Signal and Image Processing, 6 credits

Signal- och bildbehandling, 6 hp

TSBB14

Course starting semester

Main field of study

Biotechnology Electrical Engineering

Course level

First cycle

Course type

Programme course

Examiner

Maria Magnusson

Director of studies or equivalent

Klas Norberg

Education components

Preliminary scheduled hours: 71 h
Recommended self-study hours: 89 h

Possible deviation from course syllabus/programme syllabus

ECV = Elective / Compulsory / Voluntary

Course offered for		Semester	Period	Timetable module	Language	Campus	ECV
6CTBI	Engineering Biology, M Sc in Engineering	5 (Autumn 2017)	1, 2	3, 3	Swedish	Linköping, Valla	C

Main field of study

Biotechnology, Electrical Engineering

Course level

First cycle

Advancement level

G2X

Course offered for

Engineering Biology, M Sc in Engineering

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

One- and multidimensional calculus, Programming.

Intended learning outcomes

The course intends to give fundamental knowledge about signal and image processing. It is then used to solve application oriented problems in technique, medicine and biology. This means that a student which has taken this course is expected to be able to:

Describe basics regarding 1-D signal processing: deterministic signals, convolution, continuous and discrete linear systems, continuous and discrete Fourier transform, sampling and reconstruction, the sampling theorem, aliasing, basic filters (low-pass, high-pass, and band-pass).
Perform computations on signals and systems by using the following techniques: convolution, Fourier series, Fourier transform and z-transform (simple problems).
Describe basics regarding the generalization from 1-D to 2-D signal processing: Continuous and discrete Fourier transform with accompanying theorems, sampling and reconstruction, convolution, re-sampling and interpolation.
Interpret the result of a 2-D Fourier transform of an image, such as what is a spatial frequency? Be acquainted with the most common convolution kernels and describe their appearance in the spatial and Fourier domain, respectively.
Describe some classical operations for image processing such as histogram, thresholding and morphological operations. Understand how measurements such as area, length and perimeter can be performed in images.
Produce an oral and Power-Point presentation in English or Swedish of an application related to the theory described in the course.

Course content

1-D signal processing: Signals and their characteristics. Fourier series. Convolution. The Fourier transform and its accompanying theorems. TDFT and DFT. The Dirac impulse. Sampling and reconstruction. The z-transform. 1D correlation. Continuous and discrete linear systems. System characteristics such as linearity, time invariance, causality and stability.
2-D signal processing: From 1-D to 2-D Fourier transform. Continuous and discrete Fourier transform, TDFT and DFT. Sampling and reconstruction. Convolution and filtering, translation, scaling, derivative, rotation, and other linear operations on digital images. Convolution kernels in the spatial and Fourier domain, low-pass, high-pass, and derivative (sobel). Edge detection using the magnitude of the gradient. Re-sampling and interpolation. Histogram and thresholding. Binary image processing. 2-D correlation.
Application examples: Signal processing of ECG-signal, computed tomography (CT), magnetic resonance imaging (MRI), 3-D visualization, analysis of microscopy images, image compression, signal processing in a CD-player, phase vocoder.

Teaching and working methods

The course consists of lectures, lessons, laboratory assignments based on Matlab, and a group project concerning an application studied by literature and laboratory Matlab work. The group project is examined with an oral and Power-Point presentation in English or Swedish.
The course runs over the entire autumn semester.

Examination

LABA	Laboratory work	2.5 credits	U, G
TENA	Written examination	3.5 credits	U, 3, 4, 5

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för systemteknik

Director of Studies or equivalent

Klas Norberg

Examiner

Maria Magnusson

Course website and other links

https://www.cvl.isy.liu.se/education/undergraduate

Education components

Preliminary scheduled hours: 71 h
Recommended self-study hours: 89 h

Course literature

Additional literature

Books

Compendia

Laborationshäfte: Signal- and Image Processing.
Signal- och bildbehandling.

Code	Name	Scope	Grading scale
LABA	Laboratory work	2.5 credits	U, G
TENA	Written examination	3.5 credits	U, 3, 4, 5

Regulations (apply to LiU in its entirety)

The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.

LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.

Student rights and obligations (login required)
Linköping University common rules and regulations (in Swedish)

Course literature is preliminary.

Additional literature

Books

Compendia

Laborationshäfte: Signal- and Image Processing.

Signal- och bildbehandling.

Download

Download course literature list as PDF

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize

		I	U	A	Modules
1. DISCIPLINARY KNOWLEDGE AND REASONING
	1.1 Knowledge of underlying mathematics and science (G1X level)			X
	1.2 Fundamental engineering knowledge (G1X level)	X	X	X	LABA TENA
	1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)	X	X		LABA TENA
	1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)
	1.5 Insight into current research and development work
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
	2.1 Analytical reasoning and problem solving		X	X	LABA TENA
	2.2 Experimentation, investigation, and knowledge discovery		X	X	LABA
	2.3 System thinking
	2.4 Attitudes, thought, and learning		X	X	TENA
	2.5 Ethics, equity, and other responsibilities
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
	3.1 Teamwork			X
	3.2 Communications		X	X	LABA
	3.3 Communication in foreign languages			X
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
	4.1 External, societal, and environmental context
	4.2 Enterprise and business context
	4.3 Conceiving, system engineering and management	X	X	X	LABA
	4.4 Designing	X	X	X	LABA
	4.5 Implementing	X	X	X	LABA
	4.6 Operating
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
	5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development
	5.2 Economic conditions for knowledge development
	5.3 Identification of needs, structuring and planning of research or development projects
	5.4 Execution of research or development projects
	5.5 Presentation and evaluation of research or development projects

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