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Hankel Structured Low Rank and Sparse Representation Via L0-Norm Optimization for Compressed Ultrasound Plane Wave signal Reconstruction

Hankel Structured Low Rank and Sparse Representation Via L0-...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Miaomiao Zhang Ji Chen Xiaoyan Fu Ge Xin Jingzhi Zhang Na Jiang Jan D’Hooge College of Information Engineering Capital Normal University Beijing China School of Traffic and Transportation Beijing Jiaotong University Beijing China Department of Cardiovascular Sciences Laboratory of Cardiovascular Imaging and Dynamics KU Leuven Leuven Belgium

Ultrasound plane wave imaging is widely used in many applications thanks to its capability in reaching high frame rates. However, the amount of data acquisition and storage in a period of time can become a bottleneck in ultrasound system design for thousands frames per second. In our previous study, we proposed a low-rank and joint-sparse model to reduce the amount of sampled channel data of focused beam imaging by considering all the received data as a 2D matrix. However, for a single plane wave transmission, the number of channels is limited and the low-rank property of the received data matrix is no longer achieved. In this study, a L 0 -norm based Hankel structured low-rank and sparse model is proposed to reduce the channel data. An optimization algorithm, based on the alternating direction method of multipliers (ADMM), is proposed to efficiently solve the resulting optimization problem. The performance of the proposed approach was evaluated using the data published in Plane Wave Imaging Challenge in Medical Ultrasound (PICMUS) in 2016. Results on channel and plane wave data show that the proposed method is better adapted to the ultrasound channel signal and can recover the image with fewer samples than the conventional CS method.

关键词： Adaptation models Ultrasonic imaging signal processing algorithms Data models signal reconstruction Sparse matrices Speech processing

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design Concepts and Characterization of a Next Generation Clinical PET Detector

Design Concepts and Characterization of a Next Generation Cl...

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IEEE Nuclear Science Symposium

作者： J. W. Cates C. S. Levin School of Automotive Engineering Dalian University of Technology Dalian P. R. China

The future of positron emission tomography (PET) is systems with ultra-precise coincidence time resolution (CTR) to advance time-of-flight PET (TOF-PET) performance. Current state-of-the-art commercial PET systems have 350-800 ps full-width-at-half-maximum (FWHM) timing performance, constraining annihilation events to lie somewhere within a 5-12 cm region along system detector response lines (LORs). This constraint is applied during the image reconstruction process to enhance image SNR for improved lesion detectability, increased accuracy and precision of lesion uptake measurements, less sensitivity to errors in data correction techniques (normalization, scatter, and attenuation corrections), lower injected dose, or shorter scan time. The effect of these improvements on image quality and accuracy scales with system CTR performance, and a long-standing milestone for the TOF-PET community is to drive system CTR towards 100 ps FWHM (1.5 cm localization along LORs). At this level of performance, a factor of five improvement in SNR can be realized compared to non-TOF imaging, with a transformational impact on quantitative PET imaging in many count starved and contrast-limited scenarios. Traditional PET detector designs are not able to achieve this level of CTR performance, and thus new detector concepts and signal processing methods should be explored to advance system CTR

关键词： Crystals Detectors Photonics Delays Positron emission tomography Multiplexing

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A Key Frame Selection Algorithm Based on Sliding Window and image Features

A Key Frame Selection Algorithm Based on Sliding Window and ...

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International conference on Parallel and Distributed Systems (ICPADS)

作者： Jigang Cao Linchen Yu Mianlong Chen Xinyue Cui School of Computer China University of Geosciences Wuhan

