CN116754080A - Unstable pixel testing method of infrared focal plane device - Google Patents
Unstable pixel testing method of infrared focal plane device Download PDFInfo
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Abstract
The application discloses an unstable pixel testing method of an infrared focal plane device, which comprises the following steps: obtaining the background voltage of the area array bare circuit; obtaining area array voltage equalizing time sequence fitting curves; obtaining a time sequence fitting curve of each pixel of the area array; calculating to obtain fitting standard deviation of each pixel voltage; calculating to obtain the fitting difference standard deviation of each pixel; calculating to obtain the current spectrum density of each pixel; fitting standard deviation by each pixel, and judging the stability of a single pixel; fitting a standard deviation of the difference by each pixel, and judging the stability of a single pixel; the stability of a single pixel is judged by the current spectral density of each pixel, and the method starts from the time domain and the frequency domain of the pixel voltage Ue time sequence, and calculates by the time sequence of the pixels: fitting STD, fitting difference STD and current spectrum density, thereby accurately judging unstable pixels.
Description
Technical Field
The application relates to the technical field of infrared detector testing, in particular to an unstable pixel testing method of an infrared focal plane device.
Background
An infrared focal plane device (infrared Focal Plane Arrays) belongs to a multi-element planar array infrared detection device which can enable each pixel of a scene in the whole view field to correspond to a sensitive element on the focal plane of an infrared optical system. At present, the method has huge market potential and application prospect.
The unstable pixel of the infrared detector has a great influence on the quality of an infrared detection image. The detector generates K, B table (Y (ij) =k (ij) ×x (ij) +b (ij)) by performing two-point correction, wherein Y (ij) represents a pixel of an ith row and a jth column in the corrected image; k (ij) represents a correction coefficient corresponding to a pixel of an ith row and a jth column; x (ij) represents a pixel of an ith row and a jth column in the original image; b (ij)) represents the compensation amount corresponding to the pixel of the j-th column of the i-th row. For the plane source black body uniform surface, the detector generates K, B table (y=kx+b) by two-point correction, and for the black body uniform surface, the Y image is non-uniformly fluctuated, the root cause is that the pixel current Ie is changed, so that the pixel voltage Ue of the X image is fluctuated, and the unstable pixel (ueune) is the unstable pixel with larger Ue fluctuation, see fig. 1.
At present, the conventional peripheral AD average value comparison method has certain defects: if the AD value of one pixel changes greatly (for example, is 8 times greater than the judgment threshold value), unstable erroneous judgment of 8 surrounding effective pixels can be caused, and the measurement accuracy of the unstable elements is poor. How to accurately and quantitatively measure unstable pixels is very important for the evaluation of the detector grade.
Disclosure of Invention
In order to solve the technical problems, the application provides an unstable pixel testing method of an infrared focal plane device.
The technical problems solved by the application can be realized by adopting the following technical scheme:
a method for testing an unstable pixel of an infrared focal plane device comprises the following steps:
step S1, setting a detector to be a preset distance from a surface source black body, and setting the surface source black body to be a preset temperature;
s2, closing Gpol, setting minimum integration time, continuously acquiring a plurality of pieces of image data, generating an infrared detection image acquired each time, and calculating average voltage for each pixel of an area array to obtain area array bare circuit background voltage;
step S3, setting Gpol, setting integration time, continuously collecting a plurality of pieces of image data, generating an infrared detection image collected each time on average, then obtaining area array voltage-sharing, and performing curve fitting on an area array voltage-sharing time sequence to obtain an area array voltage-sharing time sequence fitting curve; performing curve fitting on the voltage time sequence of each pixel to obtain a fitting curve of the time sequence of each pixel of the area array;
s4, fitting curves are fitted through the voltage time sequence of each pixel of the area array and the time sequence of each pixel of the area array, and the fitting standard deviation of each pixel voltage is calculated;
s5, fitting a curve by each pixel time sequence of the area array, fitting a curve by the voltage-equalizing time sequence of the area array, and calculating to obtain the standard deviation of each pixel fitting difference by the average value of the fitting curve of each pixel time sequence of the area array and the average value of the fitting curve of the voltage-equalizing time sequence of the area array;
s6, calculating the current spectral density of each pixel by the area array bare circuit background voltage, the area array each pixel voltage time sequence, the pixel integration capacitance and the pixel effective integration time;
step S7, fitting standard deviation by each pixel, and judging the stability of a single pixel;
fitting a standard deviation of the difference by each pixel, and judging the stability of a single pixel;
and judging the stability of the single pixel according to the current spectrum density of each pixel.
