A System for Compressive Sensing Signal Reconstruction

An architecture for hardware realization of a system for sparse signal reconstruction is presented. The threshold based reconstruction method is considered, which is further modified in this paper to reduce the system complexity in order to provide easier hardware realization. Instead of using the partial random Fourier transform matrix, the minimization problem is reformulated using only the triangular R matrix from the QR decomposition. The triangular R matrix can be efficiently implemented in hardware without calculating the orthogonal Q matrix. A flexible and scalable realization of matrix R is proposed, such that the size of R changes with the number of available samples and sparsity level.Comment: 6 page

Image watermarking based on the space/spatial-frequency analysis and Hermite functions expansion

International audienceAn image watermarking scheme that combines Hermite functions expansion and space/spatial-frequency analysis is proposed. In the first step, the Hermite functions expansion is employed to select busy regions for watermark embedding. In the second step, the space/spatial-frequency representation and Hermite functions expansion are combined to design the imperceptible watermark, using the host local frequency content. The Hermite expansion has been done by using the fast Hermite projection method. Recursive realization of Hermite functions significantly speeds up the algorithms for regions selection and watermark design. The watermark detection is performed within the space/spatial-frequency domain. The detection performance is increased due to the high information redundancy in that domain in comparison with the space or frequency domains, respectively. The performance of the proposed procedure has been tested experimentally for different watermark strengths, i.e., for different values of the peak signal-to-noise ratio (PSNR). The proposed approach provides high detection performance even for high PSNR values. It offers a good compromise between detection performance (including the robustness to a wide variety of common attacks) and imperceptibility

Watermark Detection in Impulsive Noise Environment Based on the Compressive Sensing Reconstruction

The watermark detection procedure for images corrupted by impulsive noise is proposed. The procedure is based on the compressive sensing (CS) method for the reconstruction of corrupted pixels. It is shown that the proposed procedure can extract watermark with a moderate impulsive noise level. It is well known that most of the images are approximately sparse in the 2D DCT domain. Moreover, we can force sparsity in the watermarking procedure and obtain almost strictly sparse image as a desirable input to the CS based reconstruction algorithms. Compared to the state-of-the-art methods for impulse noise removal, the proposed solution provides much better performance in watermark extraction

Effects of Cauchy integral formula discretization on the precision of IF estimation; unified approach to complex-lag distribution and its counterpart L form

Papier accepté en IEEE Signal Processing en novembre 2008International audienceAn interpretation of time-frequency (TF) distribution concentration based on discretization of Cauchy's integral formula, is provided. In order to increase the accuracy of instantaneous frequency (IF) estimation, two solutions are considered: increasing the number of points for integration and multiple integrations using the same number of points (it corresponds to L form of TF distribution). In practical applications, L form of the fourth order complex-lag distribution has shown excellent results. For this case the analysis of noise influence is provided, as well