- Detailed the algorithm for edge highlighting, i.e., the output is the sum of the input image and the negation of the laplacian of the image.
- Show some results for this algorithm.
- Explain what this function does geometrically at image edge locations.
- Explain the algorithm, its mathematical formulation, and an example of its operation.
High Boost Filtering
- Explain the algorithm, its mathematical formulation, and some examples of its operation on images.
Handout on Edge Detection
- Revisit the edge detection problem.
- Explain 3 steps to generic edge detection.
- Discuss the tradeoff between supressing spurious edges, i.e., edges not associated with image structure, also called edges due to noise, and obtaining edge localization, i.e., and exact location of where the image edge occurred in the image.
- Discuss Canny, Roberts, and Sobel edge detectors.
- Discuss the algorithm for Non-Maximum suppression to localize the exact location of an edge in cases where multiple edges are detected in the vicinity of a single true edge.