首页/论文/1306.6281

arXiv 1306.62812013-06-26cs.ITcs.CVmath.ITstat.AP

Compressive Coded Aperture Keyed Exposure Imaging with Optical Flow Reconstruction

The University of Wisconsin-Madison（威斯康星大学麦迪逊分校）；Duke University（杜克大学）；University of California, Merced（加利福尼亚大学默塞德分校）

Zachary T. Harmany, Roummel F. Marcia, Rebecca M. Willett

备注：: 13 pages, 4 figures, Submitted to IEEE Transactions on Image Processing. arXiv admin note: substantial text overlap with arXiv:1111.7247

阅读 PDF ↗

arXiv 页面 ↗HTML 原文 ↗

英文摘要相关论文

英文摘要：

This paper describes a coded aperture and keyed exposure approach to compressive video measurement which admits a small physical platform, high photon efficiency, high temporal resolution, and fast reconstruction algorithms. The proposed projections satisfy the Restricted Isometry Property (RIP), and hence compressed sensing theory provides theoretical guarantees on the video reconstruction quality. Moreover, the projections can be easily implemented using existing optical elements such as spatial light modulators (SLMs). We extend these coded mask designs to novel dual-scale masks (DSMs) which enable the recovery of a coarse-resolution estimate of the scene with negligible computational cost. We develop fast numerical algorithms which utilize both temporal correlations and optical flow in the video sequence as well as the innovative structure of the projections. Our numerical experiments demonstrate the efficacy of the proposed approach on short-wave infrared data.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

阅读原文

阅读 PDF ↗

arXiv 页面 ↗HTML 原文 ↗

本文内容

英文摘要相关论文

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

继续探索

相关论文

Spatio-temporal Compressed Sensing with Coded Apertures and Keyed Exposures

Optical systems which measure independent random projections of a scene according to compressed sensing (CS) theory face a myriad of practical challenges related to the size of the physical platform, photon efficiency, the need for high temporal resolution, and fast reconstruction in video settings. This paper describes a coded aperture and keyed exposure approach to compressive measurement in optical systems. The proposed projections satisfy the Restricted Isometry Property for sufficiently sparse scenes, and hence are compatible with theoretical guarantees on the video reconstruction quality…

2012-01-06math.OCmath.STstat.AP

Coded aperture compressive temporal imaging

Duke University（杜克大学）；Fitzpatrick Institute for Photonics（菲茨帕特里克光子学研究所）

We use mechanical translation of a coded aperture for code division multiple access compression of video. We present experimental results for reconstruction at 148 frames per coded snapshot.

2013-02-04cs.CVcs.ITmath.IT

Characterization of Coded Random Access with Compressive Sensing based Multi-User Detection

The emergence of Machine-to-Machine (M2M) communication requires new Medium Access Control (MAC) schemes and physical (PHY) layer concepts to support a massive number of access requests. The concept of coded random access, introduced recently, greatly outperforms other random access methods and is inherently capable to take advantage of the capture effect from the PHY layer. Furthermore, at the PHY layer, compressive sensing based multi-user detection (CS-MUD) is a novel technique that exploits sparsity in multi-user detection to achieve a joint activity and data detection. In this paper, we c…

2014-04-08cs.ITmath.IT

Coded Compressive Sensing: A Compute-and-Recover Approach

In this paper, we propose \textit{coded compressive sensing} that recovers an $n$-dimensional integer sparse signal vector from a noisy and quantized measurement vector whose dimension $m$ is far-fewer than $n$. The core idea of coded compressive sensing is to construct a linear sensing matrix whose columns consist of lattice codes. We present a two-stage decoding method named \textit{compute-and-recover} to detect the sparse signal from the noisy and quantized measurements. In the first stage, we transform such measurements into noiseless finite-field measurements using the linearity of latti…

2016-01-26cs.ITmath.IT

Compressive Coded Random Access for Massive MTC Traffic in 5G Systems

Massive MTC support is an important future market segment, but not yet efficiently supported in cellular systems. In this paper we follow-up on recent concepts combining advanced MAC protocols with Compressed Sensing (CS) based multiuser detection. Specifically, we introduce a concept for sparse joint activity, channel and data detection in the context of the Coded ALOHA (FDMA) protocol. We will argue that a simple sparse activity and data detection is not sufficient (as many papers do) because control resources are in the order of the data. In addition, we will improve on the performance of s…

2017-06-29cs.ITmath.IT

Graph Attention Network Based Single-Pixel Compressive Direction of Arrival Estimation

İstanbul Technical University（伊斯坦布尔理工大学）；Queen’s University（女王大学）；Polytechnique Montréal（蒙特利尔理工学院）

In this paper, we present a single-pixel compressive direction of arrival (DoA) estimation technique leveraging a graph attention network (GAT)-based deep-learning framework. The physical layer compression is achieved using a coded-aperture technique, probing the spectrum of far-field sources that are incident on the aperture using a set of spatio-temporally incoherent modes. This information is then encoded and compressed into the channel of the coded-aperture. The coded-aperture is based on a metasurface antenna design and it works as a receiver, exhibiting a single-channel and replacing the…

