Bregman Iteration for Correspondence Problems: A Study of Optical Flow
Bregman iterations are known to yield excellent results for denoising, deblurring and compressed sensing tasks, but so far this technique has rarely been used for other image processing problems. In this paper we give a thorough description of the Bregman iteration, unifying thereby results of different authors within a common framework. Then we show how to adapt the split Bregman iteration, originally developed by Goldstein and Osher for image restoration purposes, to optical flow which is a fundamental correspondence problem in computer vision. We consider some classic and modern optical flow models and present detailed algorithms that exhibit the benefits of the Bregman iteration. By making use of the results of the Bregman framework, we address the issues of convergence and error estimation for the algorithms. Numerical examples complement the theoretical part.
Code (0)
등록된 구현이 없습니다.
Tasks
compressed sensingDeblurringDenoisingImage RestorationOptical Flow EstimationSimilar Papers 제목 키워드 기반
Linearized Bregman Iterations for Automatic Optical Fiber Fault Analysis
Supervision of the physical layer of optical networks is an extremely relevant subject. To detect fiber faults, single-ended solutions such as the Optical Time Domain Reflectometer (OTDR) allow for precise measurements o…
parameter estimationSpecificityOn Optical Flow Models for Variational Motion Estimation
The aim of this paper is to discuss and evaluate total variation based regularization methods for motion estimation, with particular focus on optical flow models. In addition to standard $L^2$ and $L^1$ data fidelities w…
Motion EstimationOptical Flow EstimationA Fiber Measurement System with Approximate Deconvolution Based on the Analysis of Fault Clusters in Linearized Bregman Iterations
Automatic detection of faults in optical fibers is an active area of research that plays a significant role in the design of reliable and stable optical networks. A fiber measurement system that combines automated data a…
Event DetectionManagementError concealment by means of motion refinement and regularized Bregman divergence
This work addresses the problem of error concealment in video transmission systems over noisy channels employing Bregman divergences along with regularization. Error concealment intends to improve the effects of disturba…
parameter estimationThe Linearized Bregman Method via Split Feasibility Problems: Analysis and Generalizations
The linearized Bregman method is a method to calculate sparse solutions to systems of linear equations. We formulate this problem as a split feasibility problem, propose an algorithmic framework based on Bregman projecti…