Sensor device and method for determining correction coefficient

Abstract

The present invention relates to a sensor device and a method of determining a correction coefficient. The sensor device comprises a plurality of pixels; and a controller configured to correct measurement signals of the plurality of pixels. Each pixel of the plurality of pixels comprises a photodetector; and a pixel circuit configured to output a signal from the photodetector. The controller is configured to: acquire an unknown measurement signal from one pixel of the plurality of pixels; and correct the unknown measurement signal of the one pixel with a correction coefficient based on a ratio between values obtained from the one pixel under a plurality of reference lights having different intensities and a statistical value acquired from values obtained from measurement signals according to the plurality of pixels under the plurality of reference lights having different intensities.

Description

Technical Field

[0001] The present invention relates to techniques for reducing noise in signals from photodetectors. Background Art

[0002] The noise included in the signal output from the light imaging element is classified into random noise that varies with time and fixed pattern noise (FPN) that does not vary with time. FPN is further classified into two types of FPN: dark FPN and bright FPN. Dark FPN is observed when the light imaging element does not receive light. The intensity of bright FPN varies depending on the intensity of the incident light. It is known that dark FPN is caused by changes in the input and output characteristics of the pixel circuit and readout circuit of the imaging element, while bright FPN is caused by changes in the characteristics of the photoelectric conversion element. The intensity of bright FPN increases as the intensity (number of photons) of the incident light increases.

[0003] Because FPN does not change over time but is spatially fixed due to changes in imaging pixel characteristics, it can be reduced through appropriate signal processing. For example, to reduce dark-time FPN, a method is known that pre-stores the dark-state signal in memory and subtracts it from the detection signal of the photodetector.

[0004] To reduce bright-time FPN, one method is known that prepares one or two reference signals while illuminating the sensor device with uniform reference light of varying intensities and subtracts the reference signals from the detection signal. JP 2015-100099A proposes another method for reducing bright-time FPN by dividing the detection signal by the reference signal under uniform reference light. Summary of the Invention

[0005] However, existing methods cannot sufficiently reduce bright-time FPN. Therefore, a more effective technique is needed to reduce bright-time FPN of a photodetector.

[0006] One aspect of the present invention is a sensor device comprising: a plurality of pixels; and a controller configured to correct measurement signals of the plurality of pixels, wherein each of the plurality of pixels comprises: a photodetector; and a pixel circuit configured to output a signal from the photodetector, and wherein the controller is configured to: obtain an unknown measurement signal from one of the plurality of pixels; and correct the unknown measurement signal of the one pixel using a correction coefficient based on a ratio between a value obtained from the measurement signal of the one pixel under a plurality of reference lights having different intensities and a statistical value obtained from values ​​obtained from the measurement signals of the plurality of pixels under a plurality of reference lights having different intensities.

[0007] One aspect of the present invention is a method for determining a correction coefficient to be used by a controller of a sensor device when correcting measurement signals of multiple pixels of the sensor device, each of the multiple pixels including a photodetector and a pixel circuit configured to output a signal from the photodetector, the method comprising: acquiring measurement signals from the multiple pixels under multiple reference lights having different intensities; determining statistical values ​​of the measurement signals of the multiple pixels under each of the multiple reference lights; and determining a correction coefficient for each pixel based on the statistical values ​​of the measurement signals of the multiple pixels and the measurement signal of each pixel under each of the multiple reference lights.

[0008] An aspect of the present invention can effectively reduce noise included in a signal from a photodetector.

[0009] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 : is a block diagram showing a configuration example of an image sensor according to Embodiment 1.

[0011] Figure 2 A configuration example of a main controller is schematically shown.

[0012] Figure 3 is a circuit diagram showing an example of a circuit configuration of a pixel.

[0013] Figure 4 is a signal flow chart illustrating a calculation method of noise reduction processing according to the related art.

[0014] Figure 5 Experimental results of noise reduction processing of measurement signals according to related art are provided.

[0015] Figure 6 Experimental results of noise reduction processing of measurement signals according to related art are provided.

[0016] Figure 7 This is a signal flow chart showing a calculation method of the noise reduction process in the embodiment of this specification.

[0017] Figure 8 This is a signal flow chart illustrating a method of determining a weight coefficient in an embodiment of this specification.

[0018] Figure 9 An example of raw measurement data of a pixel before noise is removed therefrom is provided.

[0019] Figure 10 Provided according to reference Figure 4 Correction results of the related art described.

