CN106228517A - Image collecting device image-forming component defect calibration steps - Google Patents
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- G06T5/70—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
Abstract
The present invention proposes a kind of image collecting device image-forming component defect calibration steps, including step: utilize the image acquisition device uniformly white field picture of band image-forming component defect；Obtain the pixel grey scale data of the whitest field picture；The defect pixel of threshold test based on pixel grey scale data and setting uniformly white field picture and normal pixel；Defect pixel and the pixel grey scale deviation ratio of normal pixel of the whitest field picture is obtained based on pixel grey scale data；And utilizing the defect pixel of the whitest field picture and the pixel grey scale deviation ratio of normal pixel to customize the configuration file of described image collecting device, when wherein configuration file is used for image acquisition device image described in later use, the pixel grey scale data to each image pixel of acquired image are calibrated.The present invention calculates defect pixel gray-scale deviation ratio the defect pixel gamma calibration for subsequent acquired image by the whitest field picture, thus so that the image that image-forming component defect is caused can be improved.
Description
Technical field
The present invention relates to image variants technical field, particularly relate to a kind of image collecting device image-forming component (example
Such as area array cameras CCD) defect calibration steps.
Background technology
In the last few years, the use of domestic and international LED display becomes increasingly popular, and meanwhile LED based on area array cameras shows
The development of screen pointwise correction technology is the most progressively accelerated.One Core Superiority of data acquisition amount wonderful works area array cameras, is also it
The major reason being rapidly developed, if but area array cameras the most less notes or not hooligan in daily
If Yanging, it is easy to camera body made moist or the dirty point of CCD occurs, thus causing the local pixel of captured image to occur
Defect.For camera lens external dirty point, finger-marks, can on-the-spot wiping eliminate the effects of the act；And camera lens internal CCD bad point, dirt
Stains etc., cannot eliminate the effects of the act in scene in wiping.Area array cameras for band CCD spot is used for the situation of LED display pointwise correction,
The LED point data utilizing defect CCD pixel to gather may be caused to form abnormal bright dim spot, serious shadow after pointwise correction
Ring the viewing effect to LED display.
Camera CCD spot question essence processing method at present LED display correction is to be directly sent to specialized maintenance shop
Paving is cleaned comprehensively, if but just find camera CCD spot during straightened up in place, take camera temporarily apart and clean and do not show
Real, then processing mode conventional during straightened up in place mainly has software algorithm processing mode and local secondary correction processing mode.
Wherein, software algorithm processing mode is i.e. to use band CCD spot collected by camera LED spot meter to calculate correction system
During number, abnormality detection compensation can be carried out in LED point brightness or correction coefficient rank, thus it is dirty to improve camera CCD
The impact that LED display pointwise correction is brought by stain；LED point brightness or correction coefficient rank no doubt carry out abnormality detection
Requirement can be reached, but seem to compensate when headlight point data by similar local mean value, because current LED point is by phase
The true deviation amount of machine CCD spot impact is not measured by, and more cannot accurately calculate, so the process of this software algorithm is scarce
Point is the correction uniformity that cannot ensure abnormal LED point self.
And local secondary correction process mode refers to that whole pointwise correction process still uses band CCD spot camera to complete,
Shoot topography for the defective locations in effect after correction the most again and do secondary correction, repair the some brightness of defective locations lamp
Value；When LED display exception lamp point is more and distribution relatively dissipates, the process operation of local secondary correction is relatively cumbersome and time-consumingly consumes
Power, additionally local secondary correction may bring the transition problem of screen calibration result whole with surrounding, i.e. local and whole screen to exist slightly
Bright chroma difference.
Summary of the invention
Therefore, based on the asking of the defect such as camera CCD bad point, spot present in prior art LED display pointwise correction
Topic, the present invention proposes a kind of image collecting device image-forming component defect calibration steps based on the whitest field, and it can be necessarily
Improve in degree, eliminate the correction appearance exception that such as area array cameras CCD defect is brought due to image collecting device image-forming component
The problem of lamp point, so that pointwise correction uniformity consistency effect is more stable, is more favored by user.
