Javier Vázquez Castillo

Enhancement and Edge-Preserving Denoising: An OpenCL-Based Approach for Remote Sensing Imagery

Image enhancement and edge-preserving denoising are relevant steps before classification or other postprocessing techniques for remote sensing images. However, multisensor array systems are able to simultaneously capture several low-resolution images from the same area on different wavelengths, forming a high spatial/spectral resolution image and raising a series of new challenges. In this paper, an open computing language based parallel implementation approach is presented for near real-time enhancement based on Bayesian maximum entropy (BME), as well as an edge-preserving denoising algorithm for remote sensing imagery, which uses the local linear Steins unbiased risk estimate (LLSURE). BME was selected for its results on synthetic aperture radar image enhancement, whereas LLSURE has shown better noise removal properties than other commonly used methods. Within this context, image processing methods are algorithmically adapted via parallel computing techniques and efficiently implemented using CPUs and commodity graphics processing units (GPUs). Experimental results demonstrate the reduction of computational load of real-world image processing for near real-time GPU adapted implementation.

Geometry-Based Statistical Modeling of Non-Stationary MIMO Vehicle-to-Vehicle Channels

A novel geometry-based statistical model (GBSM) for non-stationary multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) fading channels is presented in this paper. In contrast to the existing geometrical models for non-stationary channels, which are based on a spherical wave propagation (SWP) approach, our proposal builds on the principles of plane wave propagation (PWP). This modeling approach simplifies the mathematical analysis of the relevant statistics of non-stationary channels, such as the space-time-frequency cross-correlation function (STF-CCF). To demonstrate the mathematical tractability of the model, we derive a novel closed-form expression for the STF-CCF. For that purpose, we consider a geometrical one-ring scattering model, and assume that the angle of arrival (AOA) of the received multipath signal follows the von Mises distribution. The obtained results provide valuable theoretical insights into the cross-correlation properties of non-stationary MIMO V2V fading channels.

Modeling of Non-WSSUS Double-Rayleigh Fading Channels for Vehicular Communications

This paper deals with the modeling of nonstationary time-frequency (TF) dispersive multipath fading channels for vehicle-to-vehicle (V2V) communication systems. As a main contribution, the paper presents a novel geometry-based statistical channel model that facilitates the analysis of the nonstationarities of V2V fading channels arising at a small-scale level due to the time-varying nature of the propagation delays. This new geometrical channel model has been formulated following the principles of plane wave propagation (PWP) and assuming that the transmitted signal reaches the receiver antenna through double interactions with multiple interfering objects (IOs) randomly located in the propagation area. As a consequence of such interactions, the first-order statistics of the channel model’s envelope are shown to follow a worse-than-Rayleigh distribution; specifically, they follow a double-Rayleigh distribution. General expressions are derived for the envelope and phase distributions, four-dimensional (4D) TF correlation function (TF-CF), and TF-dependent delay and Doppler profiles of the proposed channel model. Such expressions are valid regardless of the underlying geometry of the propagation area. Furthermore, a closed-form solution of the 4D TF-CF is presented for the particular case of the geometrical two-ring scattering model. The obtained results provide new theoretical insights into the correlation and spectral properties of small-scale nonstationary V2V double-Rayleigh fading channels.

Dynamic wavelet-based pilot allocation algorithm for OFDM-based cognitive radio systems

In a cognitive radio system, the goal is to make better use of the radio electric spectrum, allowing non-licensed users access to those currently unused electromagnetic bands assigned to licensed users (LUs). This can be achieved using OFDM, where the non-licensed users must select the temporarily available subcarriers and turn off those subcarriers used by LUs in order to avoid interference. Hence, only a subset of the subcarriers can be used for data or pilot tone transmission. To this end, some pilot allocation algorithms have been proposed for this dynamic scenario, but they are designed in such away that an equispaced pilot placement is respected (as much as possible) while minimizing the mean squared error of the channel estimate. Nevertheless, this equispaced placement can lead to the use of an increased number of pilots in order to achieve a good channel estimation. In this work, a new pilot allocation algorithm based on wavelet transform is presented. The proposed algorithm uses the discrete wavelet transform to analyze the previous channel state information, taking the knowledge of the available subcarriers into account to provide a suboptimal solution for the pilot positions. This solution leads to a non-equispaced pilot placement, which improves the channel estimation and consequently, the system performance. Likewise, the introduced algorithm allows a reduction of the number of necessary pilots, which aids in increasing the data rate. Finally, simulation results corroborate the effectiveness of the algorithm in dynamic channel scenarios.

FPGA based radar image enhanced: A robust evolutionary controlled filter approach

In this work, we implemented the robust evolutionary controlled (REC) filter in a FPGA platform. Due unknown a priori statistical information, we replace the Optimal Wiener Filter by its rough approximation referred to as REC filter. The evolution of the filter is controlled by changing/choosing the vector of the controlled parameters gamma. Such a control provides additional degrees of freedom of the filter. We report and discuss some implementation results in the Xilinx Virtex-II Pro XC2VP30 FPGA related to enhancement of the uncertain real-world RS imagery, these are indicative of the significantly increased performance efficiency gained with the developed approach.