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# IEEE Transactions on Computational Imaging

## Issue 2 • June 2017

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## Filter Results

Displaying Results 1 - 25 of 25

Publication Year: 2017, Page(s):C1 - C4
| PDF (127 KB)
• ### IEEE Signal Processing Society

Publication Year: 2017, Page(s): C2
| PDF (56 KB)
• ### Guest Editorial Computational Imaging for Earth Sciences

Publication Year: 2017, Page(s):144 - 145
| PDF (40 KB) | HTML
• ### Fast Hyperspectral Unmixing in Presence of Nonlinearity or Mismodeling Effects

Publication Year: 2017, Page(s):146 - 159
| | PDF (1517 KB) | HTML

This paper presents two novel hyperspectral mixture models and associated unmixing algorithms. The two models assume a linear mixing model corrupted by an additive term whose expression can be adapted to account for multiple scattering nonlinearities (NL), or mismodeling effects (ME). The NL model generalizes bilinear models by taking into account higher order interaction terms. The ME model accou... View full abstract»

• ### Distributed Blind Hyperspectral Unmixing via Joint Sparsity and Low-Rank Constrained Non-Negative Matrix Factorization

Publication Year: 2017, Page(s):160 - 174
| | PDF (1152 KB) | HTML

Hyperspectral unmixing is a crucial processing step in remote sensing image analysis. Its aim is the decomposition of each pixel in a hyperspectral image into a number of materials, the so-called endmembers, and their corresponding abundance fractions. Among the various unmixing approaches that have been suggested in the literature, we are interested here in unsupervised techniques that rely on so... View full abstract»

• ### Robust Fusion of Multiband Images With Different Spatial and Spectral Resolutions for Change Detection

Publication Year: 2017, Page(s):175 - 186
| | PDF (737 KB) | HTML

Archetypal scenarios for change detection generally consider two images acquired through sensors of the same modality. However, in some specific cases such as emergency situations, the only images available may be those acquired through different kinds of sensors. More precisely, this paper addresses the problem of detecting changes between two multiband optical images characterized by different s... View full abstract»

• ### Fast and Accurate Multiplicative Decomposition for Fringe Removal in Interferometric Images

Publication Year: 2017, Page(s):187 - 201
| | PDF (1752 KB)

Airborne hyperspectral images can be efficiently obtained with imaging static Fourier transform spectrometers. However, to be effective on any location, this technology requires to know the relief of the scene. This is not a straightforward process, as the horizontal interference fringes on the images, which are necessary for spectrum construction, prevent efficient stereoscopic processing. We pre... View full abstract»

• ### Colored Coded Aperture Design in Compressive Spectral Imaging via Minimum Coherence

Publication Year: 2017, Page(s):202 - 216
| | PDF (4441 KB) | HTML

Colored coded aperture optimization in compressive spectral imaging is discussed. Based on the analysis of the coherence of the underlying sensing matrix, a general family of codes is derived. These designs lead to reconstructions of multispectral scenes of better quality than the ones obtained using the traditional random black and white coded apertures. The approach used in this work exploits th... View full abstract»

• ### Sensing Matrix Design via Mutual Coherence Minimization for Electromagnetic Compressive Imaging Applications

Publication Year: 2017, Page(s):217 - 229
| | PDF (1752 KB) | HTML

Compressive sensing (CS) theory states that sparse signals can be recovered from a small number of linear measurements y = Ax using l1norm minimization techniques, provided that the sensing matrix satisfies a restricted isometry property (RIP). Unfortunately, the RIP is difficult to verify in electromagnetic imaging applications, where the sensing matrix is computed deterministically. A... View full abstract»

• ### Large-Scale Feature Selection With Gaussian Mixture Models for the Classification of High Dimensional Remote Sensing Images

Publication Year: 2017, Page(s):230 - 242
| | PDF (674 KB) | HTML Media

A large-scale feature selection wrapper is discussed for the classification of high dimensional remote sensing. An efficient implementation is proposed based on intrinsic properties of Gaussian mixtures models and block matrix. The criterion function is split into two parts:one that is updated to test each feature and one that needs to be updated only once per feature selection. This split saved a... View full abstract»

• ### Unsupervised Data Driven Feature Extraction by Means of Mutual Information Maximization

Publication Year: 2017, Page(s):243 - 253
| | PDF (1235 KB) | HTML

In Earth observations technical literature, several methods have been proposed and implemented to efficiently extract a proper set of features for classification and segmentation purposes. However, these architectures show drawbacks when the considered datasets are characterized by complex interactions among the samples, especially when they rely on strong assumptions on noise and label domains. I... View full abstract»

• ### Online Target Recognition for Time-Sensitive Space Information Networks

Publication Year: 2017, Page(s):254 - 263
| | PDF (1010 KB) | HTML

The key difficulties of online target recognition task for space information networks lie in the contradiction between time-sensitive response requirement and resource constraints(e.g., computation resource, communication resource, and training samples). To deal with the above problems, an effective online target recognizing approach is proposed, which seamlessly integrates fast online information... View full abstract»

• ### Beating Level-Set Methods for 5-D Seismic Data Interpolation: A Primal-Dual Alternating Approach