The application starts from the time domain and the frequency domain of the pixel voltage Ue time sequence, calculates by the time sequence of the pixels: the method for effectively measuring the unstable pixel of the infrared detector is provided by three criteria of fitting STD, fitting difference STD and current spectral density, so that the unstable pixel can be accurately judged.
Drawings
FIG. 1 is a schematic diagram of a pixel;
FIG. 2 is a flow chart of an unstable pixel testing method of the present application;
FIGS. 3-4 are schematic diagrams of overstepping unstable pixels corresponding to fdSTD/csP;
FIGS. 5-6 are schematic diagrams of overstepping unstable pixels corresponding to fSTD/fdSTD/csP;
FIGS. 7-8 are schematic diagrams of unstable pixels screened out corresponding to an overstd;
FIGS. 9-10 are schematic diagrams of the screening out of unstable pixels corresponding to an overdstd;
FIGS. 11-12 are schematic diagrams of overstepping unstable pixels corresponding to csP;
FIGS. 13 to 14 are schematic views of normal pixels;
FIGS. 15 to 16 are schematic views of another normal pixel;
fig. 17 to 19 are schematic diagrams illustrating the screening of unstable pixels with different depths by adjusting the 3-class judgment threshold according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described in the following with reference to the drawings in the embodiments of the present application, so that the advantages and features of the present application can be more easily understood by those skilled in the art, and thus the protection scope of the present application is more clearly and clearly defined. It should be apparent that the described embodiments of the application are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In a preferred embodiment of the present application, based on the above-mentioned problems existing in the prior art, a method for testing an unstable pixel of an infrared focal plane device is provided, which belongs to the technical field of infrared detector testing, as shown in fig. 2, and includes:
step S1, setting a detector to be a preset distance from a surface source black body, and setting the surface source black body to be a preset temperature;
specifically, before testing, first, test preparation is performed, including: the device comprises a surface source black body, a test tool, a detector and a preset blind pixel table.
In a preferred embodiment, in step S1, the preset distance is not greater than 1cm.
Specifically, the distance between the window of the detector and the surface source black body is less than or equal to 1cm.
In a preferred embodiment, in step S1, the preset temperature is 15 to 40, for example 25 ℃.
Specifically, the temperature of the surface source black body is set according to the use condition of the detector, and is preferably 25 ℃.
And S2, closing the Gpol, setting the minimum integration time, continuously acquiring a plurality of pieces of image data, generating an infrared detection image acquired each time, and calculating the average voltage of each pixel of the area array to obtain the background voltage of the area array bare circuit.
Specifically, the GPOL voltage is turned off, a minimum integration time is set, and the minimum integration time is set in association with the readout circuit, for example, the minimum integration time in this embodiment, that is, the acquisition time, and n pieces of image data are continuously acquired at the frame rate f1 at a minimum integration time, for example, 0.33 ms. In this embodiment f1=10 to 100HZ, e.g. 25HZ, n=10 to 1000, e.g. 100, the minimum integration time is 4ms. And generating an infrared detection image acquired each time, and then calculating average voltage for each pixel of the area array to obtain bare circuit background voltage, wherein each pixel of the area array is subjected to n-point diagram voltage equalizing Be (ij) t.
Step S3, setting Gpol, setting integration time, continuously acquiring a plurality of pieces of image data under the preset integration time, generating an infrared detection image acquired each time on average, and then obtaining area array voltage-sharing, and performing linear fitting on an area array voltage-sharing time sequence, namely fitting the area array pixel voltage-sharing measured each time into an area array voltage-sharing time sequence fitting curve; and performing linear fitting on each pixel voltage time sequence, namely fitting each measured pixel voltage into a planar array each pixel time sequence fitting curve.
