Motion estimation is a long-standing cornerstone of image and video processing. Most notably, motion estimation serves as the foundation for many of today's ubiquitous video coding standards including H.264. Motion estimators also play key roles in countless other applications that serve the consumer, industrial, biomedical, and military sectors. Of the many available motion estimation techniques, optical flow is widely regarded as most flexible. The flexibility offered by optical flow is particularly useful for complex registration and interpolation problems, but comes at a considerable computational expense. As the volume and dimensionality of data that motion estimators are applied to continue to grow, that expense becomes more and more costly. Control grid motion estimators based on optical flow can accomplish motion estimation with flexibility similar to pure optical flow, but at a fraction of the computational expense. Control grid methods also offer the added benefit of representing motion far more compactly than pure optical flow. This booklet explores control grid motion estimation and provides implementations of the approach that apply to data of multiple dimensionalities. Important current applications of control grid methods including registration and interpolation are also developed. Table of Contents: Introduction / Control Grid Interpolation (CGI) / Application of CGI to Registration Problems / Application of CGI to Interpolation Problems / Discussion and Conclusions
Author(s): Christine M. Zwart, David H. Frakes
Series: Synthesis Lectures on Algorithms and Software in Engineering
Publisher: Morgan & Claypool Publishers
Year: 2013
Language: English
Pages: 88
Tags: Информатика и вычислительная техника;Обработка медиа-данных;Обработка видео;
Registration and Motion Estimation......Page 11
Block-based Motion Estimation......Page 12
Optical Flow......Page 16
Organization of the Book......Page 17
Control Grid Interpolation (CGI)......Page 19
One-Dimensional......Page 20
Two-Dimensional......Page 23
Optimization Mathematics......Page 26
One-Dimensional Control Grid and One Degree of Freedom Optical Flow......Page 27
Two Dimensional Control Grid and One Degree of Freedom Optical Flow......Page 31
Two-Dimensional Control Grid and Two Degrees of Freedom Optical Flow......Page 32
Symmetric Implementations......Page 33
Summary......Page 34
Dynamic Time Warping......Page 37
Isophote Identification......Page 42
Motion Estimation......Page 53
Mitigation of Atmospheric Turbulence Distortion......Page 55
Medical Image Registration......Page 59
Summary......Page 63
Single-Image Super-resolution......Page 65
Video Deinterlacing......Page 70
Inter-frame Interpolation......Page 72
Summary......Page 75
Strengths and Weaknesses......Page 77
Application to Higher-Dimensions and Multivariate Optimization......Page 78
Final Thoughts and Conclusions......Page 79
Bibliography......Page 81
Authors' Biographies......Page 89
