Browsing by Author "Flandrin, Patrick"
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Item Edge Localized Image Sharpening via Reassignment with Application to Computed Tomography(2000-07-01) Dorney, Timothy D.; Bhashyam, Srikrishna; Doran, Andrew; Choi, Hyeokho; Flandrin, Patrick; Baraniuk, Richard G.; Center for Multimedia Communications (http://cmc.rice.edu/); Digital Signal Processing (http://dsp.rice.edu/)Traditional filtering methods operate on the entire signal or image. In some applications, however, errors are concentrated in specific regions or features. A prime example is images generated using computed tomography. Practical implementations limit the amount of high frequency content in the reconstructed image, and consequently, edges are blurred. We introduce a new post-reconstruction edge enhancement algorithm, based on the reassignment principle and wavelets, that localizes its sharpening exclusively to edge features. Our method enhances edges without disturbing the low frequency textural details.Item Measuring Time-Frequency Information and Complexity using the Renyi Entropies(1995-09-01) Baraniuk, Richard G.; Flandrin, Patrick; Michel, Olivier; Digital Signal Processing (http://dsp.rice.edu/)In search of a nonparametric indicator of deterministic signal complexity, we link the Renyi entropies to time-frequency representations. The resulting measures show promise in several situations where concepts like the time-bandwidth product fail.Item Measuring Time-Frequency Information Content using the Renyi Entropies(2001-05-01) Baraniuk, Richard G.; Flandrin, Patrick; Janssen, A. J. E. M.; Michel, Olivier; Digital Signal Processing (http://dsp.rice.edu/)The generalized entropies of Renyi inspire new measures for estimating signal information and complexity in the time-frequency plane. When applied to a time-frequency representation (TFR) from Cohen's class or the affine class, the Renyi entropies conform closely to the notion of complexity that we use when visually inspecting time-frequency images. These measures possess several additional interesting and useful properties, such as accounting and cross-component and transformation invariances, that make them natural for time-frequency analysis. This paper comprises a detailed study of the properties and several potential applications of the Renyi entropies, with emphasis on the mathematical foundations for quadratic TFRs. In particular, for the Wigner distribution, we establish that there exist signals for which the measures are not well defined.Item Multiscale Nature of Network Traffic(2002-05-01) Abry, Patrice; Baraniuk, Richard G.; Flandrin, Patrick; Riedi, Rudolf H.; Veitch, Darryl; Center for Multimedia Communications (http://cmc.rice.edu/); Digital Signal Processing (http://dsp.rice.edu/)The complexity and richness of telecommunications traffic is such that one may despair to find any regularity or explanatory principles. Nonetheless, the discovery of scaling behavior in tele-traffic has provided hope that parsimonious models can be found. The statistics of scaling behavior present many challenges, especially in non-stationary environments. In this paper, we overview the state of the art in this area, focusing on the capabilities of the wavelet transform as a key tool for unravelling the mysteries of traffic statistics and dynamics.Item Time-Frequency Complexity and Information(1994-04-01) Flandrin, Patrick; Baraniuk, Richard G.; Michel, Olivier; Digital Signal Processing (http://dsp.rice.edu/)Many functions have been proposed for estimating signal information content and complexity on the time-frequency plane, including moment-based measures such as the time-bandwidth product and the Shannon and Renyi entropies. When applied to a time-frequency representation from Cohen's class, the Renyi entropy conforms closely to the visually based notion of complexity that we use when inspecting time-frequency images. A detailed discussion reveals many of the desirable properties of the Renyi information measure for both deterministic and random signals.