1. Depth from disparity
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- Evaluated two simple denoising algorithms, namely Gaussian filtering and median filtering.
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- In addition, also implemented a more advanced algorithm based on nonlocal means.
2. Scale-space blob detection
- Built a Laplacian scale space, starting with some initial scale and going for n iterations:
- (a) Filter image with scale-normalized Laplacian at current scale.
- (b) Save the square of Laplacian response for current level of scale space.
- (c) Increase scale by a factor k.
- Perform non-maximum suppression in scale space.
- Display resulting circles at their characteristic scales for points above a threshold.
3. Image stitching
- Implemented the RANSAC algorithm to stitch two images. The input to the algorithm are two images which are related by an unknown transformation.
- Used the blobs detector implemented to extract keypoints and extract feature descriptors on them.
- Then estimated an affine transformation using feature matching and RANSAC to produce a combined image.