[0020] Figure 11 Correction results of the embodiments described are provided according to the reference Figure 7 and Figure 8 Correction results of the embodiments described are provided according to the reference

[0021] Figure 12 The relationship between the intensity of the irradiation light and the effective voltage of the noise in the rectangular region surrounded by the broken line in Figure 10 and Figure 11 is shown.

[0022] Figure 13 The relationship between the intensity of the irradiation light and the effective voltage of the noise in Embodiment 2 is shown.

[0023] Figure 14 An example of the photoelectric conversion characteristics of a pixel including a photodiode is shown.

[0024] Figure 15 An example of the noise voltage characteristics of a pixel is shown.

[0025] Figure 16 A cross-sectional structure of an OLED panel having a sensor is schematically shown.

[0026] Figure 17 An example of a cross-sectional structure of a photosensor array is schematically shown.

[0027] Figure 18 A cross-sectional structure of an X-ray sensor panel is schematically shown. DETAILED DESCRIPTION

[0028] Hereinafter, an image sensor of the present application will be described in detail with reference to the accompanying drawings. The elements in each drawing have proper variations in size or scale so as to be well recognized in the drawings. The hatching in the drawings is used to distinguish elements, and does not necessarily indicate a cross section. A nonlinear element used as a switching element or an amplifying element is referred to as a transistor. The transistor includes a thin film transistor (TFT).

[0029] In the present specification, the term "light" includes visible light and electromagnetic rays having a shorter or longer wavelength than visible light, unless otherwise specified. For example, light includes infrared rays and ultraviolet rays, which are electromagnetic rays having a shorter wavelength. That is, a photodetector or a photoelectric conversion element is an element that converts electromagnetic rays having a specific wavelength into an electric signal, unless otherwise specified.

[0030] Embodiment 1

[0031] Figure 11 is a block diagram showing a configuration example of an image sensor according to Embodiment 1. An image sensor 10 of the present invention includes a sensor board 11 and a control system. The control system includes a driver circuit 14 , a signal detector circuit 16 , and a main controller 18 .

[0032] The sensor panel 11 includes an insulating substrate (e.g., a glass substrate), a pixel region 12, and an output circuit 15. In the pixel region 12, pixels 13 are arranged horizontally and vertically on the insulating substrate in a matrix-like manner. The pixel region 12 may include a scintillator that emits fluorescence in response to radiation to be detected. A driver circuit 14 drives the pixels 13 so that they detect light. A signal detector circuit 16 detects signals from the respective signal lines of the output circuit 15. A main controller 18 controls the driver circuit 14 and the signal detector circuit 16.

[0033] The driver circuit 14 and the signal detector circuit 16 in this embodiment are manufactured as components separate from the sensor board 11. These circuits may be implemented in different IC chips; part or all of these circuits may be implemented in the same IC chip; or one circuit may be implemented in multiple IC chips.

[0034] The main controller 18 may have a computer configuration. Figure 2 A configuration example of the main controller 18 is schematically shown. Figure 2 The main controller 18 of the configuration example in FIG. 1 includes a processor 201, a memory (primary storage device) 202, an auxiliary storage device 203, an output device 204, an input device 205, a communication interface (I / F) 207, and an AD conversion interface (ADC) 208. These components are connected to each other via a bus. The memory 202, the auxiliary storage device 203, or a combination thereof is a storage device for storing programs and data to be used by the processor 201.

[0035] The memory 202 may be a semiconductor memory and is mainly used to store executed programs and data. The processor 201 performs various processes according to the programs stored in the memory 202 to realize various functional units.

[0036] The secondary storage device 203 may be a mass storage device such as a hard disk drive or a solid-state drive; it is used for long-term storage of programs and data.

[0037] The processor 201 may be one or more processing units and include one or more computing units or multiple processor cores. The processor 201 may be implemented as one or more central processing units, microprocessors, microcomputers, microcontrollers, digital signal processors, state machines, logic circuits, graphics processing units, systems on chips, and / or any device that operates signals according to control instructions.

[0038] Programs and data stored in the auxiliary storage device 203 are loaded into the memory 202 at startup or when necessary, and these programs are executed by the processor 201 to perform various processes of the main controller 18. Therefore, the processes executed according to the programs are processes executed by the processor 201 or the main controller 18.

[0039] Input device 205 is a hardware device used by a user to input instructions and information to main controller 18. Output device 204 is a hardware device used to present input and output images, such as a display device or a printer. A / D conversion interface 208 is an interface for converting input analog signals into digital signals. Communication I / F 207 is an interface for connecting to a network. Input device 205 and output device 204 are optional, and main controller 18 can be accessed from a terminal via a network.

