Sub-pixel image registration based on super resolution reconstruction

2017 ◽  
Vol 25 (2) ◽  
pp. 477-484
Author(s):  
李方彪 LI Fang-biao ◽  
何 昕 HE Xin ◽  
魏仲慧 WEI Zhong-hui ◽  
马 鑫 MA Xin
Keyword(s):  
Image Registration ◽  
Super Resolution ◽  
Pixel Image

The FPGA implementation of a one-bit-per-pixel image registration algorithm

2014 ◽  
Vol 11 (4) ◽  
pp. 799-815 ◽  
Author(s):  
An Hung Nguyen ◽  
Mark R. Pickering ◽  
Andrew Lambert
Keyword(s):  
Image Registration ◽  
Fpga Implementation ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Pixel Image

Depth estimation, spatially variant image registration, and super-resolution using a multi-lenslet camera

2010 ◽  
Author(s):  
Qiang Zhang ◽  
Mark Mirotznik ◽  
Santiago Saldana ◽  
Jarred Smith ◽  
Ryan Barnard
Keyword(s):  
Image Registration ◽  
Super Resolution ◽  
Depth Estimation ◽  
Spatially Variant

scholarly journals Image prior combination in super-resolution image registration & reconstruction

2010 ◽  
Author(s):  
Salvador Villena ◽  
Miguel Vega ◽  
S. Derin Babacan ◽  
Rafael Molina ◽  
Aggelos K. Katsaggelos
Keyword(s):  
Image Registration ◽  
Super Resolution ◽  
Resolution Image ◽  
Image Prior

A fast image registration algorithm for super-resolution

2013 ◽  
Author(s):  
Chengjin Li ◽  
Xunjie Zhao ◽  
Kai Lu ◽  
Xuesong Zhang
Keyword(s):  
Image Registration ◽  
Super Resolution ◽  
Registration Algorithm ◽  
Image Registration Algorithm

scholarly journals Hybrid 3D Dynamic Measurement by Particle Swarm Optimization and Photogrammetric Tracking

2013 ◽  
Vol 13 (6) ◽  
pp. 298-304 ◽  
Author(s):  
M. Shahbazi
Keyword(s):  
Particle Swarm Optimization ◽  
Image Registration ◽  
Linear Optimization ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Three Dimensions ◽  
Image Correlation ◽  
Motion Modeling ◽  
Swarm Optimization ◽  
Pixel Image

Abstract High-accuracy motion modeling in three dimensions via digital images has been increasingly the matter of interest in photogrammetry and computer vision communities. Although accurate sub-pixel image registration techniques are the key elements of measurement, they still demand enhanced intelligence, autonomy, and robustness. In this paper, a new correlationbased technique of stereovision is proposed to perform inter-frame feature tracking, inter-camera image registration, and to measure the 3D state vector of features simultaneously. The developed algorithm is founded on population-based intelligence (particle swarm optimization) and photogrammetric modeling. The proposed technique is mainly aimed at reducing the computational complexities of non-linear optimization methods of digital image registration for deformation measurement, and passing through 2D image correlation to 3D motion modeling. The preliminary results have illustrated the feasibility of this technique to detect and measure sub-millimeter deformations by performing accurate, sub-pixel image registration.

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