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Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie 2017 University of Dayton

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window.

The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video ...


Smooth Operator: Control Using The Smooth Robustness Of Temporal Logic, Yash Vardhan Pant, Houssam Abbas, Rahul Mangharam 2017 University of Pennsylvania

Smooth Operator: Control Using The Smooth Robustness Of Temporal Logic, Yash Vardhan Pant, Houssam Abbas, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

Modern control systems, like controllers for swarms of quadrotors, must satisfy complex control objectives while withstanding a wide range of disturbances, from bugs in their software to attacks on their sensors and changes in their environments. These requirements go beyond stability and tracking, and involve temporal and sequencing constraints on system response to various events. This work formalizes the requirements as formulas in Metric Temporal Logic (MTL), and designs a controller that maximizes the robustness of the MTL formula. Formally, if the system satisfies the formula with robustness r, then any disturbance of size less than r cannot cause it ...


Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, Renliang Gu, Aleksandar Dogandžić 2017 Iowa State University

Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, Renliang Gu, Aleksandar Dogandžić

Electrical and Computer Engineering Publications

Abstract: We develop a projected Nesterov's proximal-gradient (PNPG) approach for sparse signal reconstruction that combines adaptive step size with Nesterov's momentum acceleration. The objective function that we wish to minimize is the sum of a convex differentiable data-fidelity (negative log-likelihood (NLL)) term and a convex regularization term. We apply sparse signal regularization where the signal belongs to a closed convex set within the closure of the domain of the NLL; the convex-set constraint facilitates flexible NLL domains and accurate signal recovery. Signal sparsity is imposed using the ℓ1 -norm penalty on the signal's linear transform coefficients ...


On The Simulation And Mitigation Of Anisoplanatic Optical Turbulence For Long Range Imaging, Russell C. Hardie, Daniel A. LeMaster 2017 University of Dayton

On The Simulation And Mitigation Of Anisoplanatic Optical Turbulence For Long Range Imaging, Russell C. Hardie, Daniel A. Lemaster

Russell C. Hardie

We describe a numerical wave propagation method for simulating long range imaging of an extended scene under anisoplanatic conditions. Our approach computes an array of point spread functions (PSFs) for a 2D grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. To validate the simulation we compare simulated outputs with the theoretical anisoplanatic tilt correlation and differential tilt variance. This is in addition to comparing the long- and short-exposure PSFs, and isoplanatic angle. Our validation analysis shows an ...


Recursive Non-Local Means Filter For Video Denoising With Poisson-Gaussian Noise, Redha A. Almahdi, Russell C. Hardie 2017 University of Dayton

Recursive Non-Local Means Filter For Video Denoising With Poisson-Gaussian Noise, Redha A. Almahdi, Russell C. Hardie

Russell C. Hardie

In this paper, we describe a new recursive Non-Local means (RNLM) algorithm for video denoising that has been developed by the current authors. Furthermore, we extend this work by incorporating a Poisson-Gaussian noise model. Our new RNLM method provides a computationally efficient means for video denoising, and yields improved performance compared with the single frame NLM and BM3D benchmarks methods. Non-Local means (NLM) based methods of denoising have been applied successfully in various image and video sequence denoising applications. However, direct extension of this method from 2D to 3D for video processing can be computationally demanding. The RNLM approach takes ...


Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay 2017 University of Dayton

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay

Russell C. Hardie

Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii ...


