| Description
| Digital Image Processing Practice is a hands-on course focusing on fundamental techniques widely used in modern image processing systems. The course begins with an overview of digital imaging concepts, followed by point processing, neighborhood processing, and Discrete Fourier Transform (DFT)-based frequency-domain analysis. Students will also learn essential methods for image enhancement, image restoration, and image segmentation.
The course emphasizes understanding algorithms and practical implementation through programming exercises using MATLAB or Python, covering both spatial-domain and frequency-domain processing techniques. This course is especially suitable for students who have taken Signals and Systems and who have taken or are currently taking Digital Signal Processing. It provides an essential foundation for entering the fields of computer vision and Artificial Intelligence/Machine-Learning-based image processing.
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