ISBN: (纸本)9781509053827

Network traffic associated with video increases sharply, how to choose the interested information for a number of Internet users is challenging. So, technologies and applications related with video, such as video search, video fast browsing, video index and storage are in great demand. Behind these technologies and applications, a core problem is how to quickly browse massive video data and obtain the main content of the video. To solve this problem, different key frame extraction algorithms have been proposed. Due to the diversity of video content, different video have different characteristics. So the design of general video key frame extraction algorithm to solve the problem is not the reality. The main trend for the problem is to design the key frame extraction algorithm based on the characteristics of the video itself. In this article, we mainly focus on videos with edited boundaries and shot conversions. Aiming at this kind of video, we have designed and implemented video key frame extraction algorithm based on sliding window, the global feature Gist and local feature point detection algorithm SURF. In this algorithm, we use Gist feature to construct the global scene information of frames, and the SURF keypoint detection algorithm to extract local keypoints as local feature for each frame. Then, shot segmentation based on sliding window and shot merging algorithm is applied to dividing the original video into several shots. After that, we select the most representative frames in each video shot as key frames. Finally we evaluate the result of the algorithm from the subjective and objective perspective. Results show that key frames extracted in the algorithm are of high quality and can basically cover the main content of the original video.

关键词： Feature extraction Algorithm design and analysis signal processing algorithms Clustering algorithms Detection algorithms image color analysis Visualization

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低功耗之模組化排序單元設計

低功耗之模組化排序單元設計

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作者：林郁寧成功大學

学位级别：碩士

在资料探勘、数位讯号处理、型态辨识或影像处理等的领域中，排序已广泛的被使用且是不可或缺的一项运算，且在许多应用上，往往只需要使用到极值，故探讨如何有效率的找到极值是十分重要的。此外，对於许多需要即时处理的应用来说，即... 详细信息

在资料探勘、数位讯号处理、型态辨识或影像处理等的领域中，排序已广泛的被使用且是不可或缺的一项运算，且在许多应用上，往往只需要使用到极值，故探讨如何有效率的找到极值是十分重要的。此外，对於许多需要即时处理的应用来说，即时排序的硬体实现是不可或缺的。在本论文中，我们针对排序单元提出一个有效的硬体架构，其电路架构使用索引值以及门槛值的机制，并使用模组化的方法设计，使得整个架构容易被重复使用与平行化，藉由以上设计来达到低功耗消耗的设计，最後，提出一个迭代的架构，使得整个设计能够更有效率的被使用在不同应用上。一般的排序方法，对於一些需要较大样本宽度或较多输入值的应用来说，在电路上可能需要更多的讯号传递，或是互相交换值，而造成更多的动态功率消耗。为了解决上述的问题，我们在电路架构设计上采用了较少位元所组成的索引值以及门槛值的概念，使储存的样本值不需要进行移动排序，而仅需改变索引值来完成排序。此外，进行较大输入量的迭代运算时，利用门槛值来排除掉不必要的数值以降低重复运算的次数，如此就可有效减少电路中讯号的传递以及运算次数，藉此达到节省功率消耗的结果，此外，我们亦针对控制电路的设计以逻辑最佳化的化简方法来实现，大幅改善整体硬体成本使用。实验结果显示我们和其他文献电路架构相比，此电路的功率消耗平均仅约一半，但需要一些额外的面积代价。此论文中，所有的硬体架构之实现是使用Verilog硬体描述语言，电路合成是利用Synopsys design Vision以及TSMC的标准元件库，最後采用Synopsys Power Compiler量测电路布局後模拟的功率消耗。依据合成结果与功率消耗量测，我们所提出的电路架构设计在低功率消耗上具有极佳的竞争力。

关键词：硬體架構排序單元邏輯最佳化迭代運算低功率

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Scalable design of SDN controllers for optical networks using federation-based architectures

Scalable design of SDN controllers for optical networks usin...

