NDLI: Image mosaic with relaxed motion

Content Provider	Springer Nature Link
Author	Fang, Xianyong Zhu, Jiejie Luo, Bin
Copyright Year	2010
Abstract	We propose a novel method to stitch images with relatively large roll or pitch called relaxed motion, which defies most existing mosaic algorithms. Our approach adopts a multi-resolution strategy, which combines the merits of both feature-based and intensity-based methods. The main contribution is a robust motion estimation procedure which integrates an adaptive multi-scale block matching algorithm called TV-BMA, a low contrast filter and a RANSAC motion rectification to jointly refine motion and feature matches. Based on TV − L $^{1}$ model, the proposed TV-BMA works on the coarsest layer to find a robust initial displacement field as the initial motion for source images. This motion estimation method can generate robust correspondences for further processing. In the subsequent camera calibration step, we also present two stable methods to estimate the camera matrix. To estimate the focal length, we combine the golden section search and the simplex method based on the angle invariance of feature vectors; to estimate the rotation matrix, we introduce a subspace trust region method, which matches features based on the rotation invariance. Extensive experiments show that our approach leads to improved accuracy and robustness for stitching images with relaxed motion.
Starting Page	647
Ending Page	667
Page Count	21
File Format	PDF
ISSN	18631703
Journal	Signal, Image and Video Processing
Volume Number	6
Issue Number	4
e-ISSN	18631711
Language	English
Publisher	Springer-Verlag
Publisher Date	2010-11-21
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image mosaic Relaxed motion Block matching algorithm Low contrast filter TV − L $^{1}$ model Angle invariance Rotation invariance Computer Imaging, Vision, Pattern Recognition and Graphics Image Processing and Computer Vision Multimedia Information Systems Signal, Image and Speech Processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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