Image restoration method, image restoration system and flat panel detector

Abstract

The invention provides an image restoration method, an image restoration system and a flat panel detector, and the method comprises the steps: obtaining a first image, carrying out the connected domain analysis of the first image, and extracting all defect pixels in the first image; dividing the defect pixels into isolated point defects, cluster defects and broken line defects according to the size and shape of a connected domain; and outputting the second image and repairing the second image according to the type of the defective pixel. According to the method, defective pixels can be effectively repaired, and details of an original image can be well reserved. And repairing the second image output by the detector in real time according to the classification of the defective pixels to realize the rapid repair of the defective pixels of the image. The method is only related to the type and size of the defective pixel, the applicability is high, and the working efficiency is remarkably improved. The image restoration system is integrated in the detector, the hardware design does not need to be changed, the product cost can be reduced, and only software needs to be optimized and upgraded in subsequent upgrading and maintenance.

Description

technical field [0001] The invention relates to the field of X-ray detector imaging and image restoration, in particular to an image restoration method, an image restoration system and a flat panel detector. Background technique [0002] For X-ray flat-panel detectors, due to various reasons during the production and assembly of the detector, the detector will inevitably produce defective pixels, that is, bad pixels, which cannot truly reflect the Radiant energy received by the pixel unit. Defective pixels are detector cells that do not respond or respond poorly to X-ray intensity. The main causes of defective pixels are defects in the scintillator layer itself, defects in the photodiode and thin film transistor itself, damage to the drive circuit itself, or poor splicing of the detector board, etc. According to the different responses of defective pixels to X-rays, defective pixels can be divided into four types: dead pixels, under-response pixels, over-response pixels, a...

AI Technical Summary

Problems solved by technology

These defective pixels show different shapes when the detector is imaging, which not only reduces the yield rate of the detector when it leaves the factory, but also affects the judgment of the real situation of the photographed object

[0003] At present, there are mainly two methods to eliminate defective pixels of detectors: one is to improve the production process and process of detectors, and reduce the generation of defective pixels of detectors, but such methods are cumbersome, complicated and expensive; It is to use the method of image processing to restore the image details of the detector defects as much as possible

For example, an image processing method used in the prior art mainly uses interpolation methods such as spline interpolation, bilinear interpolation, and three-spline interpolation to repair defective pixels. The gray value of normal pixels in the domain can restore the details of the image to a certain extent, but it will cause blurring on the details of the edge, and it does not consider the details of the image texture.

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