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Compression of Bayer Colour Filter array Images 4

Compression of Bayer Colour Filter Array Images

引用

4th ieee International Conference on Recent Trends on Electronics, Information, Communication and Technology (RTEICT)

作者： Patil, Shridhar Deepika, P. RV Coll Engn Dept Elect & Commun Engn Bengaluru India

ISBN: (纸本)9781728106304;9781728106311

Bayer Colour Filter array is a matrix of photosensors covered with red, green, and blue colour filters. this setup is advantageous in smartphones as only a third of the required data is captured by the sensor in the camera. the rest of the components based on the colour format can be interpolated using a suitable algorithm to arrive at a full-colour image. Increasing the resolution of the camera sensor will translate to increased bandwidth in the image signal processing pipeline, and consequently power consumption. In addition to that, the bit depth is also on the rise to enhance the colours. these two factors will create a huge impact on the data to be handled in the pertinent processor. Hence, compression of the Bayer data is of immense significance. the existing standard compression schemes can be adapted to suit the Bayer format. Also, several compression schemes, specific to Bayer format have been proposed. Two compression methods, viz. JPEG-LS and Hierarchical Prediction based compression have been tested and the corresponding results are presented in this paper. the former is a standard while the latter has been proposed keeping the Bayer format in mind. Modelling of the algorithms shows that JPEG-LS is best suited in the use cases where lossless compression is desirable, and Hierarchical Prediction based compression is the better option where some amount of loss is acceptable.

关键词： Bayer format LOCO-I Hierarchical Prediction Entropy coding Context modelling

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Adaptive pulse design for space-time adaptive processing

Adaptive pulse design for space-time adaptive processing

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sensor array and multichannel signal processing workshop

作者： Lee K. Patton Daniel E. Hack Braham Himed Matrix Research Dayton Ohio WPAFB Air Force Research Laboratory Ohio

Space-time adaptive processing (STAP) is used in radar to adaptively suppress both ground clutter returns and radio frequency interference (RFI). However, RFI suppression utilizes degrees-of-freedom that would otherwise be applied to clutter suppression. this paper considers designing the transmit pulse so that fast-time correlated (i.e., colored) RFI is suppressed in the pulse-compression stage preceding the STAP processor. the objective function and constraints for the waveform optimization are derived, and a numerical example demonstrating the efficacy of the approach is provided.

关键词： Clutter Jamming Noise Vectors Radar Covariance matrix

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Distributed Detection and Imaging in MIMO Radar Network Based on Averaging Consensus

Distributed Detection and Imaging in MIMO Radar Network Base...

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sensor array and multichannel signal processing workshop

作者： Anton A. Zabolotsky Evgeny A. Mavrychev Dept. of Informational Radio Systems Nizhny Novgorod State Technical University Nizhny Novgorod Russia

In this paper, we consider distributed signal processing in a MIMO radar network. We suppose that transmitting and receiving nodes of MIMO radar are distributed in a large-scale area. In this network the neighboring receiving nodes communicate with each other to exchange data. A fully distributed algorithm for detection and imaging is proposed. this algorithm is based on the averaging consensus approach. the effectiveness of the proposed technique is confirmed by numerical examples. It is compared to the centralized solution in a fusion center, the local solution in an individual receiving node and the proposed distributed algorithm.

关键词： MIMO radar Radar imaging signal processing algorithms Detectors Artificial neural networks Radar antennas

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Algorithms for tracking with an array of magnetic sensors

Algorithms for tracking with an array of magnetic sensors

引用

sensor array and multichannel signal processing workshop

作者： Richard J. Kozick Brian M. Sadler Bucknell University Lewisburg PA USA Army Research Laboratory Adelphi MD USA

We consider the problem of tracking a magnetic target as it travels in a straight-line path in the vicinity of N magnetic sensors. the target is modeled as a magnetic dipole, and we study tracking algorithms when the sensors are total-field (scalar) magnetometers and vector magnetometers. A novel, computationally-efficient vector-field algorithm is presented that jointly processes the data from N sensors, yielding estimates of the track and the target dipole moment vector. Simulation examples are included to illustrate the performance of the total-field and vector algorithms.

关键词： sensors Magnetic sensors Target tracking Magnetic field measurement Magnetometers Magnetic fields Magnetostatics

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Consistent Least Squares Estimator for Co-array-Based DOA Estimation

Consistent Least Squares Estimator for Co-Array-Based DOA Es...

引用

sensor array and multichannel signal processing workshop

作者： Saeid Sedighi R Bhavani Shankar Mysore Sina Maleki Björn Ottersten Reliability and Trust (SnT) University of Luxembourg

Sparse linear arrays (SLAs), such as nested and co-prime arrays, have the attractive capability of providing enhanced degrees of freedom by exploiting the co-array model. Accordingly, co-array-based Direction of Arrivals (Doas) estimation has recently gained considerable interest in array processing. the literature has suggested applying MUSIC on an augmented sample covariance matrix for co-array-based Doas estimation. In this paper, we propose a Least Squares (LS) estimator for co-array-based DoAs estimation employing the covariance fitting method as an alternative to MUSIC. We show that the proposed LS estimator provides consistent estimates of Doas of identifiable sources for SLAs. Additionally, an analytical expression for the large sample performance of the proposed estimator is derived. Numerical results illustrate the finite sample behavior in relation to the derived analytical expression. Moreover, the performance of the proposed LS estimator is compared to the co-array-based MUSIC.

