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IEEE Transactions on Image Processing

Issue 1 • Date Jan. 2008

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Displaying Results 1 - 15 of 15
  • Table of contents

    Publication Year: 2008, Page(s):C1 - C4
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  • IEEE Transactions on Image Processing publication information

    Publication Year: 2008, Page(s): C2
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  • Efficient 2-D Grayscale Morphological Transformations With Arbitrary Flat Structuring Elements

    Publication Year: 2008, Page(s):1 - 8
    Cited by:  Papers (30)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (470 KB) | HTML iconHTML

    An efficient algorithm is presented for the computation of grayscale morphological operations with arbitrary 2D flat structuring elements (S.E.). The required computing time is independent of the image content and of the number of gray levels used. It always outperforms the only existing comparable method, which was proposed in the work by Van Droogenbroeck and Talbot, by a factor between 3.5 and ... View full abstract»

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  • An Efficient Phase and Object Estimation Scheme for Phase-Diversity Time Series Data

    Publication Year: 2008, Page(s):9 - 15
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1141 KB) | HTML iconHTML

    We present a two-stage method for obtaining both phase and object estimates from phase-diversity time series data. In the first stage, the phases are estimated for each time frame using the limited memory BFGS method. In the second stage, an algorithm that incorporates a nonnegativity constraint as well as prior knowledge of data noise statistics is used to obtain an estimate of the object being o... View full abstract»

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  • Unsupervised Bayesian Convex Deconvolution Based on a Field With an Explicit Partition Function

    Publication Year: 2008, Page(s):16 - 26
    Cited by:  Papers (10)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (795 KB) | HTML iconHTML

    This paper proposes a non-Gaussian Markov field with a special feature: an explicit partition function. To the best of our knowledge, this is an original contribution. Moreover, the explicit expression of the partition function enables the development of an unsupervised edge-preserving convex deconvolution method. The method is fully Bayesian, and produces an estimate in the sense of the posterior... View full abstract»

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  • Image Restoration Using Space-Variant Gaussian Scale Mixtures in Overcomplete Pyramids

    Publication Year: 2008, Page(s):27 - 41
    Cited by:  Papers (58)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1373 KB) | HTML iconHTML

    In recent years, Bayes least squares-Gaussian scale mixtures (BLS-GSM) has emerged as one of the most powerful methods for image restoration. Its strength relies on providing a simple and, yet, very effective local statistical description of oriented pyramid coefficient neighborhoods via a GSM vector. This can be viewed as a fine adaptation of the model to the signal variance at each scale, orient... View full abstract»

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  • Higher Order SVD Analysis for Dynamic Texture Synthesis

    Publication Year: 2008, Page(s):42 - 52
    Cited by:  Papers (42)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3137 KB) | HTML iconHTML

    Videos representing flames, water, smoke, etc., are often defined as dynamic textures: "textures" because they are characterized by the redundant repetition of a pattern and "dynamic" because this repetition is also in time and not only in space. Dynamic textures have been modeled as linear dynamic systems by unfolding the video frames into column vectors and describing their trajectory as ... View full abstract»

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  • Sparse Representation for Color Image Restoration

    Publication Year: 2008, Page(s):53 - 69
    Cited by:  Papers (563)  |  Patents (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2194 KB) | HTML iconHTML

    Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. In particular, the design of well adapted dictionaries for images has been a major challenge. The K-SVD has been recently proposed for this t... View full abstract»

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  • A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields

    Publication Year: 2008, Page(s):70 - 83
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2021 KB) | HTML iconHTML

    This paper presents recursive cavity modeling - a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to subdivide the random field into smaller subfields, constructing cavity models which approximate these subfields. Each cavity model is a concise, yet faithful, model for the surface of one subfield sufficient for near-optim... View full abstract»

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  • Bistatic Synthetic Aperture Radar Imaging for Arbitrary Flight Trajectories

    Publication Year: 2008, Page(s):84 - 93
    Cited by:  Papers (37)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1420 KB) | HTML iconHTML

    In this paper, we present an analytic, filtered backprojection (FBP) type inversion method for bistatic synthetic aperture radar (BISAR). We consider a BISAR system where a scene of interest is illuminated by electromagnetic waves that are transmitted, at known times, from positions along an arbitrary, but known, flight trajectory and the scattered waves are measured from positions along a differe... View full abstract»

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  • Image Reconstruction and Multidimensional Field Estimation From Randomly Scattered Sensors

    Publication Year: 2008, Page(s):94 - 99
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1206 KB) | HTML iconHTML

    Many important problems in statistical signal processing can be formulated as function estimation from randomly scattered sensors in a multidimensional space, e.g., image reconstruction from photon-limited images and field estimation from scattered sensors. We present a novel approach to the study of signal reconstruction from random samples in a multidimensional space. In particular, we study a c... View full abstract»

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  • IEEE Transactions on Image Processing EDICS

    Publication Year: 2008, Page(s): 100
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  • IEEE Transactions on Image Processing Information for authors

    Publication Year: 2008, Page(s):101 - 102
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  • IEEE copyright form

    Publication Year: 2008, Page(s):103 - 104
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  • IEEE Signal Processing Society Information

    Publication Year: 2008, Page(s): C3
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Aims & Scope

IEEE Transactions on Image Processing focuses on signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing.

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Meet Our Editors

Editor-in-Chief
Scott Acton
University of Virginia
Charlottesville, VA, USA
E-mail: acton@virginia.edu 
Phone: +1 434-982-2003