An iterative phase correction method for low-quality fringe images

Abstract

The invention belongs to the field of optical measurement, and specifically discloses an iterative phase correction method for low-quality fringe images. The method includes: projecting a phase-shifted fringe image, shooting and decoding to obtain an initial phase; projecting the initial phase into the image brightness space, and obtaining a phase-projected fringe image of the current iterative cycle; performing Gaussian filtering on it to obtain a Gaussian filter of the current iterative cycle Phase; determine whether the error between the Gaussian filter phase of the current iteration cycle and the Gaussian filter phase of the previous iteration cycle is less than or equal to the preset threshold, if so, output it; if not, project it into the image brightness space for iteration . The present invention projects the phase into the image brightness space to obtain a fringe image with uniform reflectivity, and suppresses the influence of Gaussian noise. Iterative filtering for the fringe image will eliminate the influence of the surface reflectivity of the object and the nonlinear brightness of the light source, thereby Achieve high-precision phase recovery of low-quality fringe images.

Description

technical field [0001] The invention belongs to the technical field related to optical measurement, and more specifically, relates to an iterative phase correction method for low-quality fringe images. Background technique [0002] Optical 3D measurement methods, such as structured light and phase deflection, play an increasingly important role in modern manufacturing. Among them, the phase shift technology is a bridge connecting the measured object and the sensor. The accuracy of phase recovery directly determines the measurement accuracy of optical measurement methods. Generally speaking, there are three main factors that affect the accuracy of phase recovery: 1. The quality of phase shift fringe images obtained; 2. The number of phase shift steps; 3. Brightness modulation parameters. Wherein, as the number of phase shift steps increases, the number of phase shift images to be projected also increases, and the measurement speed decreases accordingly. The parameter of br...

AI Technical Summary

Problems solved by technology

Therefore, when filtering the fringe image of an object with a large reflectivity change, it will be affected by the surface reflectivity and cause distortion

And a significant drawback of high dynamic range imaging technology is the large number of projected pictures, which leads to slow measurement speed

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