Specifically, a kind of image collecting device image-forming component defect calibration steps that the embodiment of the present invention proposes, including step
Rapid: (a) utilizes the image acquisition device uniformly white field picture of band image-forming component defect；B () obtains the whitest described field figure
The pixel grey scale data of picture；C () is based on described pixel grey scale data the whitest field picture with described in the threshold test of setting lacks
Fall into pixel and normal pixel；(d) based on described pixel grey scale data obtain described uniformly white field picture described defect pixel and
The pixel grey scale deviation ratio of described normal pixel；And (e) utilizes described defect pixel and the institute of the whitest described field picture
The configuration of the image collecting device that the described pixel grey scale deviation ratio stating normal pixel customizes described band image-forming component defect is civilian
Part, to institute during the image acquisition device image of wherein said configuration file band image-forming component defect described in the later use
The pixel grey scale data of each image pixel of the image gathered are calibrated.
In one embodiment of the invention, described image collecting device image-forming component defect calibration steps is in step (c)
Further comprise the steps of: before and described pixel grey scale data are carried out smothing filtering to obtain the pixel grey scale data after smothing filtering；
Correspondingly, step (c) is the whitest field described in threshold test based on the pixel grey scale data after described smothing filtering and setting
The defect pixel of image and normal pixel.
In one embodiment of the invention, described smothing filtering is gaussian filtering.
In one embodiment of the invention, step (c) specifically includes: utilize the pixel grey scale number after described smothing filtering
According to average structure the white field data of desired homogeneous, and pixel-by-pixel calculating described smothing filtering after pixel grey scale data with described
The ratio of the white field data of desired homogeneous；And judge whether described ratio exceedes described threshold value to detect described lacking pixel-by-pixel
Fall into pixel and described normal pixel.
In one embodiment of the invention, step (d) specifically includes: by the pixel grey scale deviation ratio of described normal pixel
Example is set to 1；And utilize formulaCalculate the pixel grey scale deviation ratio of described defect pixel, its
Middle Aver represents the meansigma methods of described pixel grey scale data, origin (i, j) denotation coordination position be (i, image pixel j)
Pixel grey scale data, (i, j) denotation coordination position is (i, the pixel grey scale deviation ratio of image pixel j) to ratio.
In one embodiment of the invention, described image collecting device image-forming component defect calibration steps also includes step
Rapid: (f) utilizes the correction image of the image acquisition device LED display of described band image-forming component defect, and utilizes
Described configuration file calibrates the pixel grey scale data of each image pixel of described correction image.
In one embodiment of the invention, step (f) utilize described configuration file to calibrate described correction image
The pixel grey scale data of each image pixel include: press the pixel grey scale data of each image pixel of described correction image
Calibrating according to following equation: G'(i, (i, j) (i, j), wherein, (i j) represents described correction image to G to * ratio to j)=G
Coordinate position is that ((i j) represents respective coordinates in described configuration file to ratio for i, the pixel grey scale data of image pixel j)
Position is that (i, the pixel grey scale deviation ratio of image pixel j), G'(i j) represent that the coordinate position of described correction image is
(i, the pixel grey scale data after image pixel calibration j).
In one embodiment of the invention, the image collector of described band image-forming component defect is set to band CCD defect
Area array cameras.
Additionally, a kind of image collecting device image-forming component defect calibration steps that another embodiment of the present invention proposes, including
Step: utilize the image acquisition device uniformly white field picture of band image-forming component defect；Obtain the whitest described field picture
Pixel grey scale data；Threshold test based on described pixel grey scale data Yu setting go out the defect picture of the whitest described field picture
Element；Utilize formulaCalculate the pixel grey scale deviation ratio of described defect pixel, wherein Aver table
Showing the meansigma methods of described pixel grey scale data, (i, j) denotation coordination position is (i, the pixel grey scale of image pixel j) to origin
Data, (i, j) denotation coordination position is (i, the pixel grey scale deviation ratio of defect pixel j) to ratio；And utilize described band
The correction image of the image acquisition device LED display of image-forming component defect, and utilize the picture of described defect pixel
Element gray-scale deviation ratio adjusts image pixel identical with described defect pixel position coordinate in described correction image
Pixel grey scale data.
