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25th European signal processing conference, EUSIPCO 2017

作者： Burak Kocamis, M. Oktem, Figen S. Department of Electrical and Electronics Engineering Middle East Technical University Cankaya Ankara06800 Turkey

ISBN: (纸本)9780992862671

Near-field ultrawideband imaging is a promising remote sensing technique in various applications such as airport security, surveillance, medical diagnosis, and through-wall imaging. Recently, there has been increasing interest in using sparse multiple-input-multiple-output (MIMO) arrays to reduce hardware complexity and cost. In this paper, based on a Bayesian estimation framework, an optimal design method is presented for two-dimensional MIMO arrays in ultrawideband imaging. The optimality criterion is defined based on the image reconstruction quality obtained with the design, and the optimization is performed over all possible locations of antenna elements using an algorithm called clustered sequential backward selection algorithm. The designs obtained with this approach are compared with that of some commonly used sparse array configurations in terms of image reconstruction quality for various noise levels. © EURASIP 2017.

关键词： image reconstruction

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Custom processor design for efficient, yet flexible Lucas-Kanade optical flow

Custom processor design for efficient, yet flexible Lucas-Ka...

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conference on design and architectures for signal and image processing

作者： Sander Smets Toon Goedemé Marian Verhelst ESAT - MICAS KU Leuven Leuven Belgium EAVISE - PSI KU Leuven Sint-Katelijne-Waver Belgium

ISBN: (纸本)9781509030859

State-of-the-art solutions to optical flow fail to jointly offer high density flow estimation, low power consumption and real time operation, rendering them unsuitable for embedded applications. Joint hardware-software scalability at run-time is crucial to achieve these conflicting requirements in one device. This paper therefore presents a scalable Lucas-Kanade optical flow algorithm, together with a flexible power-optimized processor architecture. The C-programmable processor exploits algorithmic scalability through innovations in its memory structure, memory interface, and datapath optimized for efficient convolutions. Jointly, the scalable flow algorithm and optimized computer vision hardware platform enable applications to on-the-fly trade-off throughput and power consumption in function of flow density and accuracy. The processor chip is synthesized in 40nm CMOS technology and verified on FPGA. The architecture is capable of scaling the frame rate at run-time and processes 16fps of dense optical flow at 640×480 resolution with 15.06° average angular error, while only consuming 24mW.

关键词： Optical imaging Adaptive optics Optical sensors Estimation Computer architecture Power demand Scalability

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Robot navigation based on an efficient combination of an extended A∗ algorithm, bird's eye view and image stitching

Robot navigation based on an efficient combination of an ext...

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conference on design and architectures for signal and image processing

作者： Jens Rettkowski David Gburek Diana Göhringer Application-Specific Multi-Core Architectures (MCA) Group Ruhr-University Bochum (RUB) Germany

Robotics combines a lot of different domains with sophisticated challenges such as computer vision, motion control and search algorithms. Search algorithms can be applied to calculate movements. The A* algorithm is a well-known and proved search algorithm to find a path within a graph. This paper presents an extended A* algorithm that is optimized for robot navigation using a bird's eye view as a map that is dynamically generated by image stitching. The scenario is a robot that moves to a target in an environment containing obstacles. The robot is controlled by a Xilinx Zynq platform that contains an ARM processor and an FPGA. In order to exploit the flexibility of such an architecture, the FPGA is used to execute the most compute-intensive task of the extended A* algorithm. This task is responsible for sorting the accessible nodes in the graph. Several environments with different complexity levels are used to evaluate the extended A* algorithm. The environment is captured by a Kinect sensor located directly on the robot. In order to dewarp the robot's view, the frames are transformed to a bird's eye view. In addition, a wider viewing range is achieved by image stitching. The evaluation of the extended A* algorithm shows a significant improvement in terms of memory utilization. Accordingly, this algorithm is especially practicable for embedded systems since they have often only limited memory resources. Moreover, the overall execution time for several use cases is reduced up to a speed-up of 2.88x.

关键词： Heuristic algorithms Navigation Cameras Robot vision systems Path planning

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A Digital Control Mechanism for the Delay of a Dual-Microphone Analog Beamformer 2

A Digital Control Mechanism for the Delay of a Dual-Micropho...

