Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview: This course provides a beginner-friendly introduction to image and video processing, combining foundational theory with hands-on Python practice. Over five weekly modules and a final project, learners explore how digital images are created, enhanced, filtered, transformed, and analyzed. Each module builds step-by-step from basic concepts to practical implementation, culminating in a project that applies learned techniques to real-world scenarios in medicine, space, or entertainment. Total time commitment is approximately 25–30 hours.
Module 1: Introduction to Digital Images
Estimated time: 5 hours
- Pixels and image resolution
- Grayscale vs. color images
- Image file formats (JPEG, PNG, TIFF)
- Viewing and manipulating raw image data in Python
Module 2: Image Enhancement
Estimated time: 5 hours
- Understanding image histograms
- Contrast stretching techniques
- Thresholding for image binarization
- Improving visibility and brightness in images
Module 3: Filtering and Edge Detection
Estimated time: 6 hours
- Smoothing filters (e.g., Gaussian, box filters)
- Sharpening filters
- Sobel edge detection method
- Laplacian and second-order derivative filters
Module 4: Geometric Transformations
Estimated time: 5 hours
- Scaling and resizing images
- Rotation and translation
- Affine transformations
- Correcting image perspective and alignment
Module 5: Image Segmentation & Morphology
Estimated time: 6 hours
- Binary image processing
- Region labeling and connected components
- Morphological operations (erosion, dilation)
- Segmenting and labeling objects in images
Module 6: Final Project
Estimated time: 8 hours
- Apply image enhancement and filtering to a real-world dataset
- Perform segmentation on medical, satellite, or cinematic imagery
- Submit a Python notebook with analysis and visual results
Prerequisites
- No prior knowledge of image processing required
- Basic familiarity with Python programming
- Willingness to learn through hands-on coding
What You'll Be Able to Do After
- Understand how digital images are formed and represented
- Apply core image processing techniques like filtering and enhancement
- Analyze images using Python-based tools
- Perform basic image segmentation and object recognition
- Build foundational skills for computer vision and deep learning