In one embodiment of the invention, described threshold test based on described pixel grey scale data Yu setting goes out described
The step of the defect pixel of the whitest field picture specifically includes: the average structure desired homogeneous utilizing described pixel grey scale data is white
Field data, and calculate the ratio of described pixel grey scale data and the white field data of described desired homogeneous pixel-by-pixel；And pixel-by-pixel
Point judges whether described ratio exceedes described threshold value and described ratio exceedes the image pixel of described threshold value be judged to described scarce
Fall into pixel.
From the foregoing, it will be observed that the image collecting device image-forming component defect calibration steps of the embodiment of the present invention is by the whitest field figure
As calculating defect pixel gray-scale deviation ratio, constantly can be according to pixel ash in image acquisition such as pointwise correction LED display
Degree deviation ratio calibration image pixel gray level data, thus improve the problem that image-forming component defect is caused that even eliminates.
By the detailed description below with reference to accompanying drawing, the other side of the present invention and feature become obvious.But should know
Road, this accompanying drawing is only the purpose design rather than the restriction as the scope of the present invention explained.It should also be noted that it is unless another
Pointing out outward, it is not necessary to scale accompanying drawing, they only try hard to structure described herein and flow process are described conceptually.
Accompanying drawing explanation
Below in conjunction with accompanying drawing, the detailed description of the invention of the present invention is described in detail.
Fig. 1 is the dimensional Gaussian scattergram being relevant to the embodiment of the present invention.
Fig. 2 is the flow chart of a kind of image collecting device image-forming component defect calibration steps that the embodiment of the present invention proposes.
Detailed description of the invention
Understandable, below in conjunction with the accompanying drawings to the present invention for enabling the above-mentioned purpose of the present invention, feature and advantage to become apparent from
Detailed description of the invention be described in detail.
The following embodiment of the present invention lacks for the camera CCD bad point in prior art LED display pointwise correction, spot etc.
The problem fallen into, it is proposed that a kind of image collecting device image-forming component such as area array cameras CCD defect calibration based on the whitest field
Method, the method uses the image collecting device shooting of band image-forming component defect to obtain the whitest field picture, calculates the whitest field
In image, all image pixel gray level departures, then customize the configuration file of this image collecting device.Follow-up at LED display dress
Put in (such as LED display, LED box, even LED lamp panel etc.) correction and preferentially utilize configuration after extracting image pixel data
File carries out image pixel rank calibration, then carries out follow-up pointwise correction work.Which compared to existing technology in software calculate
Method processes and for the secondary correction processing mode of local, and its calibration effect is the most secure.
Specifically, a kind of based on the whitest field the image collecting device image-forming component defect school that the embodiment of the present invention proposes
Quasi-method, for purposes of illustration only, the present embodiment using area array cameras CCD as the citing of image collecting device image-forming component, it is concrete
Implementation is as follows:
I () utilizes the area array cameras of band CCD defect to gather the whitest field picture
First the uniformly white field being suitable for is selected, the pure white picture that shows such as canonical product bulb separation, liquid crystal display, opaque
Pure white cardboard etc.；Then the area array cameras alignment the whitest field shooting image utilizing band CCD defect (such as bad point, spot etc.) enters
Row saturation analysis, thus obtain the whitest field picture being suitable for.Herein it is noted that on the one hand area array cameras is in shooting
Time uniformly white field is full of whole form (image frame), to ensure that all CCD effectively use, on the other hand face battle array phase
Machine fully to defocus when shooting, it is to avoid photographs the black gap between liquid crystal display white pixel.
(ii) extract the whitest field picture pixel grey scale data, then remove noise jamming by smothing filtering
Smothing filtering commonly uses filtering mode mean filter, medium filtering, gaussian filtering etc., and the present embodiment is for example with 3*
3 gaussian filterings are especially effective for the noise removing Normal Distribution (or claiming Gauss distribution), and dimensional Gaussian is distributed such as following formula
Shown in Fig. 1:
Herein, gaussian filtering masterplate (i.e. gaussian kernel) may utilize gauss of distribution function G (x y) generate that to be arbitrarily designated size big
Little, the whitest field picture pixel grey scale data of recycling Gauss masterplate traversal, it is achieved smothing filtering removes noise.Herein, it is worth
One is mentioned that, smothing filtering remove noise jamming step be preferred steps, say, that in actual applications it is also contemplated that
Do not carry out smothing filtering.
