# IEEE Transactions on Image Processing

## Filter Results

Displaying Results 1 - 25 of 28

Publication Year: 2010, Page(s):C1 - C4
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• ### IEEE Transactions on Image Processing publication information

Publication Year: 2010, Page(s): C2
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• ### Generalized Assorted Pixel Camera: Postcapture Control of Resolution, Dynamic Range, and Spectrum

Publication Year: 2010, Page(s):2241 - 2253
Cited by:  Papers (66)  |  Patents (3)
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We propose the concept of a generalized assorted pixel (GAP) camera, which enables the user to capture a single image of a scene and, after the fact, control the tradeoff between spatial resolution, dynamic range and spectral detail. The GAP camera uses a complex array (or mosaic) of color filters. A major problem with using such an array is that the captured image is severely under-sampled for at... View full abstract»

• ### Image Segmentation by MAP-ML Estimations

Publication Year: 2010, Page(s):2254 - 2264
Cited by:  Papers (35)
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Image segmentation plays an important role in computer vision and image analysis. In this paper, image segmentation is formulated as a labeling problem under a probability maximization framework. To estimate the label configuration, an iterative optimization scheme is proposed to alternately carry out the maximum a posteriori (MAP) estimation and the maximum likelihood (ML) estimation. The MAP est... View full abstract»

• ### Joint NDT Image Restoration and Segmentation Using Gauss–Markov–Potts Prior Models and Variational Bayesian Computation

Publication Year: 2010, Page(s):2265 - 2277
Cited by:  Papers (27)
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In this paper, we propose a method to simultaneously restore and to segment piecewise homogeneous images degraded by a known point spread function (PSF) and additive noise. For this purpose, we propose a family of nonhomogeneous Gauss-Markov fields with Potts region labels model for images to be used in a Bayesian estimation framework. The joint posterior law of all the unknowns (the unknown image... View full abstract»

• ### A Bayesian Framework for Image Segmentation With Spatially Varying Mixtures

Publication Year: 2010, Page(s):2278 - 2289
Cited by:  Papers (35)
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A new Bayesian model is proposed for image segmentation based upon Gaussian mixture models (GMM) with spatial smoothness constraints. This model exploits the Dirichlet compound multinomial (DCM) probability density to model the mixing proportions (i.e., the probabilities of class labels) and a Gauss-Markov random field (MRF) on the Dirichlet parameters to impose smoothness. The main advantages of ... View full abstract»

• ### Fast Space-Variant Elliptical Filtering Using Box Splines

Publication Year: 2010, Page(s):2290 - 2306
Cited by:  Papers (8)  |  Patents (2)
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The efficient realization of linear space-variant (non-convolution) filters is a challenging computational problem in image processing. In this paper, we demonstrate that it is possible to filter an image with a Gaussian-like elliptic window of varying size, elongation and orientation using a fixed number of computations per pixel. The associated algorithm, which is based upon a family of smooth c... View full abstract»

• ### Switching Bilateral Filter With a Texture/Noise Detector for Universal Noise Removal

Publication Year: 2010, Page(s):2307 - 2320
Cited by:  Papers (55)
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In this paper, we propose a switching bilateral filter (SBF) with a texture and noise detector for universal noise removal. Operation was carried out in two stages: detection followed by filtering. For detection, we propose the sorted quadrant median vector (SQMV) scheme, which includes important features such as edge or texture information. This information is utilized to allocate a reference med... View full abstract»

• ### A Low False Negative Filter for Detecting Rare Bird Species From Short Video Segments Using a Probable Observation Data Set-Based EKF Method

Publication Year: 2010, Page(s):2321 - 2331
Cited by:  Papers (9)
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We report a new filter to assist the search for rare bird species. Since a rare bird only appears in front of a camera with very low occurrence (e.g., less than ten times per year) for very short duration (e.g., less than a fraction of a second), our algorithm must have a very low false negative rate. We verify the bird body axis information with the known bird flying dynamics from the short video... View full abstract»

• ### Robust Processing of Optical Flow of Fluids

Publication Year: 2010, Page(s):2332 - 2344
Cited by:  Papers (12)  |  Patents (2)
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This paper proposes a new approach, coupling physical models and image estimation techniques, for modelling the movement of fluids. The fluid flow is characterized by turbulent movement and dynamically changing patterns which poses challenges to existing optical flow estimation methods. The proposed methodology, which relies on Navier-Stokes equations, is used for processing fluid optical flow by ... View full abstract»

• ### Fast Image Recovery Using Variable Splitting and Constrained Optimization

Publication Year: 2010, Page(s):2345 - 2356
Cited by:  Papers (354)  |  Patents (5)
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We propose a new fast algorithm for solving one of the standard formulations of image restoration and reconstruction which consists of an unconstrained optimization problem where the objective includes an l2 data-fidelity term and a nonsmooth regularizer. This formulation allows both wavelet-based (with orthogonal or frame-based representations) regularization or total-variation ... View full abstract»

• ### Adaptive Langevin Sampler for Separation of $t$-Distribution Modelled Astrophysical Maps

Publication Year: 2010, Page(s):2357 - 2368
Cited by:  Papers (7)
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We propose to model the image differentials of astrophysical source maps by Student's t-distribution and to use them in the Bayesian source separation method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC) sampling scheme to unmix the astrophysical sources and describe the derivation details. In this scheme, we use the Langevin stochastic equation for transitions, which... View full abstract»

