Image Processing with Matlab (3 ECTS)

Learning outcomes

Knowledge and understanding:
The student will know filtering in both the spatial domain and the frequency domain through exercising mathematical calculation such as convolution and the Discrete Fourier Transform, applying their knowledge to edge detection, image enhancement, noise reduction and so on, including lowpass filtering and highpass filtering.

Skills:
The student is able to understand basic image processing techniques and use MATLAB programs for them.

Content

Core content level:
How to handle Digital Images in MATLAB, Intensity Transformations, Geometric Spatial Transformations, Linear Spatial Filtering, Nonlinear Spatial Filtering, Convolution, Complex valued plane, Euler’s formula, the Discrete Fourier Transform, Noise Reduction, Lowpass Filtering, Highpass Filtering

Additional content:
Image Restoration

Prerequisites

Fundamental engineering mathematics

Further information for students

Summer School course

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

The student understands filtering in both the spatial domain and the frequency domain after performing mathematical calculation exercises.

Assessment criteria, good (3)

The student can apply filtering in both the spatial domain and the frequency domain after performing mathematical calculation exercises.

Assessment criteria, excellent (5)

The student can apply filtering in both the spatial domain and the frequency domain via the Fourier Transform and utilize those methods in edge detection, image enhancement and noise reduction, including lowpass filtering and highpass filtering.

Assessment criteria, approved/failed

The student understands filtering in both the spatial domain and the frequency domain. / The student does not understand filtering.