Comparing Multiple Turbulence Restoration Algorithms Performance On Noisy Anisoplanatic Imagery, Michael Armand Rucci, Russell C. Hardie, Alexander J. Dapore 2017 Air Force Research Laboratory

Comparing Multiple Turbulence Restoration Algorithms Performance On Noisy Anisoplanatic Imagery, Michael Armand Rucci, Russell C. Hardie, Alexander J. Dapore

Russell C. Hardie

In this paper, we compare the performance of multiple turbulence mitigation algorithms to restore imagery degraded by atmospheric turbulence and camera noise. In order to quantify and compare algorithm performance, imaging scenes were simulated by applying noise and varying levels of turbulence. For the simulation, a Monte-Carlo wave optics approach is used to simulate the spatially and temporally varying turbulence in an image sequence. A Poisson-Gaussian noise mixture model is then used to add noise to the observed turbulence image set. These degraded image sets are processed with three separate restoration algorithms: Lucky Look imaging, bispectral speckle imaging, and a ...


Degrees Of Freedom Region For An Interference Network With General Message Demands, Lei Ke, Aditya Ramamoorthy, Zhengdao Wang, Huarui Yin 2017 Qualcomm, Inc.

Degrees Of Freedom Region For An Interference Network With General Message Demands, Lei Ke, Aditya Ramamoorthy, Zhengdao Wang, Huarui Yin

Zhengdao Wang

We consider a single-hop interference network with K transmitters and J receivers, all having M antennas. Each transmitter emits an independent message and each receiver requests an arbitrary subset of the messages. This generalizes the well-known K -user M-antenna interference channel, where each message is requested by a unique receiver. For our setup, we derive the degrees of freedom (DoF) region. The achievability scheme generalizes the interference alignment schemes proposed by Cadambe and Jafar. In particular, we achieve general points in the DoF region by using multiple base vectors and aligning all interferers at a given receiver to the interferer ...


Degrees Of Freedom Region For An Interference Network With General Message Demands, Lei Ke, Aditya Ramamoorthy, Zhengdao Wang, Huarui Yin 2017 Qualcomm, Inc.

Degrees Of Freedom Region For An Interference Network With General Message Demands, Lei Ke, Aditya Ramamoorthy, Zhengdao Wang, Huarui Yin

Zhengdao Wang

We consider a single hop interference network with K transmitters, each with an independent message and J receivers, all having the same number (M) of antennas. Each receiver requests an arbitrary subset of the messages. This generalizes the well-known K user M antenna interference channel, where each message is requested by a unique receiver. For this setup, we derive the exact degrees of freedom (DoF) region. Our achievability scheme generalizes the interference alignment scheme proposed by Cadambe and Jafar '08. In particular, we achieve general points in the DoF region by using multiple base vectors and aligning the interference at ...


Neural Networks Skin Tumor Diagnostic System, Zhao Zhang, William V. Stoecker, Randy Hays Moss 2017 Missouri University of Science and Technology

Neural Networks Skin Tumor Diagnostic System, Zhao Zhang, William V. Stoecker, Randy Hays Moss

Zhao Zhang

In this study, a malignant melanoma diagnostic system is designed using a straightforward neural network with the back-propagation learning algorithm. Eleven features are automatically extracted from skin tumor images. The correct diagnostic rate of this system is better than the average rate of 16 dermatologists who based their diagnosis with only the slide images.


A Novel Morphological Operator To Calculate Euler Number, Zhao Zhang, Randy Hays Moss, William V. Stoecker 2017 Missouri University of Science and Technology

A Novel Morphological Operator To Calculate Euler Number, Zhao Zhang, Randy Hays Moss, William V. Stoecker

Zhao Zhang

This paper introduces a novel morphological operator to calculate the Euler number for binary images. The operator is based on the condition of eight-connectedness for foreground and four-connectedness for background. It is significantly faster than the previous operators. The morphological operations used in border detection are discussed


On Non-Cooperative Multiple-Target Tracking With Wireless Sensor Networks, Ye Zhu, A. Vikram, Huirong Fu, Yong Guan 2017 Cleveland State University

On Non-Cooperative Multiple-Target Tracking With Wireless Sensor Networks, Ye Zhu, A. Vikram, Huirong Fu, Yong Guan

Yong Guan

In this paper, we propose an approach to track multiple non-cooperative targets with wireless sensor networks. Most existing tracking algorithms can not be directly applied to non-cooperative target tracking because they assume the access to signals from individual targets for tracking by assuming that: 1) there is only one target in a field; 2) signals from different co-operative targets can be differentiated; or 3) interference caused by signals from other targets is negligible because of attenuation. We propose a general approach for tracking non-cooperative targets. The tracking algorithm first separates the aggregate signals from multiple indistinguishable targets via the blind ...


