Block Compressive Sensing (BCS) Based Multi-phase Reconstruction (MPR) Framework for Video

2016 ◽  
pp. 105-115
Author(s):  
Mansoor Ebrahim ◽  
Wai Chong Chia
Keyword(s):  
Compressive Sensing ◽  
Phase Reconstruction ◽  
Multi Phase

scholarly journals Block Compressive Sensing (BCS) Based Low Complexity, Energy Efficient Visual Sensor Platform with Joint Multi-Phase Decoder (JMD)

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2309 ◽  
Author(s):  
Mansoor Ebrahim ◽  
Wai Chong Chia ◽  
Syed Hasan Adil ◽  
Kamran Raza
Keyword(s):  
Compressive Sensing ◽  
Low Cost ◽  
Low Complexity ◽  
Practical Implementation ◽  
Bandwidth Utilization ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Sensor Platform ◽  
Critical Issues ◽  
Multi Phase

Devices in a visual sensor network (VSN) are mostly powered by batteries, and in such a network, energy consumption and bandwidth utilization are the most critical issues that need to be taken into consideration. The most suitable solution to such issues is to compress the captured visual data before transmission takes place. Compressive sensing (CS) has emerged as an efficient sampling mechanism for VSN. CS reduces the total amount of data to be processed such that it recreates the signal by using only fewer sampling values than that of the Nyquist rate. However, there are few open issues related to the reconstruction quality and practical implementation of CS. The current studies of CS are more concentrated on hypothetical characteristics with simulated results, rather than on the understanding the potential issues in the practical implementation of CS and its computational validation. In this paper, a low power, low cost, visual sensor platform is developed using an Arduino Due microcontroller board, XBee transmitter, and uCAM-II camera. Block compressive sensing (BCS) is implemented on the developed platform to validate the characteristics of compressive sensing in a real-world scenario. The reconstruction is performed by using the joint multi-phase decoding (JMD) framework. To the best of our knowledge, no such practical implementation using off the shelf components has yet been conducted for CS.

Compressive Sensing Based Pseudo-random Multi-phase CW Radar

2011 ◽  
Vol 33 (2) ◽  
pp. 418-423 ◽  
Author(s):  
Ya-peng He ◽  
Ke-rang Wang ◽  
Jin-dong Zhang ◽  
Xiao-hua Zhu
Keyword(s):  
Compressive Sensing ◽  
Multi Phase ◽  
Cw Radar

scholarly journals Defining the effective deformation of the vertebral column

2020 ◽  
Vol 57 (2) ◽  
pp. 131-150
Author(s):  
Abtin Daghighi ◽  
Hans Tropp
Keyword(s):  
Cobb Angle ◽  
Vertebral Column ◽  
Three Dimensional ◽  
Local Deformation ◽  
Phase Reconstruction ◽  
Deviation Measure ◽  
Technical Procedure ◽  
Rigorous Model ◽  
Multi Phase ◽  
Future Work

SummaryThe Cobb angle is calculated in the coronal plane, irrespective of vertebral rotation, lordokyphosis and local wedge properties of individual verte-brae other than the end plates used for the measurement. Rigorous three-dimensional generalizations of the Cobb angle are complicated for at least two reasons. Firstly, the vertebral column is segmented, not continuous, making the choice of rigorous model ambiguous. Secondly, there exists an inherent curvature (in terms of thoracic kyphosis and lumbar lordosis) that may be considered physiologically healthy or ’normal’. When attempting to find a three-dimensional deviation measure, such normal sagittal curvature must be compensated for.In this paper we introduce a three-dimensional local deformation parameter (which we call the local effective deformation) motivated by both biomechanics and the basic theory of spatial curves, and simultaneously introduce a technical procedure to estimate the parameter from CT scans using MPR (multi-phase reconstruction) in PACS (IDS-7). A detailed description of the proposed modelling of vertebral column deformation is given, together with a stepwise procedure to estimate the three-dimensional deformation (in terms of local effective deformation). As a deformation measure it requires knowledge about the natural healthy kypholordosis. A method is described by which such knowledge may be incorporated in future work.

Some Applications of the U. S. Steel MVEM

1973 ◽  
Vol 31 ◽  
pp. 4-5
Author(s):  
J. S. Lally ◽  
L. E. Thomas ◽  
R. M. Fisher
Keyword(s):  
Electron Diffraction ◽  
Debye Temperature ◽  
Metals And Alloys ◽  
Critical Voltage ◽  
Dynamical Diffraction ◽  
Phase Structures ◽  
Structure Factors ◽  
Local Bonding ◽  
Diffraction Phenomenon ◽  
Multi Phase

A variety of materials containing many different microstructures have been examined with the USS MVEM. Three topics have been selected to illustrate some of the more recent studies of diffraction phenomena and defect, grain and multi-phase structures of metals and minerals.(1) Critical Voltage Effects in Metals and Alloys - This many-beam dynamical diffraction phenomenon, in which some Bragg resonances vanish at certain accelerating voltages, Vc, depends sensitively on the spacing of diffracting planes, Debye temperature θD and structure factors. Vc values can be measured to ± 0.5% in the HVEM ana used to obtain improved extinction distances and θD values appropriate to electron diffraction, as well as to probe local bonding effects and composition variations in alloys.

Digital imaging and quantitative image analysis of polymer blends

1996 ◽  
Vol 54 ◽  
pp. 170-171
Author(s):  
Xiao Zhang
Keyword(s):  
Digital Imaging ◽  
Imaging Techniques ◽  
Imaging Systems ◽  
Polymer Science ◽  
Key Factors ◽  
Multiple Imaging ◽  
Quantitative Image ◽  
Digital Imaging Systems ◽  
Multi Phase ◽  
Network Technologies

Polymer microscopy involves multiple imaging techniques. Speed, simplicity, and productivity are key factors in running an industrial polymer microscopy lab. In polymer science, the morphology of a multi-phase blend is often the link between process and properties. The extent to which the researcher can quantify the morphology determines the strength of the link. To aid the polymer microscopist in these tasks, digital imaging systems are becoming more prevalent. Advances in computers, digital imaging hardware and software, and network technologies have made it possible to implement digital imaging systems in industrial microscopy labs.

Compressive Sensing for Wireless Networks

2009 ◽  
Author(s):  
Zhu Han ◽  
Husheng Li ◽  
Wotao Yin
Keyword(s):  
Wireless Networks ◽  
Compressive Sensing

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document