[0040] The functions of the main controller 18 can be implemented in a computer system that includes one or more computers equipped with one or more processors and one or more storage devices including non-transitory storage media. The computers communicate with each other via a network. For example, part of the functions of the main controller 18 can be implemented in one computer, while another part can be implemented in another computer.

[0041] Figure 3 is a circuit diagram showing an example of a circuit configuration of one pixel 13 . Figure 3 What is shown in FIG is an example of a pixel circuit, and other circuit configurations may be adopted. One pixel 13 in the image sensor of the present invention includes four transistors TR1, TR2, TR3, and TR4 and a photodiode PD.

[0042] The photodiode PD is an example of a photodetector (also called a photoelectric conversion element). Figure 3 In the example shown, the anode terminal of the photodiode PD is connected to the gate terminal of the transistor TR1 and the drain terminal of the transistor TR3. The cathode terminal of the photodiode PD is connected to the power supply line PA. The drain terminal of the transistor TR1 is connected to the power supply line PP, and the source terminal of the transistor TR1 is connected to the drain terminal of the transistor TR2.

[0043] The gate terminal of transistor TR2 is connected to control line Gn, and the source terminal of transistor TR2 is connected to signal line Dm. The gate terminal of transistor TR3 is connected to control line Rn, and the source terminal of transistor TR3 is connected to power line PB. The gate terminal of transistor TR4 is connected to bias line BI; the drain terminal of transistor TR4 is connected to signal line Dm; and the source terminal of transistor TR4 is connected to power line VE. The power supply potential of power line VE is lower than the power supply potential of power line PP. Bias line BI supplies a constant bias potential to the gate terminal of transistor TR4.

[0044] The photodiode PD has the function of converting light into electric charge. The transistor TR1 (amplifier transistor) has the function of amplifying the potential of one end of the photodiode PD. The transistor TR2 has the function of controlling the output. The transistor TR3 has the function of resetting the potential of the photodiode PD. The transistor TR4 acts as a resistor. The signal line Dm transmits the photodetection signal Vout of the photodiode PD to the signal detector circuit 16. The driver circuit 14 Figure 3 The control and power lines shown supply control signals and power supply potentials.

[0045] The following describes the processing of the main controller 18. The main controller 18 corrects the measurement signal of light detected by each pixel 13 on the sensor panel 11 to reduce noise therein. The noise included in the measurement signal (output signal) from the pixel 13 is classified into random noise that changes with time and fixed pattern noise (FPN) that does not change with time.

[0046] Fixed pattern noise is further classified into two types of FPN: dark FPN, which is observed when the light imaging element does not receive light, and light FPN, the intensity of which varies depending on the intensity of the incident light. It is known that dark FPN is caused by changes in the input and output characteristics of the pixel circuit and the readout circuit. Light FPN is caused by changes in the characteristics of the photodiode, and its intensity increases as the intensity (number of photons) of the incident light increases. FPN does not change over time, but is spatially fixed as the pixel characteristics change. The processing described below reduces dark FPN and light FPN. In the following description, dark FPN is also called additive FPN, and light FPN is also called multiplicative FPN.

[0047] The embodiments of this specification assume that the measurement signal from the photodiode has the following noise model:

[0048] Sx = So + A*So + Rd (1),

[0049] Where Sx represents the measurement signal of the pixel including noise; Rd represents the measurement signal in the dark state, that is, additive FPN; So represents the real photodetection signal excluding noise; A represents the multiplicative FPN coefficient.

[0050] The main controller 18 corrects the measurement signal Sx received from the pixel 13 by removing additive FPN and multiplicative FPN from the measurement signal Sx to obtain a true photo-detection signal So.

[0051] Before describing the signal processing for reducing noise in the embodiment of this specification, the signal processing for reducing noise in the related art will be described. The related art prepares three types of measurement data: a measurement signal Rd in a dark state, a measurement signal Rl when the sensor device is illuminated with uniform light, and a measurement signal Sx in an actual use state from which the true photodetection signal So is extracted.

[0052] Figure 4 : This is a signal flow chart illustrating a calculation method for noise reduction processing according to the related art. The related art acquires dark-state measurement signals Rd from all pixels 13, then acquires measurement signals Sx to be corrected from a selected pixel 13. The ideal dark state for measurement is a state where light weaker than the detectable limit of the pixel 13 is present, but light weaker than a designed threshold is acceptable.

[0053] Related Art The dark state measurement signal Rd of the selected pixel 13 is subtracted from the measurement signal Sx to obtain a signal S1 (301):

[0054] S1 = Sx – Rd (2).

[0055] This process removes the additive FPN from the measurement signal Sx of the selected pixel 13 .

