Image restoration method, image restoration system and flat panel detector

A repair method and repair system technology, applied in the directions of image enhancement, image analysis, image data processing, etc., can solve problems such as affecting judgment, fuzzy details of edge classes, and complex costs, so as to improve work efficiency, reduce labor costs, and improve The effect of shipment yield

Active Publication Date: 2019-05-03
SHANGHAI IRAY TECH
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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 t

Method used

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  • Image restoration method, image restoration system and flat panel detector
  • Image restoration method, image restoration system and flat panel detector
  • Image restoration method, image restoration system and flat panel detector

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Embodiment 1

[0060] This embodiment provides an image restoration method, such as figure 1 As shown, the method includes the following steps:

[0061] get the first image;

[0062] performing connected domain analysis on the first image, and extracting all defective pixels in the first image;

[0063] Classifying the defect pixels into three categories according to the size and shape of the connected domain: isolated point defects, cluster defects and bad line defects;

[0064] Outputting a second image and repairing the second image according to the type of the defective pixel.

[0065] In this embodiment, the above-mentioned first image is preferably a defect template in an instrument such as a detector.

[0066] In a further preferred embodiment of this embodiment, the connected domain analysis may be performed on the first image, such as the above-mentioned defect template, in order from left to right and from top to bottom.

[0067] In a preferred embodiment of this embodiment, ac...

Embodiment 2

[0071] On the basis of classifying a pair of defective pixels in the embodiment and performing image restoration according to the size of the defective pixels in order from small to large, this embodiment provides a method for repairing isolated point defects. In this embodiment, the domain Weighted average method for outlier repair.

[0072] Since a single pixel does not contain too much image detail, the above-mentioned neighborhood weighted average method is used in this preferred embodiment to repair isolated point defects. The gray level of the isolated points repaired by this method is shown in the following formula (1):

[0073]

[0074] Among them, F is the original image data in the 3×3 pixel neighborhood of the isolated point defect, N is the 3×3 pixel neighborhood area of ​​the isolated point defect, and K is the weighted average coefficient corresponding to the normal pixel in the 3×3 pixel neighborhood of the isolated point defect .

[0075] In a further pref...

Embodiment 3

[0080] Similar to Embodiment 2, on the basis of Embodiment 1, this embodiment provides a method for repairing cluster defects. In this embodiment, a method combining level set and template matching is used to repair the cluster defects. Wherein, the level set method determines the repair order of the bad points of the cluster defect; the template matching method repairs the current bad points determined to be repaired.

[0081] In a preferred embodiment of this embodiment, as figure 2 As shown, using the level set method to determine the repair order of the bad points of the cluster defect includes the following steps: extract the cluster defect and determine the defect boundary of the cluster defect, initialize the defect label F and the arrival time T, and mark The normal pixel points, edge points and defect points of the defect boundary; the arrival time T is obtained based on the level set principle, and is used to determine which bad point of the cluster defect to repair...

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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...

Claims

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Application Information

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IPC IPC(8): G06T5/00
CPCG06T5/005G06T2207/10116G06T7/0002G06F18/211
Inventor 翟永立张楠方志强
Owner SHANGHAI IRAY TECH
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