Specifically, GPOL voltage is set as the optimal voltage, and integration time is set as the optimal integration time, so that the area array voltage is near the half well, and the well depth is 35% -65%. At a preset integration time, m pieces of image data are continuously acquired at a frame frequency f2, f2=1 to 100hz, m=100 to 1000 pieces, for example, the well depth is 50%, the optimum Gpol is 850mV, the optimum integration time is 28ms, f2=10 hz, and m=500 pieces. Generating pixel voltage and area array voltage equalization corresponding to each acquired infrared detection image, and performing linear fitting on the area array voltage equalization time sequence to obtain a smooth area array voltage equalization time sequence fitting curve; and performing linear fitting on the voltage time sequence of each pixel to obtain a smooth area array time sequence fitting curve of each pixel.
S4, calculating to obtain the fitting standard deviation of each pixel voltage by using the time sequence of each pixel voltage of the area array and the fitting curve of each pixel time sequence of the area array 。
The method specifically comprises the following steps: and solving the sequence standard deviation of the fitting curve of the voltage time sequence of each pixel of the area array and the time sequence of each pixel of the area array, and calculating to obtain the fitting standard deviation of the voltage of each pixel.
The specific formula is as follows:
fsTD(ij)＝std[Ue(ij)t-Fit(ij)t]
wherein fSTD (ij) represents the fitting standard deviation of each pixel, and is used for judging the stability of a single pixel and the self.
Ue (ij) t represents the time sequence of each pixel voltage in the area array, i.e. the sequence of each pixel voltage in the area array in acquisition time.
Fit (ij) t represents a time series fitted curve for each pixel in the area array.
std () represents the standard deviation of the sequence.
And S5, calculating the fitting standard deviation of each pixel by using the time series fitting curve of each pixel of the area array, the voltage-sharing time series fitting curve of the area array, the average value of the time series curve of each pixel of the area array and the average value of the voltage-sharing time series fitting curve of the area array.
The method specifically comprises the following steps:
step S51: solving a difference value between each pixel time sequence fitting curve of the area array and the area array voltage-sharing time sequence fitting curve, namely a first difference value;
step S52: solving a difference value between the average value of each pixel time sequence curve of the area array and the average value of the area array voltage-equalizing time sequence curve, namely a second difference value;
step S53: and (3) solving a sequence standard deviation of the first difference and the second difference, and calculating to obtain a fitting standard deviation of each pixel.
The specific formula is as follows:
fdSTD(ij)＝std{[Fit(ij)t-Fit(A)t]+[AvgFit(ij)t-AvgFit(A)t]}
wherein fdSTD (ij) represents the standard deviation of fitting difference of each pixel, and is used for judging the consistency of single pixel and area array voltage equalizing.
std (): and (5) solving a sequence standard deviation.
Fit (A) t represents an area array voltage equalizing time series fitting curve.
Fit (ij) t represents a time series fitted curve for each pixel of the area array.
AvgFit (ij) t represents Fit (ij) t means.
AvgFit (a) t represents Fit (a) t means.
Step S6: the current spectrum density of each pixel is calculated by the background voltage of the area array bare circuit, the time sequence of each pixel voltage of the area array, the pixel integration capacitance and the effective integration time of the pixels. The method specifically comprises the following steps:
step S61: and solving the difference value between the voltage time sequence of each pixel of the area array and the background voltage equalizing of the bare circuit of each pixel of the area array, multiplying the pixel integration capacitance by the effective integration time of the pixels, and calculating to obtain the current time sequence of each pixel of the area array.
The specific formula is as follows:
Ie(ij)t＝[Ue(ij)t-Be(ij)]*C/int
wherein: ie (ij) t represents the current time sequence of each pixel of the area array;
ue (ij) t represents the voltage time sequence of each pixel of the area array;
be (ij) t represents the background voltage of the bare circuit, and the voltage of each pixel n dot diagram of the area array is equalized.
C: and a pixel integration capacitance.
int: the effective integration time of the picture elements.
