Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 10, Date : 21/12/2011
-
Sheet 10 solution
1.
Image sharpening could be done in spatial domain using spatial filtering. The
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 9, Date : 14/12/2011
-
Sheet 9 solution
1.
The blurring mask is an averaging mask which assigns a pixel a scaled sum of th
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Master students
Sheet 6, Date : 16/11/2011
-
Sheet 6 solution
1.
This is a linear mapping function to map r values linearly so that rmin=>0 and rmax=
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 9, Date : 14/12/2011
-
Sheet 9
1.
The three images shown below were blurred using square averaging masks of sizes n = 23,
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 10, Date : 21/12/2011
-
Sheet 10
1.
Explain one way for image sharpening
2.
In a given application an averaging mask is ap
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 7, Date : 23/11/2011
-
Sheet 7 solution (histogram equalization)
1.
(a)
( )
The integration
in the right hand side of the
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Master students
Sheet 8, Date : 7/11/2011
-
Sheet 8 solution (histogram equalization)
1.
First, we obtain the histogram equalization transformation:
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 8, Date : 7/12/2011
-
Sheet 8 (histogram equalization)
1.
An image with intensities in the range [0, 1] has the PDF
shown
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 7, Date : 23/11/2011
-
Sheet 7 (histogram equalization)
1.
Consider a continuous image with intensity values in the range
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 05, Date : 02/11/2011
-
Sheet 5
1.
2.
Determine if each of the following statements is true or not. If it is not, modify i
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 05, Date : 02/11/2011
-
Sheet 5 solution
1.
Item
A
B
C
D
E
answer The true statement if False
T
( )
F
An intensity mapping
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 4, Date : 26/10/2011
-
Sheet 4
1.
Prove that finding the maximum intensity value in a digital image is a nonlinear operati
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 4, Date : 26/10/2011
-
Sheet 4 solution
1.
An operation H on a digital image f(x, y) is linear if and only if it satisfies
Lecture 1
Introduction
Objectives
Digital image processing, Why?
Scope of digital image processing
Exploration of application areas
Components in a typical general-purpose image
processing system
Directions
Digital image processing application areas
Imp
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Master students
Sheet 3, Date : 19/10/2011
-
Sheet 3 solution
1.
Item
A
B
C
D
answer The true statement if False
T
F
When the acquisition of an image
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Master students
Sheet 2, Date : 12/10/2011
-
Sheet 2
1.
Thinking purely in geometric terms, estimate the diameter of the smallest printed dot that th
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 1, Date : 3/10/2011
-
Sheet 1 solution
1.
a)
Application examples for using electromagnetic waves in imaging include: body
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Master students
Sheet 3, Date : 19/10/2011
-
Sheet 3
1.
Determine if each of the following statements is true or not. If it is not, modify it to beco
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 2, Date : 12/10/2011
-
Sheet 2
1.
Thinking purely in geometric terms, estimate the diameter of the smallest printed dot th
Lecture 9
Fundamentals of spatial filters
Frequency domain and spatial domain
Spatial domain
A filter in spatial domain is a
mask/window/kernel/neighborhoo
d and an operation
While sliding the window on the
image , the operation is performed
at each pix
Lecture 6
Intensity transformation and spatial filtering
(basics and intensity mapping)
Covers sections 3.1 and 3.2 in digital image
processing by Gonzalez and Woods, 3ED, 2009)
Main categories of spatial processing
Spatial processing
Intensity transforma
Lecture 3
Digital Image Fundamentals:
Sampling/quantization, image models,
resolution and interpolation
Image sampling and quantization
Spatial: continuous to discrete (sampling)
Amplitude: continuous to discrete(quantization)
How many samples? On whic
Lecture 8
Histogram specification and local
histogram processing
Histogram matching (specification)
Image with arbitrary
histogram
Histogram
equalization
procedure
Image with equalized
histogram
Histogram
specification
procedure
Image with the
specified h
Tanta university
Faculty of engineering
Computer and automatic control department
Image processing course
Fourth year students
Sheet 1, Date : 3/10/2011
-
Sheet 1 (Introduction)
1.
Electromagnetic and acoustic are two different imaging modalities. The sou
Lecture 4
Digital image fundamentals:
Mathematical tools (array and matrix operations,
linear and nonlinear operations, arithmetic
operation, sets and logic operation)
Mathematic operations on images
Array or matrix operations?
Array operation (default)
Lecture 7
Histogram processing
Warning: this is a draft copy. It has not been passed any revision
Histogram
For a digital image with intensity levels in the
interval [0,L-1],
Histogram is a discrete function h(rk)=nk ,
where
rk is the kth intensity valu
Lecture 2
Human visual system & Light characterization
Image acquisition
Digital image model
Elements of visual system:
Human eye structure
Cornea: tough, transparent tissue that cover the enterior
of the eye
Sclera: Opaque membrane the encloses the rem
Lecture 5
Mathematical tools for image processing,
continued
Spatial versus transform operations
Spatial operations are performed in spatial domain
Image is represented as f(x,y)
X=0,1,2,M
Y=0,1,2,N
Single pixel based operations, neighborhood operations,
