Now showing items 21-40 of 508

  • JPEG Compression History Estimation for Color Images 

    Neelamani, Ramesh; de Queiroz, Ricardo; Fan, Zhigang; Baraniuk, Richard G. (2006-06-01)
    We routinely encounter digital color images that were previously compressed using the Joint Photographic Experts Group (JPEG) standard. En route to the image's current representation, the previous JPEG compression's various ...
  • Sparse Signal Detection from Incoherent Projections 

    Davenport, Mark A.; Wakin, Michael B.; Duarte, Marco F.; Baraniuk, Richard G. (2006-05-01)
    The recently introduced theory of Compressed Sensing (CS) enables the reconstruction or approximation of sparse or compressible signals from a small set of incoherent projections; often the number of projections can be ...
  • Controlling False Alarms with Support Vector Machines 

    Davenport, Mark A.; Baraniuk, Richard G.; Scott, Clayton D. (2006-05-01)
    We study the problem of designing support vector classifiers with respect to a Neyman-Pearson criterion. Specifically, given a user-specified level alpha, 0 < alpha < 1, how can we ensure a false alarm rate no greater than ...
  • Random Projections of Signal Manifolds 

    Wakin, Michael; Baraniuk, Richard G. (2006-05-01)
    Random projections have recently found a surprising niche in signal processing. The key revelation is that the relevant structure in a signal can be preserved when that signal is projected onto a small number of random ...
  • Wavelet-Domain Approximation and Compression of Piecewise Smooth Images 

    Wakin, Michael; Romberg, Justin; Choi, Hyeokho; Baraniuk, Richard G. (2006-05-01)
    The wavelet transform provides a sparse representation for smooth images, enabling efficient approximation and compression using techniques such as zerotrees. Unfortunately, this sparsity does not extend to piecewise smooth ...
  • Random Filters for Compressive Sampling and Reconstruction 

    Baraniuk, Richard G.; Wakin, Michael; Duarte, Marco F.; Tropp, Joel A.; Baron, Dror (2006-05-01)
    We propose and study a new technique for efficiently acquiring and reconstructing signals based on convolution with a fixed FIR filter having random taps. The method is designed for sparse and compressible signals, i.e., ...
  • Universal Distributed Sensing via Random Projections 

    Wakin, Michael; Duarte, Marco F.; Baraniuk, Richard G.; Baron, Dror (2006-04-01)
    This paper develops a new framework for distributed coding and compression in sensor networks based on distributed compressed sensing (DCS). DCS exploits both intra-signal and inter-signal correlations through the concept ...
  • Faster Sequential Universal Coding via Block Partitioning 

    Baron, Dror; Baraniuk, Richard G. (2006-04-01)
    Rissanen provided a sequential universal coding algorithm based on a block partitioning scheme, where the source model is estimated at the beginning of each block. This approach asymptotically approaches the entropy at the ...
  • An Architecture for Distributed Wavelet Analysis and Processing in Sensor Networks 

    Wagner, Raymond; Baraniuk, Richard G.; Du, Shu; Johnson, David B.; Cohen, Albert (2006-04-01)
    Distributed wavelet processing within sensor networks holds promise for reducing communication energy and wireless bandwidth usage at sensor nodes. Local collaboration among nodes de-correlates measurements, yielding a ...
  • Representation and Compression of Multi-Dimensional Piecewise Functions Using Surflets 

    Chandrasekaran, Venkat; Wakin, Michael; Baron, Dror; Baraniuk, Richard G. (2006-03-01)
    We study the representation, approximation, and compression of functions in M dimensions that consist of constant or smooth regions separated by smooth (M-1)-dimensional discontinuities. Examples include images containing ...
  • Broadcast Detection Structures with Applications to Sensor Networks 

    Johnson, Don; Lexa, Michael (2006-03-01)
    Data broadcasting is potentially an effective and efficient way to share information in wireless sensor networks. Broadcasts offer energy savings over multiple, directed transmissions, and they provide a vehicle to exploit ...
  • Optimal Sampling Strategies for Multiscale Stochastic Processes 

    Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G. (2006-01-15)
    In this paper, we determine which non-random sampling of fixed size gives the best linear predictor of the sum of a finite spatial population. We employ different multiscale superpopulation models and use the minimum ...
  • The 2nu-SVM: A Cost-Sensitive Extension of the nu-SVM 

    Davenport, Mark A. (2005-12-01)
    Standard classification algorithms aim to minimize the probability of making an incorrect classification. In many important applications, however, some kinds of errors are more important than others. In this report we ...
  • The Dual-Tree Complex Wavelet Transform 

    Selesnick, Ivan W.; Baraniuk, Richard G.; Kingsbury, Nicholas G. (2005-11-01)
    The paper discusses the theory behind the dual-tree transform, shows how complex wavelets with good properties can be designed, and illustrates a range of applications in signal and image processing. The authors use the ...
  • Modeling wireless sensor and actuator networks using frame theory 

    Rozell, Chris; Johnson, Don (2005-11-01)
    Wireless sensor networks are often studied with the goal of removing information from the network as efficiently as possible. However, when the application also includes an actuator network, it is advantageous to determine ...
  • Analysis of the DCS one-stage Greedy Algorothm for Common Sparse Supports 

    Baron, Dror; Duarte, Marco F.; Wakin, Michael; Sarvotham, Shriram; Baraniuk, Richard G. (2005-11-01)
    Analysis of the DCS one-stage Greedy Algorothm for Common Sparse Supports
  • Distributed Compressed Sensing of Jointly Sparse Signals 

    Sarvotham, Shriram; Baron, Dror; Wakin, Michael; Duarte, Marco F.; Baraniuk, Richard G. (2005-11-01)
    Compressed sensing is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for reconstruction. In this paper we expand our theory for ...
  • Variable-Rate Universal Slepian-Wolf Coding with Feedback 

    Sarvotham, Shriram; Baron, Dror; Baraniuk, Richard G. (2005-11-01)
    Traditional Slepian-Wolf coding assumes known statistics and relies on asymptotically long sequences. However, in practice the statistics are unknown, and the input sequences are of finite length. In this finite regime, ...
  • Development of Japanese-language DSP Education Content in the Connexions Project 

    Frantz, Patrick; Yamada, Yoji (2005-10-01)
    Due to factors such as a small and fragmented market and rapid hardware development, the conventional textbook is inadequate for DSP lab education. Freely available open-content materials that enable and promote local ...
  • Coherent Image Processing using Quaternion Wavelets 

    Chan, Wai Lam; Choi, Hyeokho; Baraniuk, Richard G. (2005-08-01)
    We develop a quaternion wavelet transform (QWT) as a new multiscale analysis tool for geometric image features. The QWT is a near shift-invariant, tight frame representation whose coefficients sport a magnitude and three ...