Metal material industrial CT image quality rapid correction method

Abstract

Provided is a metal material industrial CT image quality rapid correction method. The method is characterized in that the method includes following steps: 1) reading a CT image with noise and ring artifact; 2) mapping the CT image read in step 1) to a polar coordinate from a rectangular coordinate, and forming a polar coordinate image; 3) calculating a filtering parameter (Sr) according to the polar coordinate image; 4) performing ring artifact filtering processing on the CT image by employing the filtering parameter (Sr) obtained in step 3) to obtain a CT image which removes the ring artifact; and 5) performing de-noising processing on the CT image which removes the ring artifact to obtain the corrected CT image. The method is used for reconstructing the post-CT image, parameter correction and automatic calculation are realized, the calculating efficiency is high, image details are saved to the maximum, the method is applicable to post-processing of a lot of industrial CT system images in the market, the image signal to noise ratio is increased, especially high-energy linear array industrial CT, the correction effect is good, and the market promotion value is good.

Description

technical field [0001] The invention relates to a method for quickly correcting image quality. Background technique [0002] CT is computer tomography, and X-ray CT essentially reconstructs images by projection. The projection constitutes the input of the whole CT process, so the quality of the projection directly affects the quality of the reconstructed image. However, when the projection data is inherently insufficient, no matter what kind of superior reconstruction algorithm is used, it is impossible to obtain a perfect slice image, and what is obtained can only be a sick CT image. Morbid CT images contain artifacts and noise. Taking linear array detectors as an example, the CT image artifacts formed are mainly ring artifacts, and the image noise is mainly Gaussian noise. Ring artifacts are a typical artifact of CT images, and their causes can be attributed to detector calibration deviation, inconsistent response of array elements, scintillator defects, and even dust ad...

AI Technical Summary

Problems solved by technology

However, the biggest disadvantage of this type of algorithm is that the calculation is complex and the amount of calculation is large, which limits the application of this algorithm in practice.

[0005] The above correction method has a good effect on ring artifact and noise suppression, but there are also some shortcomings

Although the image processing before reconstruction is superior in quality and fidelity, there are still limitations, the relevant parameters are not easy to determine, the calculation is too complicated, the correction time is relatively long, and most CT users are not easy to obtain CT images. Raw data

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