Publication Year: 2017, Page(s):264 - 274
| | PDF (1663 KB) | HTML

Acquisition cost is a crucial bottleneck for seismic workflows, and low-rank formulations for data interpolation allow practitioners to “fill in” data volumes from critically subsampled data acquired in the field. Tremendous size of seismic data volumes required for seismic processing remains a major challenge for these techniques. Residual-constrained formulations require less param... View full abstract»

• ### Low-Rank Decomposition Based on Disjoint Component Analysis With Applications in Seismic Imaging

Publication Year: 2017, Page(s):275 - 281
| | PDF (826 KB) | HTML

Low-rank decomposition plays a fundamental role in signal processing and computational imaging, due to the possibility of decomposing a signal into semantic components. The classical singular value decomposition (SVD) separates globally correlated components from uncorrelated ones. Modified versions of SVD that have been recently proposed allow the separation between horizontal and vertical compon... View full abstract»

• ### Convex Recovery From Interferometric Measurements

Publication Year: 2017, Page(s):282 - 295
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This paper discusses some questions that arise when a linear inverse problem involving $Ax = b$ is reformulated in the interferometric framework, where quadratic combinations of $b$ are considered as data in place of View full abstract»

• ### Non-Linear Inverse Scattering via Sparsity Regularized Contrast Source Inversion

Publication Year: 2017, Page(s):296 - 304
| | PDF (588 KB) | HTML

Two compressive sensing inspired approaches for the solution of non-linear inverse scattering problems are introduced and discussed. Differently from the sparsity promoting approaches proposed in most of the papers published in the literature, the two methods here tackle the problem in its full non-linearity, by adopting a contrast source inversion scheme. In the first approach, the 11-norm of the... View full abstract»

• ### Salt Reconstruction in Full-Waveform Inversion With a Parametric Level-Set Method

Publication Year: 2017, Page(s):305 - 315
| | PDF (1067 KB) | HTML

Seismic full-waveform inversion tries to estimate subsurface medium parameters from seismic data. Areas with subsurface salt bodies are of particular interest because they often have hydrocarbon reservoirs on their sides or underneath. Accurate reconstruction of their geometry is a challenge for current techniques. This paper presents a parametric level-set method for the reconstruction of salt-bo... View full abstract»

• ### Fast GPU-Based Seismogram Simulation From Microseismic Events in Marine Environments Using Heterogeneous Velocity Models

Publication Year: 2017, Page(s):316 - 329
| | PDF (2503 KB) | HTML Media

A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations for the three-dimensional (3-D) elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it fas... View full abstract»

• ### On Acoustic Signal Compression for Ultrasonic Borehole Imaging

Publication Year: 2017, Page(s):330 - 343
| | PDF (1801 KB) | HTML

This paper presents a novel approach for computationally efficient and robust compression for Ultrasonic Borehole Imaging. Although current methods achieve good compression versus accuracy tradeoffs, they inevitably employ iterative schemes, which for resource constrained downhole applications is computationally prohibitive. To alleviate this issue, we propose to model the waveforms as sum of expo... View full abstract»

• ### The Effect of Hardware-Computed Travel Time on Localization Accuracy in the Inversion of Experimental (Acoustic) Waveform Data

Publication Year: 2017, Page(s):344 - 354
| | PDF (1158 KB) | HTML Media

This study aims to advance hardware-level computations for travel-time tomography applications in which the wavelength is close to the diameter of the information that has to be recovered. Such can be the case, for example, in the imaging applications of 1) biomedical physics; 2) astrogeophysics; and 3) civil engineering. Our aim is to shed light on the effect of that preprocessing the digital wav... View full abstract»

• ### Sparse Clustered Bayesian-Inspired $T_{1}-T_{2}$ Inversion From Borehole NMR Measurements

Publication Year: 2017, Page(s):355 - 368
| | PDF (1365 KB) | HTML

This paper is interested in joint $T_1-T_2$ inversion from borehole nuclear magnetic resonance (NMR) measurements when a limited number of wait times (WTs) are used. Unlike a straightforward representation of the multi-WT NMR measurements over an overcomplete kernel matrix and using a sparsity-aware inversion m... View full abstract»

• ### High-Fidelity Real-Time Imaging With Electromagnetic Logging-While-Drilling Measurements

Publication Year: 2017, Page(s):369 - 378
| | PDF (1418 KB) | HTML

A pixel-based inversion approach is introduced for interpretation of deep directional resistivity logging-while-drilling electromagnetic measurements. It can be used for real-time reservoir mapping while drilling to accurately place the well with respect to reservoir boundaries and fluid contacts as well as for reservoir characterization in high angle and horizontal wells. The methodology is based... View full abstract»

• ### IEEE Transactions on Computational Imaging EDICS

Publication Year: 2017, Page(s): 379
| PDF (39 KB)
• ### Information for Authors

Publication Year: 2017, Page(s):380 - 381
| PDF (231 KB)
• ### Transactions on Computational Imaging

Publication Year: 2017, Page(s): C3
| PDF (250 KB)

## Aims & Scope

The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Prof. W. Clem Karl
Boston University