2017 IEEE International Conference on Computational Photography (ICCP)最新文献

Multiscale gigapixel video: A cross resolution image matching and warping approach 多尺度千兆像素视频:一种交叉分辨率图像匹配和扭曲方法

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951481

Xiaoyun Yuan, Lu Fang, Qionghai Dai, D. Brady, Yebin Liu

引用次数: 32

Fast non-blind deconvolution via regularized residual networks with long/short skip-connections 基于长/短跳跃连接的正则化残差网络的快速非盲反卷积

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951480

Hyeongseok Son, Seungyong Lee

引用次数: 40

Lensless light-field imaging with multi-phased fresnel zone aperture 多相菲涅耳带孔径无透镜光场成像

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951485

Kazuyuki Tajima, T. Shimano, Y. Nakamura, M. Sao, T. Hoshizawa

引用次数: 19

Air-light estimation using haze-lines 利用雾线进行空气光估计

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951489

Dana Berman, T. Treibitz, S. Avidan

引用次数: 131

Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset 通过传输矩阵的相干逆散射:有效的相位检索算法和公共数据集

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951483

Christopher A. Metzler, M. Sharma, S. Nagesh, Richard Baraniuk, O. Cossairt, A. Veeraraghavan

{"title":"Coherent inverse scattering via transmission matrices: Efficient phase retrieval algorithms and a public dataset","authors":"Christopher A. Metzler, M. Sharma, S. Nagesh, Richard Baraniuk, O. Cossairt, A. Veeraraghavan","doi":"10.1109/ICCPHOT.2017.7951483","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2017.7951483","url":null,"abstract":"A transmission matrix describes the input-output relationship of a complex wavefront as it passes through/reflects off a multiple-scattering medium, such as frosted glass or a painted wall. Knowing a medium's transmission matrix enables one to image through the medium, send signals through the medium, or even use the medium as a lens. The double phase retrieval method is a recently proposed technique to learn a medium's transmission matrix that avoids difficult-to-capture interferometric measurements. Unfortunately, to perform high resolution imaging, existing double phase retrieval methods require (1) a large number of measurements and (2) an unreasonable amount of computation. In this work we focus on the latter of these two problems and reduce computation times with two distinct methods: First, we develop a new phase retrieval algorithm that is significantly faster than existing methods, especially when used with an amplitude-only spatial light modulator (SLM). Second, we calibrate the system using a phase-only SLM, rather than an amplitude-only SLM which was used in previous double phase retrieval experiments. This seemingly trivial change enables us to use a far faster class of phase retrieval algorithms. As a result of these advances, we achieve a 100x reduction in computation times, thereby allowing us to image through scattering media at state-of-the-art resolutions. In addition to these advances, we also release the first publicly available transmission matrix dataset. This contribution will enable phase retrieval researchers to apply their algorithms to real data. Of particular interest to this community, our measurement vectors are naturally i.i.d. subgaussian, i.e., no coded diffraction pattern is required.","PeriodicalId":276755,"journal":{"name":"2017 IEEE International Conference on Computational Photography (ICCP)","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124458158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 58

Aperture interference and the volumetric resolution of light field fluorescence microscopy 光场荧光显微镜的孔径干涉与体积分辨率

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951486

Isaac Kauvar, Julie Chang, Gordon Wetzstein

引用次数: 4

The light field 3D scanner 光场3D扫描仪

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951484

Yingliang Zhang, Zhong Li, Wei Yang, Peihong Yu, Haiting Lin, Jingyi Yu

引用次数: 18

Reconstructing rooms using photon echoes: A plane based model and reconstruction algorithm for looking around the corner 利用光子回波重建房间:一种基于平面的模型和用于寻找角落的重建算法

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-12 DOI: 10.1109/ICCPHOT.2017.7951478

A. Pediredla, M. Buttafava, A. Tosi, O. Cossairt, A. Veeraraghavan

{"title":"Reconstructing rooms using photon echoes: A plane based model and reconstruction algorithm for looking around the corner","authors":"A. Pediredla, M. Buttafava, A. Tosi, O. Cossairt, A. Veeraraghavan","doi":"10.1109/ICCPHOT.2017.7951478","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2017.7951478","url":null,"abstract":"Can we reconstruct the entire internal shape of a room if all we can directly observe is a small portion of one internal wall, presumably through a window in the room? While conventional wisdom may indicate that this is not possible, motivated by recent work on ‘looking around corners’, we show that one can exploit light echoes to reconstruct the internal shape of hidden rooms. Existing techniques for looking around the corner using transient images model the hidden volume using voxels and try to explain the captured transient response as the sum of the transient responses obtained from individual voxels. Such a technique inherently suffers from challenges with regards to low signal to background ratios (SBR) and has difficulty scaling to larger volumes. In contrast, in this paper, we argue for using a plane-based model for the hidden surfaces. We demonstrate that such a plane-based model results in much higher SBR while simultaneously being amenable to larger spatial scales. We build an experimental prototype composed of a pulsed laser source and a single-photon avalanche detector (SPAD) that can achieve a time resolution of about 30ps and demonstrate high-fidelity reconstructions both of individual planes in a hidden volume and for reconstructing entire polygonal rooms composed of multiple planar walls.","PeriodicalId":276755,"journal":{"name":"2017 IEEE International Conference on Computational Photography (ICCP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126421385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 51

Compressive spectral anomaly detection 压缩光谱异常检测

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-01 DOI: 10.1109/ICCPHOT.2017.7951482

Vishwanath Saragadam, Jian Wang, Xin Li, Aswin C. Sankaranarayanan

{"title":"Compressive spectral anomaly detection","authors":"Vishwanath Saragadam, Jian Wang, Xin Li, Aswin C. Sankaranarayanan","doi":"10.1109/ICCPHOT.2017.7951482","DOIUrl":"https://doi.org/10.1109/ICCPHOT.2017.7951482","url":null,"abstract":"We propose a novel compressive imager for detecting anomalous spectral profiles in a scene. We model the background spectrum as a low-dimensional subspace while assuming the anomalies to form a spatially-sparse set of spectral profiles different from the background. Our core contributions are in the form of a two-stage sensing mechanism. In the first stage, we estimate the subspace for the background spectrum by acquiring spectral measurements at a few randomly-selected pixels. In the second stage, we acquire spatially-multiplexed spectral measurements of the scene. We remove the contributions of the background spectrum from the spatially-multiplexed measurements by projecting onto the complementary subspace of the background spectrum; the resulting measurements are of a sparse matrix that encodes the presence and spectra of anomalies, which can be recovered using a Multiple Measurement Vector formulation. Theoretical analysis and simulations show significant speed up in acquisition time over other anomaly detection techniques. A lab prototype based on a DMD and a visible spectrometer validates our proposed imager.","PeriodicalId":276755,"journal":{"name":"2017 IEEE International Conference on Computational Photography (ICCP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133574348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Computational multispectral flash 计算多光谱闪光

2017 IEEE International Conference on Computational Photography (ICCP) Pub Date : 2017-05-01 DOI: 10.1109/ICCPHOT.2017.7951479

H. Blasinski, J. Farrell

引用次数: 5