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International conference on Optimization of Electrical and Electronic Equipment (OPTIM) / Intl Aegean conference on Electrical Machines and Power Electronics (ACEMP)

作者： Farago, Paul Hintea, Sorin Sandu, Florin Tech Univ Cluj Napoca Cluj Napoca Romania Transilvania Univ Brasov Brasov Romania

ISBN: (纸本)9781509044894

The microelectronic industry is driven by the continuous demand for processing capabilities and performance. As such, most processing is performed nowadays in a digital fashion. Analog however is not to be neglected. A key feature in modern mixed-signal processing is wide-range tuning of the analog processing sections. One step forward is the implementation of digitally programmable analog. The aim of this paper is to illustrate the digital tuning mechanism on the analog beamformer of a dual-microphone array. Analog processing consists of having one microphone signal delayed by an allpass filter, in order to be synchronized to the other microphone signal. A Gm-C filter implementation was considered, and filter tuning was performed via the transconductor bias current. Digital control of the bias current was implemented with a current digital to analog converter, enabling a straightforward and simple control mechanism. Transistor-level simulation results validate the proposed design.

关键词： signal and image processing filtering

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Hybrid Technique for Robust image Watermarking Using Discrete Time Fourier Transform 25

Hybrid Technique for Robust Image Watermarking Using Discret...

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25th signal processing and Communications Applications conference (SIU)

作者： Abodena, Omar Agoyi, Mary Celebi, Erbug Cyprus Int Univ Inst Grad Studies & Res Dept Management Informat Syst Via Mersin 10 Lefkosa Kktc Turkey Cyprus Int Univ Fac Engn Dept Comp Engn Via Mersin 10 Lefkosa Kktc Turkey

ISBN: (纸本)9781509064946

The current paper proposes a novel scheme for nonblind watermarking of images, making use of discrete wavelet transform (DWT), discrete time Fourier transform (DTFT), as well as singular value decomposition, or SVD. During the process of embedding, 1-level DWT is used to decompose the host image into its various frequency sub-bands. After this, the high-frequency sub band receives an application of DTFT. This is followed then by SVD, after which the watermark becomes embedded into the nowtransformed host image's singular matrix. Then, the inverses of 1-level DWT, DTFT and SVD are applied in order to obtain a watermarked final image. This paper evaluates the performance of the proposed method of watermarking against a number of attacks, including sharpening, salt and pepper noise, AWGN, gamma correction, histogram equalisation, flipping and cropping. Results obtained during experiments have found that the scheme as proposed does provide high levels of robustness and imperceptibility against various signal processing attacks.

关键词： singular value decomposition discrete wavelet transform discrete time Fourier transform

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Self-sustained UWB Sensing: A Link and Energy Adaptive Approach

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JOURNAL OF signal processing SYSTEMS FOR signal image AND VIDEO TECHNOLOGY 2017年第2期88卷 233-243页

作者： Chen, Junlin Zhao, Dong Wang, Lei Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

Energy efficiency is a challenging issue in autonomous and distributed sensing systems, especially when these systems are powered by renewable energy sources. In this paper, we present a link and energy adaptive UWB-based sensing technique to improve the detection time coverage and detection range coverage for self-sustained embedded applications. The basic idea is derived from the fact that domain-specific information in such applications is often available. Thus, by jointly exploiting the link information between the transmitter and receiver of the UWB pulse radar, and the non-deterministic characteristics of the renewable energy, the proposed technique dynamically adjusts the pulse repetition frequency of the UWB radar to enhance the sustainable operation under the unreliable energy supply. The overhead of the proposed technique is negligible as compared with the overall energy consumption of the UWB pulse radar. It was demonstrated that the proposed technique can achieve much better detection time coverage and detection range coverage than the conventional UWB radar. The proposed technique is also insensitive to many practical issues such as the limited battery capacity.

关键词： Energy efficiency Real-time and embedded systems Self-sustained systems Low-power design Adaptive architectures

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A highly efficient and comprehensive image processing library for c++-based high-level synthesis 4

A highly efficient and comprehensive image processing librar...

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International Workshop on FPGAs for Software Programmers, FSP 2017, co-located with International conference on Field Programmable Logic and Applications, FPL 2017

作者： Akif Özkan, M. Reiche, Oliver Hannig, Frank Teich, Jürgen Germany

ISBN: (纸本)9783800744435

Field Programmable Gate Arrays (FPGAs) are proved to be among the most suitable architectures for image processing applications. However, accelerating algorithms using FPGAs is a time-consuming task and needs expertise. Whereas the recent advancements in High-Level Synthesis (HLS) promise to solve this problem, today's HLS tools require apt hardware descriptions of algorithms to be able to provide favorable implementations. A solution is developing highly parameterizable and optimized HLS libraries for the fundamental image processing components. Another solution is providing a higher level of abstraction in the form of a Domain-Specific Language (DSL) and a corresponding efficient back end for hardware design. In this paper, we provide a highly efficient and parameterizable C++ library for image processing applications, which would be the cornerstone for both approaches. In our library, nodes of a stream-based data flow graph can be described as C++ objects for specified functions, and the whole application can be efficiently parallelized just by defining a global constant as the parallelization factor. Moreover, the key hardware design elements, i. e., line buffers and sliding windows with different border handling patterns, can be utilized individually to ease the design of more complicated applications. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach

