scholarly journals On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Jeyarajan Thiyagalingam ◽  
Daniel Goodman ◽  
Julia A. Schnabel ◽  
Anne Trefethen ◽  
Vicente Grau
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Three Dimensional ◽  
Basic Research ◽  
Estimation Algorithm ◽  
Image Sequences ◽  
Multicore Architectures ◽  
Gpu Architectures ◽  
Access Patterns ◽  
Performance Gains

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results.

Fast Motion Estimation Algorithm Based on Real Time Monitoring

2011 ◽  
Vol 383-390 ◽  
pp. 5028-5033
Author(s):  
Xue Mei Xu ◽  
Qin Mo ◽  
Lan Ni ◽  
Qiao Yun Guo ◽  
An Li
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Computation Time ◽  
Estimation Algorithm ◽  
Video Encoding ◽  
Experimental Result ◽  
Fast Motion Estimation ◽  
Motion Activity ◽  
Search Patterns ◽  
Motion Estimation Algorithm

In the video encoding system, motion estimation plays an important role at the front-end of encoder, which can eliminate inter redundancy efficiently and improve encoding efficiency. However, traditional motion estimation algorithm can’t be used in real-time application like video monitoring due to its computational complexity. In order to improve real-time efficiency, an improved motion estimation algorithm is proposed in this paper. The essential ideas consist of early termination rules, prediction of initial search point, and determination of motion type. Furthermore, our algorithm adopts different search patterns for certain motion activity. Experimental result shows that the improved algorithm reduces the computation time significantly while maintaining the image quality, and satisfies real time requirement in monitoring system.

scholarly journals Real Time Neutron Radiography Applications in Gas Turbine and Internal Combustion Engine Technology

1988 ◽  
Author(s):  
John T. Lindsay ◽  
C. W. Kauffman
Keyword(s):  
Real Time ◽  
Gas Turbine ◽  
Internal Combustion Engines ◽  
Combustion Engine ◽  
Neutron Radiography ◽  
Three Dimensional ◽  
Basic Research ◽  
Internal Combustion ◽  
Turbine Engines ◽  
Gas Turbine Engines

Real Time Neutron Radiography (RTNR) is rapidly becoming a valuable tool for nondestructive testing and basic research with a wide variety of applications in the field of engine technology. The Phoenix Memorial Laboratory (PML) at the University of Michigan has developed a RTNR facility and has been using this facility to study several phenomena that have direct application to internal combustion and gas turbine engines. These phenomena include; 1) the study of coking and debris deposition in several gas turbine nozzles (including the JT8D), 2) the study of lubrication problems in operating standard internal combustion engines and in operating automatic transmissions (1, 2, 3), 3) the location of lubrication blockage and subsequent imaging of the improvement obtained from design changes, 4) the imaging of sprays inside metallic structures in both a two-dimensional, standard radiographic manner (4, 5) and in a computer reconstructed, three-dimensional, tomographic manner (2, 3), and 5) the imaging of the fuel spray from an injector in a single cylinder diesel engine while the engine is operating. This paper will show via slides and real time video, the above applications of RTNR as well as other applications not directly related to gas turbine engines.

scholarly journals A Homogeneous Algorithm for Motion Estimation and Compensation by Using Cellular Neural Networks

2010 ◽  
Vol 5 (5) ◽  
pp. 719 ◽  
Author(s):  
Cristian Grava ◽  
Alexandru Gacsádi ◽  
Ioan Buciu
Keyword(s):  
Neural Networks ◽  
Motion Estimation ◽  
Real Time ◽  
Cellular Neural Networks ◽  
Image Sequences ◽  
Artificial Vision ◽  
Real Time Image ◽  
Field Programmable ◽  
Real Time Applications ◽  
Time Image

In this paper we present an original implementation of a homogeneous algorithm for motion estimation and compensation in image sequences, by using Cellular Neural Networks (CNN). The CNN has been proven their efficiency in real-time image processing, because they can be implemented on a CNN chip or they can be emulated on Field Programmable Gate Array (FPGA). The motion information is obtained by using a CNN implementation of the well-known Horn & Schunck method. This information is further used in a CNN implementation of a motion-compensation method. Through our algorithm we obtain a homogeneous implementation for real-time applications in artificial vision or medical imaging. The algorithm is illustrated on some classical sequences and the results confirm the validity of our algorithm.

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