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Le Touquet - Paris-Plage, France

Trocan M.,Graduate School of Engineers in Paris | Tramel E.W.,Mississippi State University | Fowler J.E.,Mississippi State University
Proceedings - International Conference on Image Processing, ICIP | Year: 2010

Compressed sensing is applied to multiview image sets and interimage disparity compensation is incorporated into image reconstruction in order to take advantage of the high degree of interimage correlation common to multiview scenarios. Instead of recovering images in the set independently from one another, two neighboring images are used to calculate a prediction of a target image, and the difference between the original measurements and the compressed-sensing projection of the prediction is then reconstructed as a residual and added back to the prediction in an iterated fashion. The proposed method shows large gains in performance over straightforward, independent compressed-sensing recovery. Additionally, projection and recovery are block-based to significantly reduce computation time. © 2010 IEEE. Source


Trocan M.,Graduate School of Engineers in Paris
International Journal of Intelligent Information and Database Systems | Year: 2014

Interlaced video acquisition and transmission, used as a simple way of increasing motion quality in video sequences, all by respecting the bandwidth constraints of progressive format representation, has been extensively used by analogue transmission systems. However, considering that nowadays the television sets and the flat screens can display only progressive format input, ensuring a smooth and high quality interlaced to progressive format conversion represents a challenging task. If till present, interpolation-based like solutions have been preferred for performing this conversion, in this paper we use an inverse problem formulation for video deinterlacing and propose a motion-compensated total-variation-minimisation-based reconstruction algorithm for solving it. A first recovery of the progressive frame is obtained using a contour-preserving interpolation method and further used for triggering a bidirectional motion-compensated prediction for the current field. A motion-compensated residual is calculated as difference between the current field and the projection of its temporal prediction using the same parity sampling matrix. This field residual is further reconstructed using a total-variation regularisation method and added back to the motion-compensated prediction to form the final progressive frame. As shown by the experimental results, the proposed deinterlacing method presents high quality progressive frame reconstructions compared to classical deinterlacing approaches. Copyright © 2014 Inderscience Enterprises Ltd. Source


Mroueh L.,Graduate School of Engineers in Paris | Belfiore J.-C.,Telecom ParisTech
IEEE Transactions on Wireless Communications | Year: 2012

In this paper, we study the feasibility of the interference alignment (IA) scheme for the selective fading interference channel with time-frequency selective links. Unlike the frequency selective channel case, we show here that, for the scalar time-frequency (TF) selective underspread channels, there is no need to scale the bandwidth as the number of users. However, a constraint on the delay-Doppler spread of the channel itself is required. A physical interpretation of this condition in the time-frequency domain is provided and is shown to be easily satisfied in practical system. Our results are based on the polynomial channel decomposition that we derive for the TF channel with large signal duration and bandwidth. © 2012 IEEE. Source


Jandhyala S.,Indian Institute of Science | Abraham A.,Indian Institute of Science | Anghel C.,Graduate School of Engineers in Paris | Mahapatra S.,Indian Institute of Science
IEEE Transactions on Electron Devices | Year: 2012

Charge linearization techniques have been used over the years in advanced compact models for bulk and double-gate MOSFETs in order to approximate the position along the channel as a quadratic function of the surface potential (or inversion charge densities) so that the terminal charges can be expressed as a compact closed-form function of source and drain end surface potentials (or inversion charge densities). In this paper, in case of the independent double-gate MOSFETs, we show that the same technique could be used to model the terminal charges quite accurately only when the 1-D Poisson solution along the channel is fully hyperbolic in nature or the effective gate voltages are same. However, for other bias conditions, it leads to significant error in terminal charge computation. We further demonstrate that the amount of nonlinearity that prevails between the surface potentials along the channel actually dictates if the conventional charge linearization technique could be applied for a particular bias condition or not. Taking into account this nonlinearity, we propose a compact charge model, which is based on a novel piecewise linearization technique and shows excellent agreement with numerical and Technology Computer-Aided Design (TCAD) simulations for all bias conditions and also preserves the source/drain symmetry which is essential for Radio Frequency (RF) circuit design. The model is implemented in a professional circuit simulator through Verilog-A, and simulation examples for different circuits verify good model convergence. © 2012 IEEE. Source


Trocan M.,Graduate School of Engineers in Paris
Advances in Intelligent Systems and Computing | Year: 2013

With the apparition of digital television and flat displays, interlaced to progressive frame format conversion represents an importantant video systems feature. In this chapter, we use an inverse problem formulation for video deinterlacing and propose a two-step sparse-reconstruction algorithm for solving it. Firstly, an edge-preserving approximation of the progressive frame is obtained and used for triggering a bidirectional motion-compensated prediction for the current field. In a second step, a sparse residual is calculated as difference between the current field and the projection of its temporal prediction using the same parity sampling matrix. This field residual is further reconstructed using a total-variation regularization method and added back to the motion-compensated prediction to form the final progressive frame. The proposed deinterlacing method presents high quality results compared to other deinterlacing approaches. Source

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