(iii) defect pixel of the whitest field picture of detection
Utilize the average structure white field data of desired homogeneous of the image pixel gray level data after smothing filtering, then by image slices
Element one-to-one principle calculates the image pixel gray level data after smothing filtering and the ratio of the white field data of desired homogeneous, then sets
Determine threshold value and travel through whether judgement ratio exceedes this threshold value pixel-by-pixel；If being normal pixel not less than this threshold value, otherwise if
Exceed this threshold value and be defect pixel.Herein it is noted that the white field data of desired homogeneous is not limited to utilize smothing filtering
After the average of image pixel gray level data construct, it is also possible to utilize an empirical value to construct.
(iv) the pixel grey scale deviation ratio of the whitest field picture is calculated
For the normal pixel detected, then pixel grey scale deviation ratio is: and ratio (i, j)=1；And for detecting
Defect pixel, then combine following formula calculate pixel grey scale deviation ratio be:
Wherein, Aver represents the meansigma methods of the image pixel gray level data after smothing filtering, and (i j) represents smooth to origin
Filtered image pixel gray level data, (i, j) denotation coordination position is (i, the pixel ash that image pixel j) is corresponding to ratio
Degree deviation ratio.
The configuration file of the area array cameras of (v) customization band CCD spot
By each pixel grey scale deviation ratio ratio (i, j) write file, file type and the storage of the whitest field picture
Form is any, facilitates follow-up LED display timing to read.
(vi) correction image pixel gray level is calibrated
The area array cameras alignment LED display utilizing described band CCD defect gathers pointwise correction image, to collecting
Each pixel grey scale data of pointwise correction image calibrate as the following formula:
G'(i, j)=G (i, j) * ratio (i, j)
Wherein, (i, j) represents the pixel grey scale data of pointwise correction image to G, and (i j) represents image pixel ash to ratio
Degree deviation ratio, G'(i, j) represent pixel gradation data after the calibration of pointwise correction image.
Finally, it is worth mentioning at this point that, present invention is using area array cameras CCD as image collecting device imaging
The citing of element, in other embodiments of the present invention, image collecting device image-forming component can also be area array cameras CMOS etc..As
This one, the embodiment of the present invention propose image collecting device image-forming component defect calibration steps can be summarized as shown in Figure 2
Flow chart.
In sum, the image collecting device image-forming component defect calibration steps based on the whitest field of the embodiment of the present invention
Defect pixel gray-scale deviation ratio is calculated by the whitest field picture, can when image acquisition such as pointwise correction LED display
To calibrate image pixel gray level data according to pixel grey scale deviation ratio, thus improve even elimination image-forming component defect and caused
Problem, it specially can reach following beneficial effect: that 1) puts things right once and for all eliminates in image-forming component image pixel rank
The impact of the defects such as spot, is easy to use quick；And 2) image-forming component defect pixel can be ensured with less error
Uniformity consistency effect for pointwise correction LED point.
The above, be only presently preferred embodiments of the present invention, and the present invention not makees any pro forma restriction, though
So the present invention is disclosed above with preferred embodiment, but is not limited to the present invention, any technology people being familiar with this specialty
Member, in the range of without departing from technical solution of the present invention, when the technology contents of available the disclosure above makes a little change or modification
For the Equivalent embodiments of equivalent variations, as long as being without departing from technical solution of the present invention content, according to the technical spirit pair of the present invention
Any simple modification, equivalent variations and the modification that above example is made, all still falls within the range of technical solution of the present invention.
Claims (10)
1. an image collecting device image-forming component defect calibration steps, it is characterised in that include step:
A () utilizes the image acquisition device uniformly white field picture of band image-forming component defect；
B () obtains the pixel grey scale data of the whitest described field picture；
(c) defect pixel based on described pixel grey scale data the whitest field picture with described in the threshold test of setting and normal picture
Element；
D () obtains the described defect pixel of described uniformly white field picture and described normal pixel based on described pixel grey scale data
Pixel grey scale deviation ratio；And
E () utilizes described defect pixel and the described pixel grey scale deviation ratio of described normal pixel of the whitest described field picture
Customizing the configuration file of the image collecting device of described band image-forming component defect, wherein said configuration file is used for later use institute
State during the image acquisition device image of band image-forming component defect grey to the pixel of each image pixel of acquired image
Degrees of data is calibrated.