关键词： Covariance matrices Direction-of-arrival estimation Multiple signal classification Estimation array signal processing sensor arrays Geometry

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Buried object localization using direct algorithm

Buried object localization using direct algorithm

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sensor array and multichannel signal processing workshop

作者： Zineb Mehel - Saidi Salah Bourennane Caroline Fossati CRAN-ESSTIN/UHP Vandoeuvre-les-Nancy France Institut Fresnel UMR CNRS 6133 Ecole Centrale Marseille Marseilles France

this study deals with buried object localization using a towed flexible array of sensors. So, the phases of the received signals deviate from the assumed plane wave model by the phase errors which are due to the random distortions of the antenna. In this letter, an objective function is defined and a new source steering vector including the acoustic scattering model at each sensor is proposed. the robust DIRECT (DIviding RECTangles) method is applied to minimize this objective function for estimating the bearings and the ranges of objects together with the phase errors. To decorrelate the received signals and to estimate the coherent signal subspace a fast focusing operator is proposed . the performance of the developed method is investigated on experimental data recorded during underwater acoustic experiments.

关键词： arrays sensors Acoustic distortion Phase distortion sensor arrays Buried object detection Focusing

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Decision fusion in MIMO wireless sensor networks with channel state information

Decision fusion in MIMO wireless sensor networks with channe...

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sensor array and multichannel signal processing workshop

作者： Domenico Ciuonzo Gianmarco Romano Pierluigi Salvo Rossi Department of Information Engineering Second University of Naples Italy

We study channel-aware binary decision fusion over a Rayleigh flat fading shared channel with multiple antennas at the Decision Fusion Center (DFC). We derive the optimum and three sub-optimal fusion rules, namely the Max-Log, the Chair-Varshney - Maximum Likelihood and the Maximum Ratio Combining rules. Simulation results for the performance are presented in terms of Probability of Detection (under a fixed false alarm rate) vs SNR and number of antennas. the effect of multiple antennas at the DFC for the presented rules is analyzed, showing benefits and limitations of the choice.

关键词： Wireless sensor networks Antennas MIMO signal to noise ratio Vectors Approximation methods Fading

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Unmixing of Absence Epileptic Seizures in GAERS

Unmixing of Absence Epileptic Seizures in GAERS

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sensor array and multichannel signal processing workshop

作者： S. Akhavan R. Phlypo H. Soltanian-Zadeh M. Kamarei C. Jutten School of Electrical and Computer Engineering University of Tehran Tehran Iran CNRS GIPSA-lab Grenoble France

this research spatially and temporally investigates absence epileptic seizures using depth cortical data recorded from different layers of somatosensory cortex of Genetic Absence Epilepsy Rats from Strasbourg (GAERS). We model the recorded absence seizures by a linear superposition of a few epileptic activities which have spatio-temporal representations. Retrieving the epileptic activities from the recorded absence seizures is the main target of this study which helps us localize the onset layers of somatosensory cortex and understand the temporal evolution of recorded absence seizures.

关键词： Time series analysis Epilepsy Rats array signal processing sensor arrays Conferences

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Multi-target tracking with stored program adaptive CNN universal machines 7

Multi-target tracking with stored program adaptive CNN unive...

引用

7th ieee International workshop on Cellular Neural Networks and their Applications

作者： Rekeczky, C Tímár, G Cserey, G Hungarian Acad Sci Anal & Neural Comp Syst Lab Comp & Automat Res Inst Budapest Hungary

ISBN: (纸本)981238121X

this paper shows that the performance of multi-target tracking (MTT-1) systems can be significantly increased with stored program adaptive cellular array sensors. the primary motivation of the present work is to define a topographic microprocessor architecture for MTT with embedded sensors capable of operating in a process real-time manner. In the ongoing experiments it is assumed that the input data flow is acquired by a single array sensor and the data is processed on an adaptive CNN-UM [4] architecture consisting of both cellular nonlinear network (CNN, [1]-[7]) and digital signal processing (DSP) microprocessors. the algorithms designed for this combined hardware platform use adaptive multi-channel CNN solutions for instantaneous position estimation and morphological characterization of all visible targets and the DSP environment for distance calculation, gating, data association, track maintenance and dynamic target motion prediction. A special feature of the architecture is that it allows an interactive communication between the sensor and the digital environment. the configuration of functional modules for various real-time applications is discussed. Using real-life video-flows, successful tracking of several maneuvering targets is demonstrated within the proposed adaptive multi-channel framework.

关键词： Adaptive arrays Cellular networks Cellular neural networks Digital signal processing Microprocessors sensor arrays sensor phenomena and characterization sensor systems Target tracking Turing machines

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Generalized Cyclic Algorithms for Designing Unimodular Sequence Sets with Good (Complementary) Correlation Properties

Generalized Cyclic Algorithms for Designing Unimodular Seque...

引用

sensor array and multichannel signal processing workshop

作者： Arindam Bose Israel A. Arriaga-Trejo Aldo G. Orozco-Lugo Mojtaba Soltanalian University of Illinois at Chicago Chicago USA CONACYT - Autonomous University of Zacatecas Zacatecas Mexico CINVESTAV - National Polytechnique Institute Mexico Mexico

Unimodular sequences with good correlation properties have attracted significant research interest due to their applications in several areas such as radar sensing and communications. In this paper, we address the problem of designing unimodular sequence sets with good correlation and complementary correlation properties using generalized cyclic algorithms for the minimization of weighted integrated sidelobe level (WISL) based metrics. the set of sequences are obtained by considering their complete second-order characterization, which has been proven to be beneficial for identification and sensing systems employing widely linear signal processing. Several numerical examples have been presented to illustrate the performance of the proposed algorithms.

关键词： Correlation Minimization signal processing algorithms Measurement array signal processing sensor arrays

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