| TSBB14 |
Signal and Image Processing, 6 ECTS credits.
/Signal- och bildbehandling/
For:
TB
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Prel. scheduled
hours: 71
Rec. self-study hours: 89
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Area of Education: Technology
Main field of studies: Electrical Engineering
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Advancement level
(G1, G2, A): G2
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Aim:
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.
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Prerequisites: (valid for students admitted to programmes within which the course is offered)
One- and multidimensional calculus, Programming.
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshhold requirements for progression within the programme, or corresponding.
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Organisation:
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.
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Course contents:
- 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.
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Course literature:
Compendium: Signal- och Bildbehandling (in Swedish).
Lecture Power-points.
Laboratory instructions: Signal- and Image Processing.
In-depth literature can for example be Oppenheim: Signals and systems. Prentice-Hall.
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Examination: |
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A written examination
Laboratory work
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3,5 ECTS
2,5 ECTS
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Course language is Swedish.
Department offering the course: ISY.
Director of Studies: Klas Norberg
Examiner: Maria Magnusson
Link to the course homepage at the department
Course Syllabus in Swedish
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