2. image collecting device image-forming component defect calibration steps as claimed in claim 1, it is characterised in that in step (c)
Further comprise the steps of: before and described pixel grey scale data are carried out smothing filtering to obtain the pixel grey scale data after smothing filtering；
Correspondingly, step (c) is the whitest field described in threshold test based on the pixel grey scale data after described smothing filtering and setting
The defect pixel of image and normal pixel.
3. image collecting device image-forming component defect calibration steps as claimed in claim 2, it is characterised in that described smooth filter
Ripple is gaussian filtering.
4. image collecting device image-forming component defect calibration steps as claimed in claim 2, it is characterised in that step (c) has
Body includes:
Utilize the average structure white field data of desired homogeneous of the pixel grey scale data after described smothing filtering, and put calculating pixel-by-pixel
Pixel grey scale data after described smothing filtering and the ratio of the white field data of described desired homogeneous；And
Judge whether described ratio exceedes described threshold value to detect described defect pixel and described normal pixel pixel-by-pixel.
5. image collecting device image-forming component defect calibration steps as claimed in claim 1, it is characterised in that step (d) has
Body includes:
The pixel grey scale deviation ratio of described normal pixel is set to 1；And
Utilize formulaCalculate the pixel grey scale deviation ratio of described defect pixel, wherein Aver table
Showing the meansigma methods of described pixel grey scale data, (i, j) denotation coordination position is (i, the pixel grey scale of image pixel j) to origin
Data, (i, j) denotation coordination position is (i, the pixel grey scale deviation ratio of image pixel j) to ratio.
6. image collecting device image-forming component defect calibration steps as claimed in claim 1, it is characterised in that also include step
Rapid:
F () utilizes the correction image of the image acquisition device LED display of described band image-forming component defect, and utilize
Described configuration file calibrates the pixel grey scale data of each image pixel of described correction image.
7. image collecting device image-forming component defect calibration steps as claimed in claim 6, it is characterised in that in step (f)
The pixel grey scale data utilizing each image pixel of the described configuration file described correction image of calibration include: to described correction
Calibrate according to the following formula by the pixel grey scale data of each image pixel of image:
G'(i, j)=G (i, j) * ratio (i, j)
Wherein, G (i, j) represent the coordinate position of described correction image for (i, the pixel grey scale data of image pixel j),
Ratio (i, j) represent in described configuration file respective coordinates position for (i, the pixel grey scale deviation ratio of image pixel j),
G'(i, j) represents that the coordinate position of described correction image is (i, the pixel grey scale data after image pixel calibration j).
8. image collecting device image-forming component defect calibration steps as claimed in claim 1, it is characterised in that described band imaging
The image collector of component defects is set to the area array cameras of band CCD defect.
9. an image collecting device image-forming component defect calibration steps, it is characterised in that include step:
Utilize the image acquisition device uniformly white field picture of band image-forming component defect；
Obtain the pixel grey scale data of the whitest described field picture；
Threshold test based on described pixel grey scale data Yu setting go out the defect pixel of the whitest described field picture；
Utilize formulaCalculate the pixel grey scale deviation ratio of described defect pixel, wherein Aver table
Showing the meansigma methods of described pixel grey scale data, (i, j) denotation coordination position is (i, the pixel grey scale of image pixel j) to origin
Data, (i, j) denotation coordination position is (i, the pixel grey scale deviation ratio of defect pixel j) to ratio；And
Utilize the correction image of the image acquisition device LED display of described band image-forming component defect, and utilize institute
State the pixel grey scale deviation ratio of defect pixel adjust in described correction image with described defect pixel position coordinate phase
The pixel grey scale data of same image pixel.
