Improvement of motion estimation accuracy using gradient vector distribution in advanced picture coding

1996 ◽  
Vol 42 (3) ◽  
pp. 237-244 ◽  
Author(s):  
Y. Kaneko ◽  
Y. Shishikui ◽  
Y. Tanaka ◽  
F. Okano
Keyword(s):  
Motion Estimation ◽  
Estimation Accuracy ◽  
Gradient Vector ◽  
Picture Coding ◽  
Vector Distribution

scholarly journals A Preprocess Method of External Disturbance Suppression for Carotid Wall Motion Estimation Using Local Phase and Orientation of B-Mode Ultrasound Sequences

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Qinghui Zhang ◽  
Junqiu Li ◽  
Zhenping Qiang ◽  
Libo He
Keyword(s):  
Motion Estimation ◽  
Wall Motion ◽  
Structural Information ◽  
External Disturbance ◽  
Estimation Accuracy ◽  
Ultrasound Images ◽  
Local Phase ◽  
Registration Method ◽  
Anisotropic Diffusion Filter ◽  
Disturbance Suppression

Estimating the motions of the common carotid artery wall plays a very important role in early diagnosis of the carotid atherosclerotic disease. However, the disturbances caused by either the instability of the probe operator or the breathing of subjects degrade the estimation accuracy of arterial wall motion when performing speckle tracking on the B-mode ultrasound images. In this paper, we propose a global registration method to suppress external disturbances before motion estimation. The local vector images, transformed from B-mode images, were used for registration. To take advantage of both the structural information from the local phase and the geometric information from the local orientation, we proposed a confidence coefficient to combine them two. Furthermore, we altered the speckle reducing anisotropic diffusion filter to improve the performance of disturbance suppression. We compared this method with schemes of extracting wall displacement directly from B-mode or phase images. The results show that this scheme can effectively suppress the disturbances and significantly improve the estimation accuracy.

syris: a flexible and efficient framework for X-ray imaging experiments simulation

2017 ◽  
Vol 24 (6) ◽  
pp. 1283-1295 ◽  
Author(s):  
Tomáš Faragó ◽  
Petr Mikulík ◽  
Alexey Ershov ◽  
Matthias Vogelgesang ◽  
Daniel Hänschke ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Data Processing ◽  
Graphics Processing Units ◽  
High Speed ◽  
Real Data ◽  
Estimation Accuracy ◽  
Processing Parameter ◽  
X Ray ◽  
X Ray Imaging ◽  
Imaging Conditions

An open-source framework for conducting a broad range of virtual X-ray imaging experiments,syris, is presented. The simulated wavefield created by a source propagates through an arbitrary number of objects until it reaches a detector. The objects in the light path and the source are time-dependent, which enables simulations of dynamic experiments,e.g.four-dimensional time-resolved tomography and laminography. The high-level interface ofsyrisis written in Python and its modularity makes the framework very flexible. The computationally demanding parts behind this interface are implemented in OpenCL, which enables fast calculations on modern graphics processing units. The combination of flexibility and speed opens new possibilities for studying novel imaging methods and systematic search of optimal combinations of measurement conditions and data processing parameters. This can help to increase the success rates and efficiency of valuable synchrotron beam time. To demonstrate the capabilities of the framework, various experiments have been simulated and compared with real data. To show the use case of measurement and data processing parameter optimization based on simulation, a virtual counterpart of a high-speed radiography experiment was created and the simulated data were used to select a suitable motion estimation algorithm; one of its parameters was optimized in order to achieve the best motion estimation accuracy when applied on the real data.syriswas also used to simulate tomographic data sets under various imaging conditions which impact the tomographic reconstruction accuracy, and it is shown how the accuracy may guide the selection of imaging conditions for particular use cases.

Simulation of Range Imaging-based Estimation of Respiratory Lung Motion

2014 ◽  
Vol 53 (04) ◽  
pp. 257-263 ◽  
Author(s):  
R. Werner ◽  
M. Blendowski ◽  
J. Ortmüller ◽  
H. Handels ◽  
M. Wilms
Keyword(s):  
Motion Estimation ◽  
Simulation Study ◽  
Respiratory Motion ◽  
Internal Motion ◽  
Estimation Accuracy ◽  
Patient Specific ◽  
Range Images ◽  
Motion Patterns ◽  
Multidimensional Signals ◽  
Lung Motion

SummaryObjectives: A major problem associated with the irradiation of thoracic and abdominal tumors is respiratory motion. In clinical practice, motion compensation approaches are frequently steered by low-dimensional breathing signals (e.g., spirometry) and patient-specific correspondence models, which are used to estimate the sought internal motion given a signal measurement. Recently, the use of multidimensional signals derived from range images of the moving skin surface has been proposed to better account for complex motion patterns. In this work, a simulation study is carried out to investigate the motion estimation accuracy of such multidimensional signals and the influence of noise, the signal dimensionality, and different sampling patterns (points, lines, regions).Methods: A diffeomorphic correspondence modeling framework is employed to relate multidimensional breathing signals derived from simulated range images to internal motion patterns represented by diffeomorphic non-linear transformations. Furthermore, an automatic approach for the selection of optimal signal combinations/patterns within this framework is presented.Results: This simulation study focuses on lung motion estimation and is based on 28 4D CT data sets. The results show that the use of multidimensional signals instead of one-dimensional signals significantly improves the motion estimation accuracy, which is, however, highly affected by noise. Only small differences exist between different multidimensional sampling patterns (lines and regions). Automatically determined optimal combinations of points and lines do not lead to accuracy improvements compared to results obtained by using all points or lines.Conclusions: Our results show the potential of multidimensional breathing signals derived from range images for the model-based estimation of respiratory motion in radiation therapy.

