn(size
Home Assignment 1
Due on January 18, 2012
Exercise 1
State, with reasons, whether the following systems are linear and shift invariant.
1. Hcfw_f [n, m] = f [2n n0 , 2m m0 ]
2. Hcfw_f [n, m] = f [n, m] + g [n, m]f [n 3, m 2] + 5
Exercise 2
Prove the follo
Home Assignment
10
Due on April 2th , 2012
Question 1
1. Let the real-random variables X and Y take the values xi , 1 i n and yi , 1 i n
respectively. The joint entropy between two random variables X and Y is dened as
n
n
H (X, Y ) =
p(xi , yj ) log2 [p(
Home Assignment
9
Due on March 26, 2012
Question 1
Let u RN be an N dimensional, real vector. Then its discrete cosine transform (DCT)
coecients U RN are dened as
1 N 1 u[n] cos (2n+1)k , k = 0
n=0
N
2N
[k ] =
(1)
U
N 1
2
u[n] cos (2n+1)k , k = 0
N
n=0
Home Assignment
8
Due on March 19th , 2012
Question 1
Consider a one dimensional signal f and a blurring kernel h. Let H be the convolution matrix
corresponding to the kernel h such that the matrix-vector product Hf gives the result of
convolution between
Home Assignment
7
Due on March 12th , 2011
Exercise 1
In MATLAB load the image liftingbody.png and assign it to the variable f. Check the
size of the image using [n,m]=size(f).
1. Simulate a motion blur lter of length 9 at an angle of 30 degrees using the
Home Assignment
3
Due on March 8, 2013
Exercise 1
Part A: Non-rectangular sampling/generalized sampling
Suppose that an image f : R2 R is sampled according to:
f [n] = f (x)|x=Dn = f (Dn),
n Z2 .
where D R22 is an invertible matrix (i.e., det(D) |D| = 0),
Home Assignment 2
Due on February 20, 2013
Remark: Consider using the subplot, xlabel, num2str, and axis image functions
of MATLAB when comparing images graphically.
Exercise 1
Load the cameraman image in MATLAB and assign it to the variable f. Contaminat
Home Assignment 1
Due on January 31, 2013
Exercise 1
In MATLAB, load the cameraman image using
f=imread(cameraman.tif);
and convert it into a double-precision array using the double command. (As a
general rule, if you want to know how to use a MATLAB func
Home Assignment 5
Due on February 20. 2012
Question 1
1. Download the image ctscan.png from the course website. In MATLAB, load the
image using imread.m and subsequently display it using, e.g., imagesc.m. You will see
that it is dicult to discern the deta