关键词： High level synthesis

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MULTI-MODAL/MULTI-SCALE CONVOLUTIONAL NEURAL NETWORK BASED IN-LOOP FILTER design FOR NEXT GENERATION VIDEO CODEC 24

MULTI-MODAL/MULTI-SCALE CONVOLUTIONAL NEURAL NETWORK BASED I...

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24th IEEE International conference on image processing (ICIP)

作者： Kang, Jihong Kim, Sungjei Lee, Kyoung Mu Seoul Natl Univ Dept ECE ASRI Seoul South Korea Korea Elect Technol Inst Seongnam Si South Korea

ISBN: (纸本)9781509021758

In this paper, we propose a novel in-loop filter design for video compression. Our approach aims to replace existing deblocking filter and SAO (Sample Adaptive Offset) of HEVC standard with multi-modal/multi-scale convolutional neural network (MMS-net). The proposed CNN architecture consists of two sub-networks of different scales. An input image is down-sampled first and restored through the lower scale network, then the output image from it is fed into higher scale network concatenated with the original input image. Moreover, to boost the restoration performance, the proposed architecture utilizes information resides in the coded sequence. Specifically, the compression parameters from coding tree units (CTU) are exploited as input to CNN, which helps to alleviate blocking artifacts on the reconstructed images. In the experiments, our method reduces the average BD-rate by 4.55% and 8.5%, respectively, compared with the conventional neural network based approach [1] and HEVC reference software HM16.7 [2] in `All Intra -Main' configuration.

关键词： In-loop filter HEVC CNN video compression image restoration

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A Filter Bank Architecture Based on Wavelet Transform for ECG signal Denoising 4

A Filter Bank Architecture Based on Wavelet Transform for EC...

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4th IEEE International conference on signal processing, Computing and Control (ISPCC)

作者： Kumar, Ashish Tiwari, Rakesh N. Kumar, Manjeet Kumar, Yogendera Bennett Univ Dept Elect & Commun Engn Greater Noida India Raffles Univ Neemrana Dept Elect & Commun Engn Neemrana Rajasthan India Galgotias Univ Sch Elect Elect & Commun Engn Greater Noida India

ISBN: (纸本)9781509058389

One of the most important aspects of the electrocardiogram (ECG) signal processing is the removal of noises from the signals. In the present work a filter bank architecture based on wavelet transform is proposed for this purpose. Proposed design uses four levels of wavelet transform based filter bank for the ECG signals denoising. A digitized ECG signal is applied as an input to the four levels of wavelet transform based filter bank that separates the ECG signal from the noises. Obtained results show that the proposed architecture requires less hardware, small area on the chip and lower cost compared to the previously designed architectures.

关键词： Electrocardiogram Integrated Circuit Wavelet Transform

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Associative Memory based on clustered Neural Networks: Improved model and architecture for Oriented Edge Detection

Associative Memory based on clustered Neural Networks: Impro...

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conference on design and architectures for signal and image processing

作者： Robin Danilo Hugues Nono Wouafo Cyrille Chavet Vincent Gripon Laura Conde-Canencia Philippe Coussy Lab-STICC Université de Bretagne-Sud Morbihan France Electronics Department Télécom Bretagne Brest France

ISBN: (纸本)9781509030859

Associative Memories (AM) are storage devices that allow addressing content from part of it, in opposition of classical index-based memories. This property makes them promising candidates for various search challenges including pattern detection in images. Clustered based Neural Networks (CbNN) allow efficient design of AM by providing fast pattern retrieval, especially when implemented in hardware. In particular, they can be used to store and next quickly identify oriented edges in images. However, current models of CbNN only provide good performances when facing erasures in the inputs. This paper introduces several improvements to the CbNN model in order to cope with intrusion and additive noises. Namely, we change the initialization of neurons to account for precise information depending on Euclidean distance. We also update the activation rules accordingly, resulting in an efficient handling of various types of input noise. To complete this paper, associated hardware architectures are presented along with the proposed computation models and those are compared with the existing CbNN implementation. Synthesis results show that among them, several divide the cost of that implementation by 3 while increasing the maximal frequency by 25%.

关键词： Neurons Associative memory image edge detection Computer architecture Hardware Decoding Neural networks

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