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Sensing matrix measurement method based on variational Bayesian expectation Maximization algorithm

An expectation-maximization algorithm, variational Bayesian technology, applied in the measurement of scattering properties, analyzing materials, complex mathematical operations, etc., can solve the problems of slow running speed and expensive scale of SLM, and achieve fast running speed, cheap and stable equipment. good effect

Active Publication Date: 2018-03-13
NANJING UNIV OF SCI & TECH
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Problems solved by technology

The disadvantage of this method is that SLM is too expensive and small in scale, and its operation speed is relatively slow compared to DMD (Digital Microlens Array)

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  • Sensing matrix measurement method based on variational Bayesian expectation Maximization algorithm
  • Sensing matrix measurement method based on variational Bayesian expectation Maximization algorithm
  • Sensing matrix measurement method based on variational Bayesian expectation Maximization algorithm

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Embodiment Construction

[0023] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0024] The present invention proposes a sensing matrix measurement method based on Bayesian framework and mean field assumption, the steps are as follows:

[0025] First, briefly describe the optical path setting and its specific characteristics of the imaging system. By light path figure 2 , the laser generated by the laser passes through the beam expander system to generate parallel light and strikes on the digital microlens array DMD; the DMD performs random binary amplitude modulation (0-1 modulation) on the incident light, and each mode state of the DMD can be regarded as a Light wavefront input; the wavefront light modulated by DMD is focused on the scattering medium through the lens, and random scattering occurs when the light is transported in the medium, such as figure 2 The light shown on the right forms an output mode after passing through the ...

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Abstract

The invention discloses a sensing matrix measurement method based on a variational Bayesian expectation Maximization algorithm. According to the sensing matrix measurement method, light wave-front modulation is performed with a digital micro lens array (DMD), and calibration measurement is performed, wherein yp is |Dxp|, and p belongs to {1,2, . . . . P}; the image data is processed to obtain B, and the calculation of a sensing matrix D is replaced with the calculation of am[belong to]A, wherein B is |[phi]A|; mean-field hypothesis is introduced, and variational Bayesian expectation Maximization (VBEM) algorithm is performed to solve a maximum a posteriori estimation problem to obtain am; and the am is combined to obtain a matrix A so as to obtain the sensing matrix D. According to the present invention, the light wave-front modulation is performed with the DMD, and the method has advantages of high equipment speed, large pixel size and reasonable algorithm complexity, and can well complete the measurement of the sensing matrix.

Description

technical field [0001] The invention belongs to the sensory matrix measurement technology in the field of parallel compressed sensing, in particular to a sensory matrix measurement method based on variational Bayesian expectation maximum algorithm. Background technique [0002] Compressed Sensing (CS) is a new theoretical method in the field of signal acquisition and processing in recent years. Different from the traditional sampling theory of first sampling and then compression, its core idea is to directly obtain the compressed signal, that is, to combine the signal compression process in the imaging system. The number of samples obtained by this method is much smaller than the traditional method based on Shannon's theorem, which can significantly save the storage space required for signal processing and transmission. [0003] The Cs theory mainly includes three aspects: the sparse representation of the signal, the design of the sensing matrix and the reconstruction algor...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/47G06F17/16
CPCG01N21/47G01N2201/06113G06F17/16
Inventor 隋修宝周圣航陈钱顾国华赵耀高航刘源张业伟杨成章
Owner NANJING UNIV OF SCI & TECH
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