Step S62: and (5) obtaining Fourier transform of each pixel current time sequence of the area array, and calculating to obtain the current spectrum density of each pixel.
csP(ij)＝FFT(Ie(ij)t)
csP (ij): the current spectral density of each pixel, and the signal noise of the random telegraph.
FFT (): fourier transform, time-series current is converted to frequency-domain current spectral density.
Step S7, fitting standard deviation by each pixel, and judging the stability of a single pixel;
fitting a standard deviation of the difference by each pixel, and judging the stability of a single pixel;
and judging the stability of the single pixel according to the current spectrum density of each pixel.
Specifically, the method comprises the following steps:
step S71: setting fSTDth (standard deviation judgment threshold), comparing each fSTD (ij) (pixel fitting standard deviation) with fSTDth (fitting standard deviation judgment threshold), if fSTD (ij) > fSTDth,
and judging that the stability of the single pixel per se exceeds the standard and the single pixel is an unstable pixel.
Step S72: setting fdSTDth (fitting difference standard deviation criterion threshold), comparing each pixel fdSTD (ij) (fitting difference standard deviation) with fdSTDth (fitting difference standard deviation criterion threshold), if fdSTD (ij) > fdSTDth,
and judging that the consistency of single pixel and area array voltage equalizing exceeds the standard and the single pixel is an unstable pixel.
Step S73: setting csPth (current spectral density criterion threshold), comparing the current spectral density of each pixel csP (ij) with csPth (current spectral density criterion threshold), if csP (ij) > csPth,
the random telegraph signal noise is considered to be out of standard and is an unstable pixel.
Unstable pixels can be screened out in the application in several ways, and in the implementation unstable pixels are screened out by exceeding one of fSTD/fdSTD/csP; and if all three parameters are not out of standard, the normal pixel is obtained.
F1=25 hz and n=100 sheets are set in the following in conjunction with fig. 3 to 19; f2 The embodiment of the present application will be described with reference to experimental data presented in the accompanying drawings, in which 10hz and m=500, i.e. 500 frames are taken as an example.
Fig. 3 to 16 show that 3 types of criteria threshold values are set, fstdth=1.0 mV; fdstdth=0.4 mV; the csPth=8E-15A/Hz condition is taken as an example, and the corresponding overstepping unstable pixel obtained by the test of the method is shown in a schematic diagram.
Fig. 3 is in particular a block diagram in which the pixel of row 2, column 624 is calculated according to the method of the application:
fdSTD＝0.643mV>fdSTDth＝0.4mV；
fSTD＝0.687mV<fSTDth＝1.0mV；
FIG. 4 is a schematic diagram of the pixel of FIG. 3 corresponding to csP superscalar, where csP =1.2E-14A/HZ > csPth=8E-15A/Hz;
thus, it can be seen that this pixel fdSTD/csP exceeds the standard and is an unstable pixel.
Fig. 5 is a schematic diagram in which the 505 th row 431 column pixel is calculated according to the method of the present application:
fdSTD＝0.512mV>fdSTDth＝0.4mV；
fSTD＝1.022mV>fSTDth＝1.0mV；
FIG. 6 is a schematic diagram of the pixel of FIG. 5 corresponding to csP superscalar, where csP =1.4E-14A/HZ > csPth=8E-15A/Hz;
thus, it can be seen that the pixels fdSTD/fsTD/csP are all overstandard and are unstable pixels.
Fig. 7 shows pixels in row 32 and column 588 calculated according to the method of the present application:
fdSTD＝0.270mV<fdSTDth＝0.4mV；
fSTD＝1.008mV>fSTDth＝1.0mV；
FIG. 8 is a schematic diagram of the pixel of FIG. 7 corresponding to csP without exceeding the standard, wherein csP =6.1E-15A/HZ < csPth=8E-15A/Hz;
thus, it can be seen that this pixel is only overstd and is an unstable pixel.
Fig. 9 specifically shows a pixel in which the 76 th row 444 column is calculated according to the method of the present application:
fdSTD＝0.408mV>fdSTDth＝0.4mV；
fSTD＝0.653mV<fSTDth＝1.0mV；
fig. 10 is a schematic diagram of the pixel of fig. 9 corresponding to csP without exceeding the standard, wherein csP =6.6e-15A/HZ < cspth=8e-15A/HZ;
thus, it can be seen that this pixel is only fdSTD out of specification, being an unstable pixel.
