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Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints最新文献

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The Phase Problem in Object Reconstruction and Interferometry 物体重建与干涉测量中的相位问题
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.tha1
H. Ferwerda
{"title":"The Phase Problem in Object Reconstruction and Interferometry","authors":"H. Ferwerda","doi":"10.1364/srs.1983.tha1","DOIUrl":"https://doi.org/10.1364/srs.1983.tha1","url":null,"abstract":"In this contribution I shall review phase problems from different fields of optics which can be handled with similar techniques. In all cases the problem is to reconstruct the phase of a function from its modulus. In object reconstruction we have to know the complex image wave function (w.f.) while the intensity distribution only gives its modulus. In speckle interferometry only the autocorrelation of the brightness distribution of the source (or equivalently the modulus squared of its Fourier transform) is measurable. In interference microscopy often only the visibility of the interference fringes formed in a Michelson interferometer can be observed, yielding the absolute value of the complex degree of temporal coherence. But we also need its phase for the calculation of the spectral distribution of the source.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115098403","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: 0
Speckle Interferometry: One-Dimensional Image Reconstruction from Zeros of Complex Spectrum 散斑干涉法:复光谱的一维图像零点重建
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.tha6
Y. Bruck, L. Sodin
{"title":"Speckle Interferometry: One-Dimensional Image Reconstruction from Zeros of Complex Spectrum","authors":"Y. Bruck, L. Sodin","doi":"10.1364/srs.1983.tha6","DOIUrl":"https://doi.org/10.1364/srs.1983.tha6","url":null,"abstract":"The method suggested by Labeyrie [1] allows reconstruction of the Fourier spectrum modulus to be performed for images scattered by a random atmosphere. Ultimately one is able to determine the autocorrelation function of the image, yet not the image itself.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134538295","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: 0
Localization From Projections Based on Detection and Estimation of Objects* 基于目标检测和估计的投影定位方法*
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.fa3
D. Rossi, A. Willsky
{"title":"Localization From Projections Based on Detection and Estimation of Objects*","authors":"D. Rossi, A. Willsky","doi":"10.1364/srs.1983.fa3","DOIUrl":"https://doi.org/10.1364/srs.1983.fa3","url":null,"abstract":"The problem of reconstructing a two-dimensional (2D) function from its ID projections arises, typically in the context of cross-sectional imaging, in a diversity of disciplines [1-3]. In this problem, a 2D function f(x) is estimated from samples of its Radon, transform (line integral measurements) where \u0000θ_=(cosθ sinθ)¢. The major emphasis of research and applications in this area has been on producing accurate, high-resolution cross-sectional images (requiring a large number of high signal-to-noise ratio (SNR) measurements taken over a wide viewing angle [4,5]) which in practice are post-processed, perhaps by humans, to remove artifacts and extract the information of interest about the cross-section. For example, in nondestructive testing applications [3], reconstructed images are post-processed to determine whether flaws or defects are present within a homogeneous medium; in oceanographic applications, reconstructed images are post-processed to determine where within the cross section an oceanographic cold-core ring is located [2]. Such post-processing is effectively the utilization of a priori information about the medium being measured to enhance and extract specific pieces of information.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130918717","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: 0
Averaging the Fourier Phase Information in a Signal Ensemble without Calculating Phase 在不计算相位的情况下对信号集合中的傅里叶相位信息进行平均
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.tha10
H. W. Swan, J. Goodman
{"title":"Averaging the Fourier Phase Information in a Signal Ensemble without Calculating Phase","authors":"H. W. Swan, J. Goodman","doi":"10.1364/srs.1983.tha10","DOIUrl":"https://doi.org/10.1364/srs.1983.tha10","url":null,"abstract":"A length-M discrete stochastic process, s(k), and a length-N deterministic sequence, h(k), are convolved to yield the discrete stochastic process, x(k). If we take the length-L discrete Fourier transform of s(k), h(k), and x(k), where L is some integer greater than N+M−2, and pad with zeros as necessary, then (1) for 0 ≤ n < L. Here H(n) is deterministic while X(n) and S(n) are stochastic. Given an ensemble of the process x(k), and sufficient knowledge of the self-statistics of s(k), we wish to recover h(k). Problems such as this arise in the fields of geophysics, radar signal processing, and space object imaging. Although it is easy to estimate the Fourier magnitude of h(k) from (2) estimating the phase of H(n) can be difficult, due to the phase unwrapping problem[1]. The difficulty is worsened by observational noise and by extending the problem to 2-dimensional images.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125034521","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: 0
Signal Reconstruction from Partial Fourier Domain Information* 基于部分傅立叶域信息的信号重构*
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.tha12
A. Oppenheim, Jae S. Lim
