Improving IVUS palpography by incorporation of motion compensation based on block matching and optical flow

2008 ◽  
Vol 55 (11) ◽  
pp. 2392-2404 ◽  
Author(s):  
M. Danilouchkine ◽  
F. Mastik ◽  
A. van der Steen
Keyword(s):  
Optical Flow ◽  
Motion Compensation ◽  
Block Matching

Analysis and Implementation of MPEG-4 Motion Codec

2012 ◽  
Vol 268-270 ◽  
pp. 1667-1670
Author(s):  
Yun Peng Liu ◽  
Ren Fang Wang ◽  
Jin Li
Keyword(s):  
Motion Estimation ◽  
Motion Compensation ◽  
Block Matching ◽  
Modified Block

Motion codec is the key technique of MPEG-4 VM. The motion encoding and decoding use “Unrestricted Motion Estimation”, “Advanced Prediction”, “Overlapped Motion Compensation”, in addition, the particular “Repetitive Padding”, and “Modified Block Matching “ are added for MPEG-4. At the same time, some questions during motion are explained carefully, and some new viewpoints are brought forward.

scholarly journals A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878175 ◽  
Author(s):  
Shahrukh Ashraf ◽  
Priyanka Aggarwal ◽  
Praveen Damacharla ◽  
Hong Wang ◽  
Ahmad Y Javaid ◽  
...  
Keyword(s):  
Optical Flow ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Motion Vector ◽  
Block Matching ◽  
Positioning System ◽  
Simulation Studies ◽  
Flow Measurements ◽  
Global Positioning ◽  
Aerial Vehicle

The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely determines its utility and performance. The current navigation systems are highly dependent on the global positioning system and are prone to error because of global positioning system signal outages. However, advancements in onboard processing have enabled inertial navigation algorithms to perform well during short global positioning system outages. In this article, we propose an intelligent optical flow–based algorithm combined with Kalman filters to provide the navigation capability during global positioning system outages and global positioning system–denied environments. Traditional optical flow measurement uses block matching for motion vector calculation that makes the measurement task computationally expensive and slow. We propose the application of an artificial bee colony–based block matching technique for faster optical flow measurements. To effectively fuse optical flow data with inertial sensors output, we employ a modified form of extended Kalman filter. The modifications make the filter less noisy by utilizing the redundancy of sensors. We have achieved an accuracy of ~95% for all non-global positioning system navigation during our simulation studies. Our real-world experiments are in agreement with the simulation studies when effects of wind are taken into consideration.

Sign in / Sign up

Export Citation Format

Share Document