2021-11-01cs.ITcs.LGeess.SP

更多相关论文收起更多论文

压缩反卷积在随机掩码成像中的应用

Compressive Deconvolution in Random Mask Imaging

School of Electrical and Computer Engineering, Georgia Institute of Technology（佐治亚理工学院电气与计算机工程学院）

研究通过随机编码掩码实现信号重建，证明在少量测量下可稳定反卷积，并展示稀疏图像恢复的可行性。

2015-09-03cs.ITcs.NAmath.FA

Quantized Compressive Sensing

We study the average distortion introduced by scalar, vector, and entropy coded quantization of compressive sensing (CS) measurements. The asymptotic behavior of the underlying quantization schemes is either quantified exactly or characterized via bounds. We adapt two benchmark CS reconstruction algorithms to accommodate quantization errors, and empirically demonstrate that these methods significantly reduce the reconstruction distortion when compared to standard CS techniques.

2009-03-07cs.ITmath.IT

A new compressive video sensing framework for mobile broadcast

Rice University（莱斯大学）

A new video coding method based on compressive sampling is proposed. In this method, a video is coded using compressive measurements on video cubes. Video reconstruction is performed by minimization of total variation (TV) of the pixelwise DCT coefficients along the temporal direction. A new reconstruction algorithm is developed from TVAL3, an efficient TV minimization algorithm based on the alternating minimization and augmented Lagrangian methods. Video coding with this method is inherently scalable, and has applications in mobile broadcast.

2013-02-08cs.CVcs.ITcs.MM

Approximate Message Passing in Coded Aperture Snapshot Spectral Imaging

We consider a compressive hyperspectral imaging reconstruction problem, where three-dimensional spatio-spectral information about a scene is sensed by a coded aperture snapshot spectral imager (CASSI). The approximate message passing (AMP) framework is utilized to reconstruct hyperspectral images from CASSI measurements, and an adaptive Wiener filter is employed as a three-dimensional image denoiser within AMP. We call our algorithm "AMP-3D-Wiener." The simulation results show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (…

2015-09-08cs.ITmath.IT

Compressive Hyperspectral Imaging via Approximate Message Passing

We consider a compressive hyperspectral imaging reconstruction problem, where three-dimensional spatio-spectral information about a scene is sensed by a coded aperture snapshot spectral imager (CASSI). The CASSI imaging process can be modeled as suppressing three-dimensional coded and shifted voxels and projecting these onto a two-dimensional plane, such that the number of acquired measurements is greatly reduced. On the other hand, because the measurements are highly compressive, the reconstruction process becomes challenging. We previously proposed a compressive imaging reconstruction algori…

2015-10-28cs.ITmath.IT

使用可重构智能表面的编码孔径雷达成像

Coded Aperture Radar Imaging Using Reconfigurable Intelligent Surfaces

本文研究利用单个收发器与可重构智能表面（RIS）的编码孔径雷达成像，通过投影梯度下降设计RIS相移并结合压缩感知，从单天线观测中恢复点散射体和扩展目标雷达场景。

2023-08-11cs.ITeess.SPmath.IT

考虑饱和的快照压缩成像：理论与算法

Snapshot Compressive Imaging under Saturation: Theory, Mask Design, and Reconstruction

Rutgers University（罗格斯大学）

本文提出考虑饱和的快照压缩成像理论与算法，通过分析饱和对SCI重建的影响，提出SAPnet框架以提高重建性能。

2026-08-18cs.ITeess.IVmath.IT

A Variable Density Sampling Scheme for Compressive Fourier Transform Interferometry

Fourier Transform Interferometry (FTI) is an appealing Hyperspectral (HS) imaging modality for many applications demanding high spectral resolution, e.g., in fluorescence microscopy. However, the effective resolution of FTI is limited by the durability of biological elements when exposed to illuminating light. Overexposed elements are subject to photo-bleaching and become unable to fluoresce. In this context, the acquisition of biological HS volumes based on sampling the Optical Path Difference (OPD) axis at Nyquist rate leads to unpleasant trade-offs between spectral resolution, quality of th…

2019-01-30cs.ITmath.IT

High Resolution Compressed Sensing Radar using Difference Set Codes

In this paper, we consider compressive sensing (CS)-based recovery of delays and Doppler frequencies of targets in high resolution radars. We propose a novel sub-Nyquist sampling method in the Fourier domain based on difference sets (DS), called DS-sampling, to create dictionaries with highly incoherent atoms. The coherence of the dictionary reaches the Welch minimum bound if the DS-sampling is employed. This property let us to implement sub-Nyquist high resolution radars with minimum number of samples. We also develop a low complexity recovery method, based on structured CS and propose a new …

2018-10-31cs.ITmath.IT