{"title":"Signal Reconstruction from Partial Fourier Domain Information*","authors":"A. Oppenheim, Jae S. Lim","doi":"10.1364/srs.1983.tha12","DOIUrl":"https://doi.org/10.1364/srs.1983.tha12","url":null,"abstract":"There are a variety of practical problems in which only the phase or magnitude of the Fourier transform of a signal is known and it is desired to reconstruct the signal. In this talk, a number of results developed in the Digital Signal Processing Group at M.I.T. over the past several years will be described. The work discussed began initially with an exploration of the intelligibility of phase-only signals, that is ones for which the correct Fourier transform phase is combined with a constant or characteristic Fourier transform magnitude function. Motivated by the importance of Fourier transform phase in relation to Fourier transform magnitude, a theory and associated algorithms were then developed for the exact reconstruction of finite length signals from phase information alone.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130358069","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: 2
Practical Interpolation of 2-D Surfaces Using the Gerchberg Algorithm 利用Gerchberg算法对二维曲面进行实用插值
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.wa3
M. Carlotto, Victor T. Tom
{"title":"Practical Interpolation of 2-D Surfaces Using the Gerchberg Algorithm","authors":"M. Carlotto, Victor T. Tom","doi":"10.1364/srs.1983.wa3","DOIUrl":"https://doi.org/10.1364/srs.1983.wa3","url":null,"abstract":"The interpolation of 2-D wind and hydrographic surfaces is accomplished using the Gerchberg algorithm. Special emphasis is given to algorithm implementation on an array processor.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126238216","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: 0
Inverse Scattering Reconstructions From Incomplete Fourier Space Data 不完全傅里叶空间数据的逆散射重建
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.fa9
N. Farhat
{"title":"Inverse Scattering Reconstructions From Incomplete Fourier Space Data","authors":"N. Farhat","doi":"10.1364/srs.1983.fa9","DOIUrl":"https://doi.org/10.1364/srs.1983.fa9","url":null,"abstract":"We show that 3-D tomographic inverse scattering reconstruction of a scattering object is obtainable from data lying on a curved surface, rather than within a volume, of its accessed Fourier space as would ordinarily be required.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":" 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120828316","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: 0
Optimal Iterative Image Reconstruction with Incomplete and Approximate Data 不完全近似数据下图像的最优迭代重建
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.wa11
J. Gassmann
{"title":"Optimal Iterative Image Reconstruction with Incomplete and Approximate Data","authors":"J. Gassmann","doi":"10.1364/srs.1983.wa11","DOIUrl":"https://doi.org/10.1364/srs.1983.wa11","url":null,"abstract":"For the determination and improvement of phases in X-ray analysis a procedure called \"phase correction\" or \"density modification\" has been developed1,2). It is applicable to all types of images when the spectral density is known. It has been applied to various structure determinations of small molecules3), resolution extension of macro molecules4), phase improvement in a virus structure5) and reduction of the effect of missing projection data in electron microscopy.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115037626","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: 0
Signal Deconvolution Using Frequency and Time Domain Magnitude Constraints 利用频域和时域幅度约束的信号反卷积
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.wa14
H. Trussell, P. Sura
{"title":"Signal Deconvolution Using Frequency and Time Domain Magnitude Constraints","authors":"H. Trussell, P. Sura","doi":"10.1364/srs.1983.wa14","DOIUrl":"https://doi.org/10.1364/srs.1983.wa14","url":null,"abstract":"In many signal restoration problems we have very limited knowledge about the statistics required for implementation of the most common restoration techniques, for example, Wiener filtering. We do, however, possess some practical a priori knowledge about the nature of the signal we week to estimate. Because of this a priori knowledge, it may be suboptimal to use methods which make few assumptions about the nature of the ideal signal, for example, maximum entropy restoration [1]. Iterative restoration methods can be easily modified to incorporate such a priori knowledge while requiring little statistical information [2].","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"723 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116558879","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: 0
Partial Shape Recognition using Fourier-Mellin Transform Methods 基于Fourier-Mellin变换方法的部分形状识别
Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints Pub Date : 1900-01-01 DOI: 10.1364/srs.1983.tha19
T. A. Grogan, O. Mitchell
{"title":"Partial Shape Recognition using Fourier-Mellin Transform Methods","authors":"T. A. Grogan, O. Mitchell","doi":"10.1364/srs.1983.tha19","DOIUrl":"https://doi.org/10.1364/srs.1983.tha19","url":null,"abstract":"In recognizing shapes automatically by computer, a problem often arises when the unknown object is partially obscured or poorly segmented. Most algorithms described in the literature use syntactic methods. A major problem is describing a proper grammar for several objects. This problem is even further complicated when each object may be imaged from many possible aspect angles. The algorithm in this paper avoids this problem. It uses a global method to normalize scale and starting point, even when part of the contour is missing or incorrect.","PeriodicalId":279385,"journal":{"name":"Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints","volume":"04 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129852541","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: 0
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