4 RequirementRead n>2 images, and create an image mosaic by registering, projective warping, resampling, and compositing them.(bonus) multiband blending, SIFT ,panorama or other methods mentioned in class.
6 Steps Shoot the Pictures Recover Homographies Warp the Images/ Image RectificationGain CompensationBlend the images into a mosaic
7 Shoot the PicturesYou may use the photos on the webpage, but shoot your own photos and mosaic them will get bonus credit.Shoot photos as:Overlap the fields of view significantly. 40% to 70% overlap is recommended.
8 Recover HomographiesConstruct a linear system as: p’=Hp, where p’ and p are correspondence points.Follow the Lecture 8 page 6~9. You may try Affine mappings(DOF=6) or Projective mappings(DOF=8).Solve Ax=0
9 Warp the Images/Image Rectification Source scanning(forward mapping) or destination scanning(inverse mapping).You will need to avoid aliasing when resampling the image.Be careful of the size of the resulting image.
10 Gain CompensationFind the optimize gains of gi according to means of overlapping regions between image pair i and j.
11 Blend the images into a mosaic Linear blending by the weights:where w(x) varies linearly from 1 at the centre of the image to 0 at the edge.Multi-band blending (bonus):AB𝐼(𝑥,𝑦)= 𝐼𝑎∗ 𝑊−𝐷𝑎 +𝐼𝑏∗(𝑊−𝐷𝑏) 𝑊−𝐷𝑎 +(𝑊−𝐷𝑏)
12 Multi-band blending Band 1 scale 0 to σ Band 2 scale σ to 2σ Band 3 lower than 2σ
13 Support Your own project1a code. A C called matlab library. to calculate inverse matrix , SVD or etc.