Formalization Of Matrix Theory In Hol4, Zhiping Shi, Yan Zhang, Zhenke Liu, Xinan Kang, Yong Guan, Jie Zhang, Xiaoyu Song 2017 Chinese Academy of Sciences

Formalization Of Matrix Theory In Hol4, Zhiping Shi, Yan Zhang, Zhenke Liu, Xinan Kang, Yong Guan, Jie Zhang, Xiaoyu Song

Yong Guan

Matrix theory plays an important role in modeling linear systems in engineering and science. To model and analyze the intricate behavior of complex systems, it is imperative to formalize matrix theory in a metalogic setting. This paper presents the higherorder logic (HOL) formalization of the vector space and matrix theory in the HOL4 theorem proving system. Formalized theories include formal definitions of real vectors and matrices, algebraic properties, and determinants, which are verified in HOL4. Two case studies, modeling and verifying composite two-port networks and state transfer equations, are presented to demonstrate the applicability and effectiveness of our work.


Game-Day Football Visualization Experience On Dissimilar Virtual Reality Platforms, Vijay Kalivarapu, Anastacia Maria MacAllister, Melynda Tess Hoover, Shubang Sridhar, Jonathan Andrew Schlueter, Anthony Civitate, Phillip Thompkins, Jesse Smith, Janae Hoyle, James H. Oliver, Eliot H. Winer, Gerrit Chernoff 2017 Iowa State University

Game-Day Football Visualization Experience On Dissimilar Virtual Reality Platforms, Vijay Kalivarapu, Anastacia Maria Macallister, Melynda Tess Hoover, Shubang Sridhar, Jonathan Andrew Schlueter, Anthony Civitate, Phillip Thompkins, Jesse Smith, Janae Hoyle, James H. Oliver, Eliot H. Winer, Gerrit Chernoff

Vijay K Kalivarapu

College football recruiting is a competitive process. Athletic administrations attempt to gain an edge by bringing recruits to a home game, highlighting the atmosphere unique to campus. This is however not always possible since most recruiting efforts happen off-season. So, they relate the football game experience through video recordings and visits to football facilities. While these substitutes provide a general idea of a game, they cannot capture the feeling of playing while cheered on by a crowd of 55,000 people. To address this challenge and improve the recruitment process, the Iowa State University (ISU) athletic department and the Virtual ...


Damage Detection On Mesosurfaces Using Distributed Sensor Network And Spectral Diffusion Maps, Venkatesh Chinde, Liang Cao, Umesh Vaidya, Simon Laflamme 2017 Iowa State University

Damage Detection On Mesosurfaces Using Distributed Sensor Network And Spectral Diffusion Maps, Venkatesh Chinde, Liang Cao, Umesh Vaidya, Simon Laflamme

Umesh Vaidya

In this work, we develop a data-driven method for the diagnosis of damage in mesoscale mechanical structures using an array of distributed sensor networks. The proposed approach relies on comparing intrinsic geometries of data sets corresponding to the undamaged and damaged states of the system. We use a spectral diffusion map approach to identify the intrinsic geometry of the data set. In particular, time series data from distributed sensors is used for the construction of diffusion maps. The low dimensional embedding of the data set corresponding to different damage levels is obtained using a singular value decomposition of the diffusion ...