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European conference on Networks and Optical Communications (NOC)

作者： João Santos Coriant R&D Portugal Amadora Portugal

The introduction of software-defined networking (SDN) principles in the optical communications ecosystem promises to change the way things are done nowadays. Although many of these principles still require proper maturation, the main premises behind SDN are quite attractive: 1) The separation of control and data plane will ultimately result in simpler hardware elements in the network with the network intelligence all concentrated in software controllers; 2) With this separation, the control plane is relieved of the hardware limitations intrinsic to the network equipment. This eases the creation of automated and virtualized functions at the controller where capacity can be added; 3) Open and standardized interfaces between applications, controllers, and network elements is going to promote innovation, interoperability and disaggregated systems. In this context, the network controller, whose main responsibility lies in the efficient configuration of the network equipment, is a crucial element to the SDN architecture. Typically, such controllers are centralized elements that detain the complete knowledge of the network. However, for large-sized networks, such concentration can lead to lengthier operations, heavier resiliency schemes, and availability of excessive storage and processing capacity. To obviate these issues and promote scalability, this paper presents a new controller architecture based on a federation of multiple sub-network controllers, each managing only a section of the network, conveniently coordinated by a hierarchically-superior controller. A clustering algorithm, based on single-linkage, is developed to create sub-networks under different grouping policies. In order to assess the impact of employing the federated approach in an optical network, we use a reference topology to determine the amount of routed demands and regeneration cards required. The results obtained show that the performance of the federated architecture can only resemble that of th

关键词： Computer architecture Clustering algorithms Repeaters Routing Optical fiber networks signal to noise ratio

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Hybrid hierarchical search motion estimation for Video Compression

Hybrid hierarchical search motion estimation for Video Compr...

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International conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB)

作者： Twinkle Sebastian J. Anitha Department of Electronics and Communication Karunya University Tamil Nadu India

ISBN: (纸本)9781467397469

There has been an increasing demand for digital video technology in various fields of telecommunication, entertainment, medicine etc. and hence the need for Video Compression. Motion estimation techniques help in better Video Compression performance by removing the temporal redundancy effectively between frames. Block based motion estimation has been widely used for video coding. One such method is the Hierarchical Search Technique for BMA. In this work, a hierarchical search approach making use of three different algorithms Full Search Algorithm, New Cross Diamond Search Algorithm and a New Three Step Search Algorithm are used. The original image is sub-sampled into additional two levels. The Full Search is performed on the highest level where the complexity is relatively low. The New Cross Diamond search algorithm and a New Three-Step Search Algorithm are used in the consecutive two levels. The results of the algorithm show better performance in terms of PSNR with reduced complexity.

关键词： Motion estimation Algorithm design and analysis Diamond signal processing algorithms Video compression Complexity theory Pattern matching

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EEG source imaging assists decoding in a face recognition task

EEG source imaging assists decoding in a face recognition ta...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Rasmus S. Andersen Anders U. Eliasen Nicolai Pedersen Michael Riis Andersen Sofie Therese Hansen Lars Kai Hansen Technical University of Denmark Department of Applied Mathematics and Computer Science Richard Petersens Plads B324 DK-2800 Kgs. Lyngby Denmark

ISBN: (纸本)9781509041183

EEG based brain state decoding has numerous applications. State of the art decoding is based on processing of the multivariate sensor space signal, however evidence is mounting that EEG source reconstruction can assist decoding. EEG source imaging leads to high-dimensional representations and rather strong a priori information must be invoked. Recent work by Edelman et al. (2016) has demonstrated that introduction of a spatially focal source space representation can improve decoding of motor imagery. In this work we explore the generality of Edelman et al. hypothesis by considering decoding of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source imaging does not lead to an improved decoding. We design a distributed pipeline in which the classifier has access to brain wide features which in turn does lead to a 15% reduction in the error rate using source space features. Hence, our work presents supporting evidence for the hypothesis that source imaging improves decoding.

关键词： Brain state decoding Brain computer interface BCI EEG source imaging Face recognition Facial Recognition source image DECODING Brain-Computer Interfaces Error analysis Electroencephalography

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MCAPI-compliant Hardware Buffer Manager Mechanism to Support Communication in Multi-Core architectures

MCAPI-compliant Hardware Buffer Manager Mechanism to Support...