Fig. 11 is in particular a block diagram in which the 431 th row 295 column pixel is calculated according to the method of the present application:
fdSTD＝0.329mV<fdSTDth＝0.4mV；
fSTD＝0.527mV<fSTDth＝1.0mV；
FIG. 12 is a schematic diagram of the pixel of FIG. 11 corresponding to csP superscalar, where csP =8.1E-15A/HZ > csPth=8E-15A/Hz;
thus, it can be seen that this pixel is only csP out of standard, being an unstable pixel.
Fig. 13 is a block diagram in which the 5 th row 6 column picture elements are calculated according to the method of the present application:
fdSTD＝0.037mV<fdSTDth＝0.4mV；
fSTD＝0.513mV<fSTDth＝1.0mV；
fig. 14 is a schematic diagram of the pixel of fig. 13 corresponding to csP without exceeding the standard, wherein csP =2.0e-15A/HZ < cspth=8e-15A/HZ;
thus, none of the pixels fdSTD/fSTD/csP exceeds the standard, and the pixels are normal stable pixels.
Fig. 15 is a block diagram in which the 250 th row 312 column pixel is calculated according to the method of the present application:
fdSTD＝0.058mV<fdSTDth＝0.4mV；
fSTD＝0.489mV<fSTDth＝1.0mV；
fig. 16 is a schematic diagram of the pixel of fig. 15 corresponding to csP without exceeding the standard, wherein csP =1.8e-15A/HZ < cspth=8e-15A/HZ;
thus, none of the pixels fdSTD/fSTD/csP exceeds the standard, and the pixels are normal stable pixels.
Fig. 17 to 19 are schematic diagrams illustrating the screening of unstable pixels with different depths by adjusting the 3-class judgment threshold according to an embodiment of the present application.
The preset thresholds are different in size, and the judgment results of the corresponding unstable pixels are also different. In the embodiment, 3 kinds of judging thresholds can be adjusted, unstable elements with different depths are screened, and the smaller the preset threshold is, the smaller the relative current change rate of the corresponding pixels obtained through screening is, so that the accuracy of judging the unstable pixels is further improved. Where UNPf represents the fitting standard deviation instability bin. UNPfd represents the fitting difference standard deviation unstable element. Unplcsp represents a current spectral density instability element. UNP: total instability element.
Fig. 17 is specifically fstdth=1.1 mV; fdstdth=0.5 mV; the csPth=9E-15A/Hz condition is taken as an example, and the corresponding overstepping diagram of the unstable pixel is obtained by testing the method. From fig. 17, it can be seen that the method of the present application was used to screen out: UNPf represents 73 fitting standard deviation unstable elements. UNPfd represents 116 fitting difference standard deviation unstable elements. Unplcsp represents 316 current spectral density instabilities. UNP: and 341 total unstable elements.
Fig. 18 is specifically fstdth=1.0mV; fdstdth=0.4 mV; the csPth=8E-15A/Hz condition is taken as an example, and the corresponding overstepping unstable pixel obtained by the test of the method is shown in a schematic diagram. From fig. 18, it can be seen that the screening out using the method of the present application: un pf represents 99 fitting standard deviation instabilities. UNPfd represents 252 standard deviation unstable elements of the fitting difference. Unplcsp represents 479 current spectral density instabilities. UNP: total of 528 unstable elements.
Fig. 19 is specifically fstdth=0.9 mV; fdstdth=0.3 mV; the csPth=9E-15A/Hz condition is taken as an example, and the corresponding overstepping diagram of the unstable pixel is obtained by testing the method. From fig. 19, it can be seen that the method of the present application was used to screen out: un pf represents 161 fitting standard deviation instabilities. UNPfd represents 631 fitting difference standard deviation unstable elements. Unplcsp represents 316 current spectral density instabilities. UNP: total of 742 unstable elements.