Design and Memory Optimization of Motion Estimation Module for H.264/AVC Encoder

2011 ◽  
Vol 179-180 ◽  
pp. 1350-1355
Author(s):  
Duo Li Zhang ◽  
Chuan Jie Wang ◽  
Yu Kun Song ◽  
Gao Ming Du ◽  
Xian Wen Cheng
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Estimation Accuracy ◽  
Memory Optimization ◽  
Search Window ◽  
Pipeline Architecture ◽  
Macro Block ◽  
Block Level ◽  
Organization Strategy ◽  
On Chip

H.264/AVC standard has been widely used in video compression at various kinds of application domain. Motion estimation takes the most calculation workload of H.264/AVC encoder. Memory optimization has played an even more important role in encoder design. Firstly, dependency relation between motion vectors was analyzed and removed at a little cost of estimation accuracy decrement, and then a 3-stage macro-block level pipeline architecture was proposed to increase parallel process ability of motion estimation. Then an optimized memory organization strategy of reference frame data was put forward, aiming at avoiding row changing frequently in SDRAM access. Finally, based on the 3-stage pipeline structure, a shared cyclic search window memory was proposed: 1) data relativity between adjacent macro-block was analyzed, 2) and search window memory size was elaborated, 3) and then a slice based structure and the work process were discussed. Analysis and experiment result show that 50% of on chip memory resource and cycles for off chip SDRAM access can be saved. The whole design was implemented with Verilog HDL and integrated into a H.264 encoder, which can demo 1280*720@30 video successfully at frequency of 120MHz under a cyclone III FPGA development board.

scholarly journals A Fast Fractal Video Coding Algorithm Using Cross-Hexagon Search for Block Motion Estimation

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Kamel Belloulata ◽  
Shiping Zhu ◽  
Zaikuo Wang
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Search Algorithm ◽  
Motion Vector ◽  
Block Matching ◽  
Block Motion ◽  
Search Patterns ◽  
Vector Distribution ◽  
Search Speed ◽  
Block Motion Estimation

We propose a novel fractal video coding method using fast block-matching motion estimation to overcome the drawback of the time-consuming character in the fractal coding. As fractal encoding essentially spends most time on the search for the best-matching block in a large domain pool, search patterns and the center-biased characteristics of motion vector distribution have large impact on both search speed and quality of block motion estimation. In this paper, firstly, we propose a new hexagon search algorithm (NHEXS), and, secondly, we ameliorate, by using this NHEXS, the traditional CPM/NCIM, which is based on Fisher's quadtree partition. This NHEXS uses two cross-shaped search patterns as the first two initial steps and large/small hexagon-shaped patterns as the subsequent steps for fast block motion estimation (BME). NHEXS employs halfway stop technique to achieve significant speedup on sequences with stationary and quasistationary blocks. To further reduce the computational complexity, NHEXS employs modified partial distortion criterion (MPDC). Experimental results indicate that the proposed algorithm spends less encoding time and achieves higher compression ratio and compression quality compared with the traditional CPM/NCIM method.

scholarly journals MOTION ESTIMATION OF AN UNDERWATER PLATFORM USING IMAGES FROM TWO SONAR SENSORS

2021 ◽  
Author(s):  
José Enrique Almanza-Medina ◽  
Benjamin Henson ◽  
Yuriy Zakharov
Keyword(s):  
Motion Estimation ◽  
Performance Improvement ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
High Accuracy ◽  
Estimation Accuracy ◽  
Navigation Systems ◽  
Sonar Sensors ◽  
Acoustic Images ◽  
Single Sensor

Many underwater applications that involve the use of autonomous underwater vehicles require accurate navigation systems. Image registration from acoustic images is a technique that can be used to achieve this task by comparing two consecutive sonar images and estimate the motion of the vechicle. The use of deep learning (DL) techniques for motion estimation can significantly reduce the processing complexity and achieve high-accuracy position estimates. In this paper we investigate the performance improvement when using two sonar sensors compared to using a single sensor. The DL network is trained using images generated by a sonar simulator. The results show an improvement in the estimation accuracy when using two sensors.

Fast Global Motion Estimation Algorithm for Microscopic Image Sequences

2010 ◽  
Vol 20-23 ◽  
pp. 1103-1108
Author(s):  
Xiao Tao Zhu ◽  
Mei Yu ◽  
Yi Gang Wang ◽  
Gang Yi Jiang
Keyword(s):  
Motion Estimation ◽  
Estimation Algorithm ◽  
Image Sequences ◽  
Estimation Accuracy ◽  
Microscopic Image ◽  
Global Motion ◽  
Translation Model ◽  
Global Motion Estimation ◽  
Speed Up ◽  
Motion Estimation Algorithm

In this paper, a fast global motion estimation algorithm is proposed to speed up the processing of microscopic image sequence. A translation model based on non-linear density estimation is adopted by the proposed algorithm. To speed up the process, three-level pyramid is used. Noise detection and feature pixel extraction run simultaneously in each pyramid level. Then the motion parameters is estimated only with the feature pixels. The experimental results show that the computational complexity of the proposed algorithm is reduced much while estimation accuracy is maintained compared with the MPEG-4 algorithm.

scholarly journals Comparison Between Multiline Transmission and Diverging Wave Imaging: Assessment of Image Quality and Motion Estimation Accuracy

2019 ◽  
Vol 66 (10) ◽  
pp. 1560-1572
Author(s):  
Emilia Badescu ◽  
Herve Liebgott ◽  
Damien Garcia ◽  
Philippe Joos ◽  
Adeline Bernard ◽  
...  
Keyword(s):  
Image Quality ◽  
Motion Estimation ◽  
Estimation Accuracy ◽  
Wave Imaging
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