Course contents: Digital image - digitizing two-dimensional signals (2D). Two-dimensional transforms (Fourier, Z, DFT, etc.) and 2D filters. Image analysis and processing, size modification, contrast/brightness modification, histogram and equalization. Techniques and methods for image segmentation, edge detection, contour and point of interest detection. Tools for image restoration, de-noising, color enhancement, reconstruction. Applications using software (e.g. MatLab).

Assessment: Written exams at the end of the semester which will contribute 60% to the final grade. Laboratory reports and/or oral examination which will contribute 40% to the final grade. The aforementioned percentages may vary by ±10% depending on the requirements of the laboratory work each academic year.