10. image collecting device image-forming component defect calibration steps as claimed in claim 9, it is characterised in that described based on
The step of the defect pixel that described pixel grey scale data and the threshold test of setting go out the whitest described field picture specifically includes:
Utilize the average structure white field data of desired homogeneous of described pixel grey scale data, and calculate described pixel grey scale pixel-by-pixel
Data and the ratio of the white field data of described desired homogeneous；And
Judge whether described ratio exceedes described threshold value and described ratio exceedes the image pixel of described threshold value sentence pixel-by-pixel
It is set to described defect pixel.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106918575A (en) * | 2017-01-19 | 2017-07-04 | 上海胤飞自动化科技有限公司 | A kind of online refractometer optical image security method and system |
| CN107274353A (en) * | 2017-05-17 | 2017-10-20 | 上海集成电路研发中心有限公司 | The bearing calibration of defect pixel in a kind of black white image |
| CN109102466A (en) * | 2017-06-20 | 2018-12-28 | 杭州海康威视数字技术股份有限公司 | Image smear determination method and device |
| CN109357687A (en) * | 2018-09-07 | 2019-02-19 | 上海集成电路研发中心有限公司 | A kind of defect inspection method of cmos image sensor |
| CN110519585A (en) * | 2019-08-23 | 2019-11-29 | 凌云光技术集团有限责任公司 | A kind of imaging calibration method and device applied to image capture device |
| CN113014908A (en) * | 2019-12-19 | 2021-06-22 | 西安诺瓦星云科技股份有限公司 | Image detection method, device and system and computer readable storage medium |
| CN113532801A (en) * | 2021-06-24 | 2021-10-22 | 四川九洲电器集团有限责任公司 | High/multispectral camera dead pixel detection method and system based on distribution quantile |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1732682A (en) * | 2002-12-27 | 2006-02-08 | 株式会社尼康 | Image processing device and image processing program |
| CN102300057A (en) * | 2011-06-14 | 2011-12-28 | 北京空间机电研究所 | Method for correcting response inconsistency of linear array CCD (Charge Coupled Device) image elements |
| CN102968776A (en) * | 2012-11-13 | 2013-03-13 | 华中科技大学 | Linear filter and non-linear filter combined heterogeneity correction method |
| WO2014203366A1 (en) * | 2013-06-20 | 2014-12-24 | 三菱電機株式会社 | Image processing device, method, and program, and image display device |
-
2016
- 2016-07-15 CN CN201610561372.0A patent/CN106228517A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1732682A (en) * | 2002-12-27 | 2006-02-08 | 株式会社尼康 | Image processing device and image processing program |
| CN102300057A (en) * | 2011-06-14 | 2011-12-28 | 北京空间机电研究所 | Method for correcting response inconsistency of linear array CCD (Charge Coupled Device) image elements |
| CN102968776A (en) * | 2012-11-13 | 2013-03-13 | 华中科技大学 | Linear filter and non-linear filter combined heterogeneity correction method |
| WO2014203366A1 (en) * | 2013-06-20 | 2014-12-24 | 三菱電機株式会社 | Image processing device, method, and program, and image display device |
Non-Patent Citations (1)
| Title |
|---|
| 陈兵旗: "《实用数字图像处理与分析》", 28 February 2014 * |
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| CN106918575A (en) * | 2017-01-19 | 2017-07-04 | 上海胤飞自动化科技有限公司 | A kind of online refractometer optical image security method and system |
| CN107274353A (en) * | 2017-05-17 | 2017-10-20 | 上海集成电路研发中心有限公司 | The bearing calibration of defect pixel in a kind of black white image |
| CN109102466A (en) * | 2017-06-20 | 2018-12-28 | 杭州海康威视数字技术股份有限公司 | Image smear determination method and device |
| CN109357687A (en) * | 2018-09-07 | 2019-02-19 | 上海集成电路研发中心有限公司 | A kind of defect inspection method of cmos image sensor |
| CN110519585A (en) * | 2019-08-23 | 2019-11-29 | 凌云光技术集团有限责任公司 | A kind of imaging calibration method and device applied to image capture device |
| CN110519585B (en) * | 2019-08-23 | 2021-07-30 | 凌云光技术股份有限公司 | Imaging calibration method and device applied to image acquisition equipment |
| CN113014908A (en) * | 2019-12-19 | 2021-06-22 | 西安诺瓦星云科技股份有限公司 | Image detection method, device and system and computer readable storage medium |
| CN113532801A (en) * | 2021-06-24 | 2021-10-22 | 四川九洲电器集团有限责任公司 | High/multispectral camera dead pixel detection method and system based on distribution quantile |
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