Fast Phase Retrieval from Local Correlation Measurements
نویسندگان
چکیده
منابع مشابه
Fast Phase Retrieval from Local Correlation Measurements
We develop a fast phase retrieval method which can utilize a large class of local phaseless correlationbased measurements in order to recover a given signal x ∈ C (up to an unknown global phase) in near-linear O ( d log d ) -time. Accompanying theoretical analysis proves that the proposed algorithm is guaranteed to deterministically recover all signals x satisfying a natural flatness (i.e., non...
متن کاملPhase retrieval from very few measurements
In many applications, signals are measured according to a linear process, but the phases of these measurements are often unreliable or not available. To reconstruct the signal, one must perform a process known as phase retrieval. This paper focuses on completely determining signals with as few intensity measurements as possible, and on efficient phase retrieval algorithms from such measurements...
متن کاملDisparity from Local Weighted Phase Correlation
Phase based methods for extracting binocular dispar ity are discussed including phase di erence methods and phase correlation A third method is also described that combines some of their properties and appears consistent with recent physiological data
متن کاملCompressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming ?
Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear program, namely, `1-minimization, guarantees recovery of sparse parameter signals even when the system is underdetermined. In this paper, we consider a more chal...
متن کاملFast Compressive Phase Retrieval under Bounded Noise
We study the problem of recovering a t-sparse vector ±x0 in R from m quadratic equations yi = (ai x) with noisy measurements yi’s. This is known as the problem of compressive phase retrieval, and has been widely applied to Xray diffraction imaging, microscopy, quantum mechanics, etc. The challenge is to design a a) fast and b) noise-tolerant algorithms with c) near-optimal sample complexity. Pr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SIAM Journal on Imaging Sciences
سال: 2016
ISSN: 1936-4954
DOI: 10.1137/15m1053761