• ### Bidirectional Composition on Lie Groups for Gradient-Based Image Alignment

Publication Year: 2010, Page(s):2369 - 2381
Cited by:  Papers (8)
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In this paper, a new formulation based on bidirectional composition on Lie groups (BCL) for parametric gradient-based image alignment is presented. Contrary to the conventional approaches, the BCL method takes advantage of the gradients of both template and current image without combining them a priori. Based on this bidirectional formulation, two methods are proposed and their relationship with s... View full abstract»

• ### Optimal PET Protection for Streaming Scalably Compressed Video Streams With Limited Retransmission Based on Incomplete Feedback

Publication Year: 2010, Page(s):2382 - 2395
Cited by:  Papers (4)
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For streaming scalably compressed video streams over unreliable networks, Limited-Retransmission Priority Encoding Transmission (LR-PET) outperforms PET remarkably since the opportunity to retransmit is fully exploited by hypothesizing the possible future retransmission behavior before the retransmission really occurs. For the retransmission to be efficient in such a scheme, it is critical to get ... View full abstract»

• ### Distributed Consensus on Camera Pose

Publication Year: 2010, Page(s):2396 - 2407
Cited by:  Papers (5)
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Our work addresses pose estimation in a distributed camera framework. We examine how processing cameras can best reach a consensus about the pose of an object when they are each given a model of the object, defined by a set of point coordinates in the object frame of reference. The cameras can only see a subset of the object feature points in the midst of background clutter points, not knowing whi... View full abstract»

• ### A Statistical Pixel Intensity Model for Segmentation of Confocal Laser Scanning Microscopy Images

Publication Year: 2010, Page(s):2408 - 2418
Cited by:  Papers (2)
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Confocal laser scanning microscopy (CLSM) has been widely used in the life sciences for the characterization of cell processes because it allows the recording of the distribution of fluorescence-tagged macromolecules on a section of the living cell. It is in fact the cornerstone of many molecular transport and interaction quantification techniques where the identification of regions of interest th... View full abstract»

• ### A Multiresolution Approach to Iterative Reconstruction Algorithms in X-Ray Computed Tomography

Publication Year: 2010, Page(s):2419 - 2427
Cited by:  Papers (9)
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In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations... View full abstract»

• ### Regularization of Phase Retrieval With Phase-Attenuation Duality Prior for 3-D Holotomography

Publication Year: 2010, Page(s):2428 - 2436
Cited by:  Papers (42)
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We consider the phase retrieval problem in 3-D holotomography for strongly absorbing objects. Holotomography combines phase retrieval from Fresnel diffraction patterns with tomographic reconstruction to reconstruct the 3-D refractive index distribution. The main interest is the increase in sensitivity of up to three orders of magnitude compared to standard, absorption based tomography. Most existi... View full abstract»

• ### Determinant and Exchange Algorithms for Observation Subset Selection

Publication Year: 2010, Page(s):2437 - 2443
Cited by:  Papers (4)
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In many applications involving image reconstruction, signal observation time is limited. This emphasizes the requirement for optimal observation selection algorithms. A selection criterion using the trace of a matrix forms the basis of two existing algorithms, the Sequential Backward Selection and Sequential Forward Selection algorithms. Neither is optimal although both generally perform well. Her... View full abstract»

• ### Prostate Cancer Localization With Multispectral MRI Using Cost-Sensitive Support Vector Machines and Conditional Random Fields

Publication Year: 2010, Page(s):2444 - 2455
Cited by:  Papers (44)
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Prostate cancer is a leading cause of cancer death for men in the United States. Fortunately, the survival rate for early diagnosed patients is relatively high. Therefore, in vivo imaging plays an important role for the detection and treatment of the disease. Accurate prostate cancer localization with noninvasive imaging can be used to guide biopsy, radiotheraphy, and surgery as well as to ... View full abstract»

• ### Automated Polar Ice Thickness Estimation From Radar Imagery

Publication Year: 2010, Page(s):2456 - 2469
Cited by:  Papers (7)
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This paper focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables... View full abstract»

• ### User-Friendly Interactive Image Segmentation Through Unified Combinatorial User Inputs

Publication Year: 2010, Page(s):2470 - 2479
Cited by:  Papers (54)  |  Patents (1)
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One weakness in the existing interactive image segmentation algorithms is the lack of more intelligent ways to understand the intention of user inputs. In this paper, we advocate the use of multiple intuitive user inputs to better reflect a user's intention. In particular, we propose a constrained random walks algorithm that facilitates the use of three types of user inputs: 1) foreground and back... View full abstract»

• ### Efficient Particle Filtering via Sparse Kernel Density Estimation

Publication Year: 2010, Page(s):2480 - 2490
Cited by:  Papers (12)
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Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to appropriately sample from the posterior distribution, maintain multiple hypotheses, and alleviate computational costs while preserving tracking accuracy. To address these issues, a novel utilization of the support vector data ... View full abstract»

• ### Joint Random Field Model for All-Weather Moving Vehicle Detection

Publication Year: 2010, Page(s):2491 - 2501
Cited by:  Papers (12)
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This paper proposes a joint random field (JRF) model for moving vehicle detection in video sequences. The JRF model extends the conditional random field (CRF) by introducing auxiliary latent variables to characterize the structure and evolution of visual scene. Hence, detection labels (e.g., vehicle/roadway) and hidden variables (e.g., pixel intensity under shadow) are jointly estimated to enhance... View full abstract»

• ### Extracting Multiple Features in the CID Color Space for Face Recognition

Publication Year: 2010, Page(s):2502 - 2509
Cited by:  Papers (10)
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This correspondence presents a novel face recognition method that extracts multiple features in the color image discriminant (CID) color space, where three new color component images, D1, D2, and D3, are derived using an iterative algorithm. As different color component images in the CID color space display different characteristics, three diff... View full abstract»

## 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