To know the basic components of an image processing system.
To understand how images are represented; including optical images, analog images, and digital images. Understand image types such as binary images, gray-scale images, color and multi-spectral images.
To understand why preprocessing is performed and know about image geometry, convolution masks, image algebra and basic spatial filters.
To understand image quantization in both the spatial and brightness domains.
To understand how discrete transforms work.
To understand lowpass, highpass, bandpass and notch filters.
To know the three categories of image processing applications: enhancement, restoration and compression.
Prerequisite(s)
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Corequisite(s)
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Special Requisite(s)
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Instructor(s)
Assist. Prof. Dr. Ertuğrul Saatçi
Course Assistant(s)
Schedule
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Office Hour(s)
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Teaching Methods and Techniques
The module will be delivered in a series of lectures, supported by practical sessions and self-directed study on the part of the student. The course is taught by lectures at the rate of 2 hours and 2 hours practical sessions per week.
A part of the lectures will consist of delivery of the course material using powerpoint.
The lectures will follow a textbook and will contain supporting material for the practical sessions. The practical sessions will consist of a set of experiment using MATLAB programming language.
The lectures will include discussion questions which will be used to stimulate in-class discussion.
Principle Sources
“Digital Image Processing”, Third Edition, Gonzalez and Woods, Prentice Hall, 2008.
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction and Motivation
Oral presentation
2. Week
Visual perception, light and EM spectrum, Mathematical model of an image, Image sensing and acquisition
Oral presentation, Laboratory
3. Week
Introduction to MATLAB
Oral presentation, Laboratory
4. Week
Linear Systems, Convolution, Correlation, Impulse Response
Oral presentation, Laboratory
5. Week
Fourier transform and its properties, The frequency concept in an image and its frequency spectrum, Sampling of an image, aliasing and conditions on sampling frequency, Construction of an image from sinusoidal plane waves
Oral presentation, Laboratory
6. Week
Image Enhancement in the spatial domain: Pixel-Point Operations such as lightening, darkening, changing the contrast (histogram enhancement)
Oral presentation, Laboratory
7. Week
Image Enhancement in the spatial domain: Pixel-Group Operations such as convolution operation and related concepts as the convolution mask and the impulse response.
Oral presentation, Laboratory
8. Week
Midterm I
9. Week
Image Enhancement in the frequency domain
Oral presentation, Laboratory
10. Week
Image Enhancement in the frequency domain continued
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1
Demonstrate an understanding of the digital image fundamentals including image capture system, representation, format and human vision perception.
LO-2
Apply image processing techniques in both spatial domain and spatial frequency domain to solve image processing problems.
LO-3
Compare different approaches to solving the same image processing tasks.
LO-4
Implement image processing algorithms on the computer by MATLAB.
LO-5
Distinguish appropriate image processing techniques to solve image processing problems.
