# IEEE Transactions on Computational Imaging

## Issue 1 • March 2018

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## Filter Results

Displaying Results 1 - 19 of 19

Publication Year: 2018, Page(s):C1 - C4
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• ### IEEE Signal Processing Society

Publication Year: 2018, Page(s): C2
| |PDF (55 KB)
• ### A Framework for Dynamic Image Sampling Based on Supervised Learning

Publication Year: 2018, Page(s):1 - 16
| |PDF (2630 KB) | HTML

Sparse sampling schemes can broadly be classified into two main categories: static sampling where the sampling pattern is predetermined, and dynamic sampling where each new measurement location is selected based on information obtained from previous measurements. Dynamic sampling methods are particularly appropriate for pointwise imaging methods, in which pixels are measured sequentially in arbitr... View full abstract»

• ### A Convex Reconstruction Model for X-Ray Tomographic Imaging With Uncertain Flat-Fields

Publication Year: 2018, Page(s):17 - 31
| |PDF (6949 KB) | HTML

Classical methods for X-ray computed tomography are based on the assumption that the X-ray source intensity is known, but in practice, the intensity is measured and hence uncertain. Under normal operating conditions, when the exposure time is sufficiently high, this kind of uncertainty typically has a negligible effect on the reconstruction quality. However, in time- or dose-limited applications s... View full abstract»

• ### A Hierarchical Bayesian Model Accounting for Endmember Variability and Abrupt Spectral Changes to Unmix Multitemporal Hyperspectral Images

Publication Year: 2018, Page(s):32 - 45
| |PDF (1494 KB) | HTML Media

Hyperspectral unmixing is a blind source separation problem that consists in estimating the reference spectral signatures contained in a hyperspectral image, as well as their relative contribution to each pixel according to a given mixture model. In practice, the process is further complexified by the inherent spectral variability of the observed scene and the possible presence of outliers. More s... View full abstract»

• ### Blind Image Watermark Detection Algorithm Based on Discrete Shearlet Transform Using Statistical Decision Theory

Publication Year: 2018, Page(s):46 - 59
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Blind watermarking targets the challenging recovery of the watermark when the host is not available during the detection stage. This paper proposes Discrete Shearlet Transform (DST) as a new embedding domain for blind image watermarking. Our novel DST blind watermark detection system uses a nonadditive scheme based on the statistical decision theory. It first computes the Probability Density Funct... View full abstract»

• ### Multi-Exposure Image Fusion by Optimizing A Structural Similarity Index

Publication Year: 2018, Page(s):60 - 72
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We propose a multi-exposure image fusion (MEF) algorithm by optimizing a novel objective quality measure, namely the color MEF structural similarity (MEF-SSIM$_c$) index. The design philosophy we introduce here is substantially different from existing ones. Instead of pre-defining a systematic computational structure for MEF (<... View full abstract»

• ### SEAGLE: Sparsity-Driven Image Reconstruction Under Multiple Scattering

Publication Year: 2018, Page(s):73 - 86
Cited by:  Papers (1)
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Multiple scattering of an electromagnetic wave as it passes through an object is a fundamental problem that limits the performance of current imaging systems. In this paper, we describe a new technique—called Series Expansion with Accelerated Gradient Descent on the Lippmann–Schwinger Equation—for robust imaging under multiple scattering based on a combination of an iterative ... View full abstract»

• ### On the Superresolution Capacity of Imagers Using Unknown Speckle Illuminations

Publication Year: 2018, Page(s):87 - 98
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Speckle-based imaging consists of forming a super-resolved reconstruction of an unknown sample from low-resolution images obtained under random inhomogeneous illuminations (speckles). In a blind context, where the illuminations are unknown, we study the intrinsic capacity of speckle-based imagers to recover spatial frequencies outside the frequency support of the data, with minima... View full abstract»

• ### Optimal Threshold Design for Quanta Image Sensor

Publication Year: 2018, Page(s):99 - 111
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Quanta image sensor is a binary imaging device envisioned to be the next generation image sensor after CCD and CMOS. Equipped with a massive number of single photon detectors, the sensor has a threshold $q$ above which the number of arriving photons will trigger a binary response “1”, or “0” otherwi... View full abstract»

• ### Image Reconstruction for Limited-Angle Electron Beam X-Ray Computed Tomography With Energy-Integrating Detectors for Multiphase Flows

Publication Year: 2018, Page(s):112 - 124
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We propose a new iterative X-ray computed tomography (CT) reconstruction algorithm for electron beam X-ray tomography of multiphase flows in metal pipes. This application uses limited-angle projections due to the fixed configuration, and semiconductor-type energy-integrating detectors. For the data-fitting objective function, the proposed method incorporates a nonlinear Gaussian model with object-... View full abstract»

• ### Doppler-DPCA and Doppler-ATI: Novel SAR Modalities for Imaging of Moving Targets Using Ultra-Narrowband Waveforms

Publication Year: 2018, Page(s):125 - 136
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This paper introduces two novel imaging modalities: Doppler displaced phase center antenna (Doppler-DPCA) and Doppler along track interferometry (Doppler-ATI). The DPCA and ATI techniques have the distinct advantage of removing the response from stationary targets (clutter). We develop DPCA and ATI techniques in Doppler synthetic aperture radar (Doppler-SAR) paradigm to image moving targets embedd... View full abstract»

• ### Incorporating a Noise Reduction Technique Into X-Ray Tensor Tomography

Publication Year: 2018, Page(s):137 - 146
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X-ray tensor tomography (XTT) is a novel imaging modality for the three-dimensional reconstruction of X-ray scattering tensors from dark-field images obtained in a grating interferometry setup. The two-dimensional dark-field images measured in XTT are degraded by noise effects, such as detector readout noise and insufficient photon statistics, and consequently, the three-dimensional volumes recons... View full abstract»

• ### Sparsity Promoting Adaptive Regularization for Compressed Sensing Parallel MRI

Publication Year: 2018, Page(s):147 - 159
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Low sampling density and reduced signal-to-noise ratio resulting from accelerated magnetic resonance data acquisition calls for sparsity promoting regularization for improved reconstruction. The simplest optimization strategy relies on thresholded Landweber algorithm that results in reconstructions with slow rate of convergence. A varying threshold can accelerate the rate of convergence, but does ... View full abstract»

• ### Single- and Double-Sided Marchenko Imaging Conditions in Acoustic Media

Publication Year: 2018, Page(s):160 - 171
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In acoustic reflector imaging, we deploy sources and receivers outside a volume to collect a multisource, multioffset reflection response in order to retrieve the internal reflectivity of that volume. It has been shown that Green's functions inside the volume can be retrieved by single-sided wavefield focusing of the acquired reflection data, using so-called focusing functions, which can be... View full abstract»

• ### Real-Time High-Fidelity Compression for Extremely High Frame Rate Video Cameras

Publication Year: 2018, Page(s):172 - 180
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The single most debilitating bottleneck for sustained capturing of ultrahigh speed high-resolution video is the limited bandwidth of the on-camera mass storage device. We propose a novel downsampling-based real-time compression algorithms together with a suited camera architecture to overcome the bandwidth problem. The encoder generates and embeds into the compression code stream some useful side ... View full abstract»

• ### IEEE Transactions on Computational Imaging EDICS

Publication Year: 2018, Page(s): 181
| |PDF (39 KB)
• ### Information for authors

Publication Year: 2018, Page(s):182 - 183
| |PDF (261 KB)
• ### Transactions on Computational Imaging

Publication Year: 2018, Page(s): C3
| |PDF (51 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
Dr. Brendt Wohlberg
Los Alamos National Laboratory