This paper addresses the problem of texture images recovery from compressively sampled measurements. Texture images hardly present a sparse, or even compressible, representation in transformed domains (e.g. wavelet) and are therefore difficult to deal with in the Compressive Sampling (CS) framework. Herein, we resort to the recently defined Graph-based transform (GBT), formerly introduced for depth map coding, as a sparsifying transform for classes of textures sharing the similar spatial patterns. Since GBT proves to be a good candidate for compact representation of some classes of texture, we leverage it for CS texture recovery. To this aim, we resort to a modified version of a state-of-the-art recovery algorithm to reconstruct the texture representation in the GBT domain. Numerical simulation results show that this approach outperforms state-of-the-art CS recovery algorithms on texture images.

In compressive sensing, the Restricted Isometry Property is an analytical condition on the measurement matrix that assures reconstruction of a signal which is sparse either in the spatial or in a transformed domain given an undersampled measurements' set. In this paper, we demonstrate the RIP for a sparse, structured measurements matrix, referred to as Radon-like CS matrix. The sparse Radon-Like CS matrix favorably applies to real sensing problems, since it significantly reduces the energy/bandwidth cost of actually collecting each and every sensed values contributing to the CS measurements. Simulation results confirm the feasibility of field reconstruction from undersampled CS measurements set obtained using the Radon-Like CS matrix.

We introduce a novel, both gain and signal-to-noise ratio independent, constellation unaware, blind frequency offset estimation procedure for QAM signals. Asymptotic performance analysis and numerical simulations show that the herein presented method outperforms a selected state of the art blind constellation unaware estimator, especially for cross constellations.

In this letter, we address the problem of estimating a parameter acting as a scale factor on the observations probability density function (pdf), i.e. a scale parameter. Histogram based Maximum Likelihood (ML) estimation of a scale parameter requires the evaluation of a discrete scale correlation. We show how ML estimation can be implemented by means of a computationally efficient Discrete Fourier Transform based procedure, when geometric histogram sampling is adopted. As a case study, we analyze a gain estimator for general QAM constellations. Simulation results and theoretical performance analysis show that the presented ML estimator outperforms selected state of the art estimators, approaching the Cramér-Rao Lower Bound (CRLB) for a wide range of SNR.

In this paper we develop a strategy for visual relevancy evaluation using Rate Distortion analysis in the Circular Harmonic Functions (CHF) Domain. In the CHF domain, the different visual characteristics of the transformed frames - edges, lines, forks, crosses, etc - are emphasized. Resorting to this domain we analyze a new approach to evaluate the distortion due to an event of video data loss accounting for the visual relevance of individual lost data. In a real video streaming session, distortion measurements taking into account the visual impact of error events can be stored along with pre-coded video sequence so as to drive the strategies for ad-hoc error protection. Numerical simulations show that the approach herein proposed to evaluate the visual impact of loss events in the decoded sequences captures the visual distortion much better than commonly adopted mean square error criteria between the decoded and the original sequence.

In this paper we present theoretical performance analysis for a blind frequency offset estimator for cross quadrature amplitude modulated constellations. The estimator is based on applying a tentative frequency offset compensation by means of a nonlinear transformation of the received signal samples and on estimating an accumulation function in different angular windows. For perfect frequency offset compensation, the measurements are suitably clustered and their accumulation, named "constellation phase signature" (CPS), is a peaked function of the window orientation. Hence, the frequency offset estimator is selected by maximization of the peakness of the accumulation function. The performance analysis is shown to match the numerical simulations for medium to high values of SNR.

Fast and bit-saving video bit-rate switching is an important issue in video streaming systems on a time varying channel as the one offered by a wireless mesh network, or the one sensed during a vertical handover. The recent H.264 video coding standard supports the seamless switching among bitstreams coded at different bit-rates by means of suitably coded frames, named switching pictures. This work addresses the modelling of the traffic generated by a H.264 source performing bit-rate switching using SP frames. The H.264 source is modelled by a Markov chain where each state models the generation of an entire group of pictures (GOP), and is characterized by the kind of SP frame encoded in the GOP. Inter- frame correlation, typical of video sources, is suitably taken into account by the interstate dependence. The accuracy of the model is assessed by comparison of the cell loss rate of a fixed size buffer filled with a synthetic source according to the model herein proposed, with a state of the art AR model and with a real H.264 video codec.

In this work1we discuss a game theoretic approach to bitstream switching in video coding. Fast and bit-saving video bitstream switching is an important issue in video communication system on time varying channels. The most recent video coding standard, namely H.264, support the seamless switching among bitstreams coded at different bitrates by means of suitably coded frames, named Switching Pictures. Since the rate-distortion characteristics of switching frames differ from those of I and P frames, their location affect both the bit-rate and the quality of the coded sequence. In this work, we address the optimization of the SP frames location under an assigned bitrate budget. At this aim we restor to a game theoretic approach and we show that the optimal solution is met when the SP frames are assigned to the frame with the smallest innovation. Experimental results show the advantage in terms of both rate and distortion achieved by the optimized Switching frame insertion with respect to basic H264 coding.