ML p(r)ior | Spectrally Grouped Total Variation Reconstruction for Scatter Imaging Using ADMM

Spectrally Grouped Total Variation Reconstruction for Scatter Imaging Using ADMM

2016-01-29
We consider X-ray coherent scatter imaging, where the goal is to reconstruct momentum transfer profiles (spectral distributions) at each spatial location from multiplexed measurements of scatter. Each material is characterized by a unique momentum transfer profile (MTP) which can be used to discriminate between different materials. We propose an iterative image reconstruction algorithm based on a Poisson noise model that can account for photon-limited measurements as well as various second order statistics of the data. To improve image quality, previous approaches use edge-preserving regularizers to promote piecewise constancy of the image in the spatial domain while treating each spectral bin separately. Instead, we propose spectrally grouped regularization that promotes piecewise constant images along the spatial directions but also ensures that the MTPs of neighboring spatial bins are similar, if they contain the same material. We demonstrate that this group regularization results in improvement of both spectral and spatial image quality. We pursue an optimization transfer approach where convex decompositions are used to lift the problem such that all hyper-voxels can be updated in parallel and in closed-form. The group penalty introduces a challenge since it is not directly amendable to these decompositions. We use the alternating directions method of multipliers (ADMM) to replace the original problem with an equivalent sequence of sub-problems that are amendable to convex decompositions, leading to a highly parallel algorithm. We demonstrate the performance on real data.
PDF

Highlights - Most important sentences from the article

Login to like/save this paper, take notes and configure your recommendations

Related Articles

2014-08-01

This paper deals with the problem of reconstructing a depth map from a sequence of differently focus… show more
PDF

Highlights - Most important sentences from the article

2017-12-13
1712.04575 | cs.CV

We consider the problem of fusing an arbitrary number of multiband, i.e., panchromatic, multispectra… show more
PDF

Highlights - Most important sentences from the article

2015-05-08

We review some recent learning approaches in variational imaging, based on bilevel optimisation, and… show more
PDF

Highlights - Most important sentences from the article

2017-11-02

A major challenge in X-ray computed tomography (CT) is reducing radiation dose while maintaining hig… show more
PDF

Highlights - Most important sentences from the article

2019-04-04

The field of image reconstruction has undergone four waves of methods. The first wave was analytical… show more
PDF

Highlights - Most important sentences from the article

2018-12-11

Non-local low-rank tensor approximation has been developed as a state-of-the-art method for hyperspe… show more
PDF

Highlights - Most important sentences from the article

2019-03-21

The aim of this paper is to discuss some advanced aspects of image reconstruction in single-pixel ca… show more
PDF

Highlights - Most important sentences from the article

2018-10-12

Total variation (TV) regularization has proven effective for a range of computer vision tasks throug… show more
PDF

Highlights - Most important sentences from the article

2017-12-05

Sparse hyperspectral unmixing from large spectral libraries has been considered to circumvent limita… show more
PDF

Highlights - Most important sentences from the article

2017-06-03
1706.01000 | cs.CV

We present an end-to-end image compression system based on compressive sensing. The presented system… show more
PDF

Highlights - Most important sentences from the article

2018-10-30

In the past decade, sparsity-driven regularization has led to significant improvements in image reco… show more
PDF

Highlights - Most important sentences from the article

2018-04-13
1804.05042 | cs.CV

In many computer vision applications, obtaining images of high resolution in both the spatial and sp… show more
PDF

Highlights - Most important sentences from the article

2017-12-13

Spectral computed tomography (CT) has a great superiority in lesion detection, tissue characterizati… show more
PDF

Highlights - Most important sentences from the article

2018-02-27
1802.09879 | cs.NA

Total Variation (TV) is an effective and popular prior model in the field of regularization-based im… show more
PDF

Highlights - Most important sentences from the article

2018-09-27

An optical imager that exploits off-center image rotation to encode both the lateral and depth coord… show more
PDF

Highlights - Most important sentences from the article

2019-02-21
1902.08224 | cs.CV

Fusing a low-resolution hyperspectral image (HSI) and a high-resolution multispectral image (MSI) of… show more