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.
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 3 hours 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
R. C. Gonzalez, R. E. Woods, Digital Image Processing, 4th edition, Pearson, 2017.
A. K. Jain, Fundamentals of Digital İmage Processing, Prentice Hall, Addison-Wesley, 1989.
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction and Motivation
oral presentation, case study
2. Week
Visual perception, light and EM spectrum, Mathematical model of an image, Image sensing and acquisition
oral presentation, case study
3. Week
Linear Systems, Convolution, Correlation, Impulse Response
oral presentation, case study
4. 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, case study
5. Week
Fourier transform and its properties continued
oral presentation, case study
6. Week
Image Enhancement in the spatial domain: Pixel-Point Operations such as lightening, darkening, changing the contrast (histogram enhancement)
oral presentation, case study
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, case study
8. Week
Midterm I
oral presentation, case study
9. Week
Image Enhancement in the frequency domain
oral presentation, case study
10. Week
Image Enhancement in the frequency domain continued
an ability to apply knowledge from undergraduate and graduate engineering and other disciplines to identify, formulate, and solve novel and complex electrical/computer engineering problems that require advanced knowledge within the field
PO-2
knowledge of advanced topics within at least two subdisciplines of computer engineering
PO-3
the ability to understand and integrate new knowledge within the field;
PO-4
the ability to apply advanced technical knowledge in multiple contexts
PO-5
a recognition of the need for, and an ability to engage in, life-long learning
PO-6
the ability to plan and conduct an organized and systematic study on a significant topic within the field
PO-7
an ability to convey technical material through formal written reports which satisfy accepted standards for writing style
PO-8
the ability to analyze and use existing literature
PO-9
the ability to demonstrate effective oral communication skills
PO-10
the ability to stay abreast of advancements in the area of computer engineering
Learning Outcomes
LO-1
to understand the fundamental concepts of a digital image processing system
LO-2
to exploit and identify the analogies between 1D and 2D signal analysis and processing
LO-3
to analyze 2D signals in the frequency domain through the Fourier transform
LO-4
to design and implement algorithms for digital image processing operations
LO-5
to analyze and to compare the performance of digital image processing operations
