Panorama Creation by Image stitching Ms Sophea CHAN

Panorama Creation by Image stitching Ms. Sophea CHAN December 20, 2010

Theory Compositing Surface Image stitching process Resulting References Over View Theory Idea Compositing Surface Reference Image stitching process Image Registration Overlapped Area Blending Resulting References 12/13/2010 Sophea Chan 2

Theory Compositing Surface Image stitching process Resulting References Idea: Choose 2 images I 1(n 1 xm 1), I 2(n 2 xm 2) with overlapping fields of view. The main idea is to create a panorama images out of the input images. The approaches to create image stitching (panorama) require nearly exact overlaps between images and identical exposures to produce seamless results. 12/13/2010 Sophea Chan 3

Theory Compositing Surface Image stitching process Resulting References Over View Theory Idea Compositing surface Reference Image stitching process Image Registration Overlapping Area Blending Resulting References 12/13/2010 Sophea Chan 4

Theory Compositing Surface Image stitching process Resulting References Reference Image We select one of the images as a reference. It is the one that is geometrically most center. Other image is warped into the reference coordinate system. Image to be warped 12/13/2010 Reference Image Sophea Chan 5

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapping Area Blending Images Over View Theory Idea Training Compositing surface Image stitching process Image Registration Overlapping Area Blending Resulting References 12/13/2010 Sophea Chan 6

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapping Area Blending Images Image registration The purpose is to first extract distinctive features from each images, to match these features to a global correspondence, and to estimate the geometric transformation between the images. 1 - Extract feature 2 - Feature matching 3 - Align images (Compute Transformation Matrix) 12/13/2010 Sophea Chan 7

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images - Extract features Finding interest points of both images By using Harris Detector (Mathematics ). Window function 12/13/2010 Shifted intensity Intensity Sophea Chan 8

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images Features matching Using SIFT to extract the frames (interest Points) and the descriptors from the image I. (SIFT function is provided in the solution of exercise 4). 12/13/2010 Sophea Chan 9

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images - Overlapping area: Overlapping area between image 1 and image 2 12/13/2010 Sophea Chan 10

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapping Area Blending Images -Geometric Transformation (Homography) RANSAC is used to remove outliers. Compute Transformation Matrix T by projective transformation ( or homography). Shift Img = Original Image * T RANSAC function is Provided in the solution of exe. 4 Removed outlier by RANSAC 12/13/2010 Sophea Chan Shift Image 11

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images Technique 1: Featuring + Shift image + Reference Image = Mapped Image 12/13/2010 Sophea Chan 12

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images Technique 1: Featuring The median filter is an effective method that can suppress isolated noise without blurring sharp edges. y[m, n]=median{ x[i, j], (i, j) w } , w is represented a neighborhood centered around location in the image. Cutting Plan 12/13/2010 Median filtering n=m=5 Sophea Chan 13

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images Technique 2: Central weighting Compute the average value of each pixel. + 12/13/2010 Sophea Chan 14

Theory Compositing Surface Image stitching process Resulting References Image Registration Overlapped Area Blending Images Technique 2: Central weighting The median filter is an effective method that can suppress isolated noise without blurring sharp edges. y[m, n]=median{ x[i, j], (i, j) w } , w is represented a neighborhood centered around location in the image. Average 12/13/2010 Median filtering n=m=5 Sophea Chan 15

Output 1: Theory Compositing Surface Image stitching process Resulting References Out put Featuring image 1 image 2 Average 12/20/2010 Sophea Chan 16

Theory Compositing Surface Image stitching process Resulting References Output: Out put image 2 image 1 Featuring 12/20/2010 Average Sophea Chan 17

Theory Compositing Surface Image stitching process Resulting References Resources B. Ommer. Representation Feature. Object Recognition Lecture (Chapter 2), 2010. Richard Szeliski. Image Alignement and Stitching Technical Report MSR-TR-2004 -92 Last Updated, December 10, 2006. 12/20/2010 Sophea Chan 18

Theory Compositing Surface Image stitching process Resulting References Questions ? 12/20/2010 Sophea Chan 19

Theory Compositing Surface Image stitching process Resulting References End Thanks ! 12/20/2010 Sophea Chan 20