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design, Automation & Test in Europe conference & Exhibition

作者： Thiago Raupp da Rosa Thomas Mesquida Romain Lemaire Fabien Clermidy Univ. Grenoble Alpes F-38000 France

ISBN: (纸本)9781467392280

High performance and high power efficiency are two mandatory constraints for multi-core systems in order to successfully handle the most recent applications in several fields, e.g. image processing and communication standards. Nowadays, hardware accelerators are often used along with several processing cores to achieve the desired performance while keeping high power efficiency. However, such systems impose an increased programming complexity due to the lack of software standards that supports heterogeneity, frequently leading to custom solutions. On the other hand, implementing a standard software solution for embedded systems might induce significant overheads. This work presents a hardware mechanism in codesign with a standard programming interface (API) for embedded systems focusing to decrease overheads imposed by software implementation while increasing programmability and communication performance. The results show gains of up to 97% in latency and an increase of 40 times in throughput for synthetic traffics and an average decrease of 95% in communication time for an image processing application.

关键词： MCAPI-compliant Hardware Buffer Manager Mechanism Support Communication Multi-Core architectures

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Reduction of Non-White Noise from Hyperspectral images Based on Tensor Decomposition

Reduction of Non-White Noise from Hyperspectral Images Based...

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2016 IEEE 13th International conference on signal processing（ICSP2016）

作者： Jiwei LIU Min FU Xuefeng LIU College of Design Art Shenyang Aerospace University College of Information Science & Engineering Ocean University of China College of Automation & Electronic Engineering Qingdao University of Science & Technology

Acquired images in hyperspectral imagery are disturbed by additive noise which is usually assumes as zeromean white one. In fact, there is still non-white noise in hyperspectral images(HSIs). The 2-dimensional filtering methods and multidimensional tensor decomposition algorithms cannot be used to remove non-white noise from HSIs directly. Therefore, a prewhitening denoising solution based on tensor decomposition is proposed in this paper. The prewhitening procedure can help to transform the non-white noise into a white one and the tensor decomposition method removes the noise without affecting the related information between image planes. The simulation results show that this non-white noise reducing approach has promising prospects in this field compared to existing denoising methods.

关键词： Denoising Parallel Factor Analysis(PARAFAC) Multidimensional Wiener Filtering(MWF) HSI

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The Study of the Indoor Positioning Based on Smart Wearable Technologies

The Study of the Indoor Positioning Based on Smart Wearable ...

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2016 IEEE International conference on signal and image processing

作者： Wun-Ye Ku Yi-Shin Liou Chih-Yu Yang Ming-Yih Lee Chung-Chih Lin Wen-Yen Lin Tsai-Hsuan Tsai Computer Science and Information Engineering Healthy Aging Research Center Chang Gung University Graduate Institute of Medical Mechatronics Chang Gung University Department of Neurosurgery Chang Gung Memorial Hospital Department of Electrical Engineering Chang Gung University Department of Industrial Design Chang Gung University

we design a low energy Bluetooth(BLE) device including reference-tag-based indoor position algorithm to solve different situations including location determining, route guideline and tracking in this *** can not only help the visitor or patient to understand the position but also provide a system for medical staff to monitor the safety of patients and new born babies in *** device is tiny enough to be embedded into visitor's wristband, baby's foot band and patient's *** is composed of signal control unit, signal sensing unit and wireless connection *** signal control unit is responsible to control and memorize the status of the device by an ultra-low power MCU and an EEPROM memory *** signal sensing unit is a motion tracking sensor module to capture the accelerometer *** wireless connection unit combined of beacon and Bluetooth module to send data package as a BLE *** indoor location-based services(LBS) system is combined with smart beacon and Wi-Fi *** plays the role of client and Wi-Fi gateway is *** RSSI(Received signal Strength Indicator) of BLE signal to determine whether the beacon owner is in a particular ***, there may be two or more Wi-Fi gateways to receive the same beacon signal in the same time, we add a reference beacon to each Wi-Fi gateway to reduce the error rate of determining beacon's *** result of experim ent shows that there is only 5% error rate for determining the position of devices.

关键词： smart wearable device wireless beacon indoor positioning

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