Experimental Data Analysis Of The Vortex Structures In The Wakes Of Flapping Wings, Kai Wang, Umesh Vaidya, Baskar Ganapathysubramanian, Hui Hu 2017 Iowa State University

Experimental Data Analysis Of The Vortex Structures In The Wakes Of Flapping Wings, Kai Wang, Umesh Vaidya, Baskar Ganapathysubramanian, Hui Hu

Umesh Vaidya

The objective of this paper is to compare the existing methods and develop novel approaches for the experimental data analysis of the unsteady aerodynamics of the flapping wing microaerial-vehicle. These methods are developed for the purpose of identification of the beneficial dynamics and for the development of reduced order models for control design. We first employ Proper Orthogonal Decomposition (POD) method for the data analysis of the PIV measurements in the wakes of piezoelectric flapping wings. The basic idea behind POD based data analysis method is to decompose the time series snapshots of PIV measurements into high energy, POD, modes ...


Experimental Data Analysis Of The Vortex Structures In The Wakes Of Flapping Wings, Kai Wang, Umesh Vaidya, Baskar Ganapathysubramanian, Hui Hu 2017 Iowa State University

Experimental Data Analysis Of The Vortex Structures In The Wakes Of Flapping Wings, Kai Wang, Umesh Vaidya, Baskar Ganapathysubramanian, Hui Hu

Baskar Ganapathysubramanian

The objective of this paper is to compare the existing methods and develop novel approaches for the experimental data analysis of the unsteady aerodynamics of the flapping wing microaerial-vehicle. These methods are developed for the purpose of identification of the beneficial dynamics and for the development of reduced order models for control design. We first employ Proper Orthogonal Decomposition (POD) method for the data analysis of the PIV measurements in the wakes of piezoelectric flapping wings. The basic idea behind POD based data analysis method is to decompose the time series snapshots of PIV measurements into high energy, POD, modes ...


Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie 2017 University of Dayton

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Russell C. Hardie

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window. The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video ...


Simulation Of Anisoplanatic Imaging Through Optical Turbulence Using Numerical Wave Propagation With New Validation Analysis, Russell C. Hardie, Jonathan D. Power, Daniel A. LeMaster, Douglas R. Droege, Szymon Gladysz, Santasri Bose-Pillai 2017 University of Dayton

Simulation Of Anisoplanatic Imaging Through Optical Turbulence Using Numerical Wave Propagation With New Validation Analysis, Russell C. Hardie, Jonathan D. Power, Daniel A. Lemaster, Douglas R. Droege, Szymon Gladysz, Santasri Bose-Pillai

Russell C. Hardie

We present a numerical wave propagation method for simulating imaging of an extended scene under anisoplanatic conditions. While isoplanatic simulation is relatively common, few tools are specifically designed for simulating the imaging of extended scenes under anisoplanatic conditions. We provide a complete description of the proposed simulation tool, including the wave propagation method used. Our approach computes an array of point spread functions (PSFs) for a two-dimensional grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. The degradation ...


Block Matching And Wiener Filtering Approach To Optical Turbulence Mitigation And Its Application To Simulated And Real Imagery With Quantitative Error Analysis, Russell C. Hardie, Michael Armand Rucci, Barry K. Karch, Alexander J. Dapore 2017 University of Dayton

Block Matching And Wiener Filtering Approach To Optical Turbulence Mitigation And Its Application To Simulated And Real Imagery With Quantitative Error Analysis, Russell C. Hardie, Michael Armand Rucci, Barry K. Karch, Alexander J. Dapore

Russell C. Hardie

We present a block-matching and Wiener filtering approach to atmospheric turbulence mitigation for long-range imaging of extended scenes. We evaluate the proposed method, along with some benchmark methods, using simulated and real-image sequences. The simulated data are generated with a simulation tool developed by one of the authors. These data provide objective truth and allow for quantitative error analysis. The proposed turbulence mitigation method takes a sequence of short-exposure frames of a static scene and outputs a single restored image. A block-matching registration algorithm is used to provide geometric correction for each of the individual input frames. The registered frames ...


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