From fig. 17, fig. 18 and fig. 19, it can be seen that the smaller the preset threshold value is, the smaller the relative current change rate of the corresponding pixels obtained by screening is, the more unstable pixels are screened, and the higher the accuracy is.
The application starts from the time domain and the frequency domain of the pixel voltage Ue time sequence, calculates by the time sequence of the pixels: fitting STD, fitting difference STD and current spectrum density, thereby accurately judging unstable pixels.
The foregoing is merely illustrative of the preferred embodiments of the present application and is not intended to limit the embodiments and scope of the present application, and it should be appreciated by those skilled in the art that equivalent substitutions and obvious variations may be made using the description and illustrations herein, which should be included in the scope of the present application.
Claims (9)
1. A method for testing an unstable pixel of an infrared focal plane device, comprising:
step S1, setting a detector to be a preset distance from a surface source black body, and setting the surface source black body to be a preset temperature;
s2, closing Gpol, setting minimum integration time, continuously acquiring a plurality of pieces of image data, generating an infrared detection image acquired each time, and calculating average voltage for each pixel of an area array to obtain area array bare circuit background voltage;
step S3, setting Gpol, setting integration time, continuously collecting a plurality of pieces of image data, generating an infrared detection image collected each time on average, then obtaining area array voltage-sharing, and performing curve fitting on an area array voltage-sharing time sequence to obtain an area array voltage-sharing time sequence fitting curve; performing curve fitting on the voltage time sequence of each pixel to obtain a fitting curve of the time sequence of each pixel of the area array;
s4, fitting curves are fitted through the voltage time sequence of each pixel of the area array and the time sequence of each pixel of the area array, and the fitting standard deviation of each pixel voltage is calculated;
s5, fitting a curve by each pixel time sequence of the area array, fitting a curve by the voltage-equalizing time sequence of the area array, and calculating to obtain the standard deviation of each pixel fitting difference by the average value of the fitting curve of each pixel time sequence of the area array and the average value of the fitting curve of the voltage-equalizing time sequence of the area array;
s6, calculating the current spectral density of each pixel by the area array bare circuit background voltage, the area array each pixel voltage time sequence, the pixel integration capacitance and the pixel effective integration time;
step S7, fitting standard deviation by each pixel, and judging the stability of a single pixel;
fitting a standard deviation of the difference by each pixel, and judging the stability of a single pixel;
and judging the stability of the single pixel according to the current spectrum density of each pixel.
2. The method for testing unstable pixels of an infrared focal plane device according to claim 1, wherein in the step S1, the preset distance is not greater than 1cm.
3. The method for testing an unstable pixel of an infrared focal plane device according to claim 1, wherein in the step S1, the preset temperature is 15-40 ℃.
4. The method according to claim 1, wherein in the step S2, the well depth is 35% -65% when the plurality of image data are collected.
5. The method according to claim 1, wherein the step S4 includes determining standard deviations of the fitting curve sequences of the voltage time sequences of each pixel of the area array and the time sequences of each pixel of the area array, and calculating the standard deviations of the fitting curve sequences of each pixel voltage.
6. The method for testing unstable pixels of an infrared focal plane device according to claim 1, wherein in the step S5, the method for calculating the standard deviation of pixel voltage fitting comprises:
step S51: solving a difference value between each pixel time sequence fitting curve of the area array and the area array voltage-sharing time sequence fitting curve, namely a first difference value;
step S52: solving a difference value between the average value of each pixel time sequence curve of the area array and the average value of the area array voltage-equalizing time sequence curve, namely a second difference value;
step S53: and (3) solving a sequence standard deviation of the first difference and the second difference, and calculating to obtain a fitting standard deviation of each pixel.
7. The method for testing unstable pixels of an infrared focal plane device according to claim 1, wherein in the step S6, the method for calculating the current spectral density of each pixel comprises:
step S61: solving the difference value between the voltage time sequence of each pixel of the area array and the background voltage equalizing of the bare circuit of each pixel of the area array, multiplying the pixel integration capacitance by the effective integration time of the pixel, and calculating to obtain the current time sequence of each pixel of the area array;
step S62: and (5) obtaining Fourier transform of each pixel current time sequence of the area array, and calculating to obtain the current spectrum density of each pixel.
