The goal of this part is to create an image mosaic by doing projective warping, resampling and composing the images together.
In order to test that the homography and inverse warping work correctly, we will take a few sample images with planar surfaces and warp them to get a frontal-parallel plane. The first example is a picture of a Berkeley 150 poster. Here is the picture.
Berkeley 150 Poster
Rectifiied Berkeley 150 Poster
Cal Seal and the rectifiied image
For this part of the project we are going to stitch a few images into a mosaic. The idea is to define several corresponding points between the images. I used 3 images for this part and I had two sets of corresponding points for the first and second images, and the second and third images. The first set of points are for approximating the first homography matrix using the least squares. After calculating the homography we stitch the first two images together. Then we repeat the same logic and actions to stitch the third one on the already warped image. For combining the warped images, I used the element-wise maximum of the warp images, which gave better results than linear blending.
These are the 3 images from downtown berkeley Bart station.Downtown Berkeley
Downtown Berkeley Mosaic of 12 and 23
Downtown Berkeley Mosaic
The Memorial Glade
Downtown Berkeley Mosaic