8. The method for testing the unstable pixel of the infrared focal plane device according to claim 1, wherein in the step S7, the method specifically comprises:
and S71, setting a fitting standard deviation judgment threshold, and respectively comparing the fitting standard deviation of each pixel with the fitting standard deviation judgment threshold, if the fitting standard deviation is larger than the fitting standard deviation judgment threshold, judging that the stability of the single pixel exceeds the standard, and judging that the single pixel is an unstable pixel.
And S72, setting a fitting standard deviation criterion threshold, comparing the fitting standard deviation of each pixel with the fitting standard deviation criterion threshold, and if the fitting standard deviation is larger than the fitting standard deviation criterion threshold, judging that the consistency of the single pixel and the area array voltage equalizing exceeds the standard, and judging that the single pixel is an unstable pixel.
Step S73, setting a current spectral density criterion threshold, comparing the current spectral density of each pixel with the current spectral density criterion threshold, and if the current spectral density of each pixel is larger than the current spectral density criterion threshold, considering that the random telegraph signal noise exceeds the standard, and obtaining an unstable pixel.
9. The method for testing an unstable pixel of an infrared focal plane device of claim 8, further comprising:
step S74, the fitting standard deviation judgment threshold value is adjusted, and step S71 is repeatedly executed;
step S75, adjusting the fitting standard deviation criterion threshold value, and repeatedly executing step S72;
step S76, the current spectrum density criterion threshold value is adjusted, and step S73 is repeatedly executed.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101825516A (en) * | 2010-05-04 | 2010-09-08 | 电子科技大学 | Device and method for testing infrared focal plane array device |
| CN102410880A (en) * | 2011-08-05 | 2012-04-11 | 重庆邮电大学 | Infrared focal plane array blind pixel detection method based on integral time adjustment |
| CN104330164A (en) * | 2014-08-05 | 2015-02-04 | 凯迈（洛阳）测控有限公司 | Infrared focal plane array blind pixel detection method and device |
| US20180252590A1 (en) * | 2017-06-26 | 2018-09-06 | University Of Electronic Science And Technology Of China | System for testing thermal response time of uncooled infrared focal plane detector array and method therefor |
| CN110542480A (en) * | 2018-05-29 | 2019-12-06 | 杭州海康威视数字技术股份有限公司 | Blind pixel detection method and device and electronic equipment |
| WO2022188099A1 (en) * | 2021-03-11 | 2022-09-15 | 深圳市大疆创新科技有限公司 | Detector, detection device and method, mobile platform, and readable storage medium |
| CN115420386A (en) * | 2022-08-29 | 2022-12-02 | 浙江珏芯微电子有限公司 | Unstable pixel testing method of infrared focal plane device based on relative current |
-
2023
- 2023-06-28 CN CN202310779472.0A patent/CN116754080A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101825516A (en) * | 2010-05-04 | 2010-09-08 | 电子科技大学 | Device and method for testing infrared focal plane array device |
| CN102410880A (en) * | 2011-08-05 | 2012-04-11 | 重庆邮电大学 | Infrared focal plane array blind pixel detection method based on integral time adjustment |
| CN104330164A (en) * | 2014-08-05 | 2015-02-04 | 凯迈（洛阳）测控有限公司 | Infrared focal plane array blind pixel detection method and device |
| US20180252590A1 (en) * | 2017-06-26 | 2018-09-06 | University Of Electronic Science And Technology Of China | System for testing thermal response time of uncooled infrared focal plane detector array and method therefor |
| CN110542480A (en) * | 2018-05-29 | 2019-12-06 | 杭州海康威视数字技术股份有限公司 | Blind pixel detection method and device and electronic equipment |
| WO2022188099A1 (en) * | 2021-03-11 | 2022-09-15 | 深圳市大疆创新科技有限公司 | Detector, detection device and method, mobile platform, and readable storage medium |
| CN115420386A (en) * | 2022-08-29 | 2022-12-02 | 浙江珏芯微电子有限公司 | Unstable pixel testing method of infrared focal plane device based on relative current |
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