[0056] The related art also subtracts the measurement signal Rd of the dark state from the measurement signal R1 of the bright state in a state where the sensor device is illuminated with uniform light (reference light) to obtain a signal R1 (302) for each pixel 13:

[0057] R1 = Rl – Rd (3).

[0058] The intensity of the uniform light is within the detectable range of the pixels 13 and is much higher than the intensity of light present in the dark state.

[0059] This process removes additive FPN from the measurement signal R1 under uniform light.

[0060] The correlation technique divides the signal S1 of the selected pixel 13 by the signal R1 of the same pixel (303). The correlation technique also calculates the average value of the signals R1 of all pixels 13. <r1>(304). The related art also removes the multiplicative FPN (305) included in the signal S1 by the following calculation:

[0061] So^ = (S1 / R1)* <r1>(4),

[0062] where So^ represents the estimated value of the true photodetection signal So excluding noise.

[0063] The reason why the related art assumes that S1^ is the true photodetection signal So will be described. According to the above noise model, the following relationship is established:

[0064] S1 = So*(1 + A) (5).

[0065] Similarly, the following relationships are established:

[0066] R1 = Ro*(1 + A) (6),

[0067] Where Ro represents the actual photodetection signal in the measurement signal R1.

[0068] The related art assumes that the average value of the signal R1 of all pixels is <r1>is the true signal value Ro of signal R1:

[0069] Ro = <r1>*(1 +A) (7).

[0070] The related art calculates the multiplicative FPN coefficient A according to formula (7) and assigns it to formula (5) to calculate the estimated value So^ of the true photodetection signal So in the measurement signal Sx.

[0071] Figure 5 and Figure 6 Experimental results of noise reduction of a measurement signal Sx according to the related art are provided. Figure 5 Provides measurement signals (raw data) acquired under conditions of exposure to four types of uniform light with different intensities. Figure 5 In the graph, the horizontal axis represents the pixel position in the row or column direction, and the vertical axis represents the output voltage of the pixel.

[0072] The intensity of the irradiated light of the measurement signals Sa, Sb, Sc and Sd increases in sequence. Signal Sd is the measurement signal when the light intensity is the highest, and signal Sa is the measurement signal when the light intensity is the lowest. Figure 5 As shown, each measurement signal exhibits significant noise.

[0073] Figure 6 The results Soa^, Sob^, Soc^, and Sod^ obtained by using the measurement signal Sa as the reference signal R1 and reducing the noise from the measurement signals Sa, Sb, Sc, and Sd according to equation (4) are provided. As shown in the signal Soa^, the noise in the measurement signal Sa is completely removed. This is because S1 = R1 in equation (4).

[0074] However, the FPN in the measurement signals Sb, Sc, and Sd increases as the illumination level deviates from the illumination level of the measurement signal Sa. Therefore, when the exposure conditions deviate significantly from the reference signal Sa, the processing according to formula (4) cannot completely remove the multiplicative FPN, as shown in the signal Sod^.

[0075] Next, the signal processing used to reduce noise in the measurement signal from the photodiode in an embodiment of the present specification is described. The embodiment of the present specification uses a correction coefficient based on multiple reference signals (measurement signals responsive to such reference light) under reference light of varying intensities to correct the measurement signal. This configuration effectively removes noise from the measurement signal. The wavelength components of the reference light of varying intensities can be the same. The intensity and wavelength components of the reference light can be appropriately determined based on the characteristics of the light to be detected by the image sensor 10.

[0076] The main controller 18 corrects the light measurement signal Sx from one pixel 13 using a correction coefficient based on multiple reference lights of varying intensities. Consequently, the noise component in the measurement signal Sx from the pixel 13 is effectively removed to obtain an estimated true photodetection signal So. As shown in the noise model of equation (1), the measurement signal Sx includes additive FPN and multiplicative FPN.

[0077] The example described below reduces both additive and multiplicative FPN. Coefficients based on multiple intensities of reference light are used to reduce multiplicative noise. If additive FPN is small, the calculations used to reduce additive FPN can be skipped.

[0078] The main controller 18 corrects the measurement signal Sx of each pixel 13 to obtain an estimated value So^ of the true signal:

[0079] So^ = (Sx - Rd)*f (8),

[0080] Here, Rd represents the dark state measurement signal Rd of the pixel 13 and is a correction coefficient for reducing additive FPN; f is a correction coefficient for reducing multiplicative FPN and is determined based on measurement results under a plurality of reference lights with different intensities.

[0081] In an embodiment of the present specification, a correction coefficient for a given pixel is based on a ratio of statistical values ​​obtained from measurement signals of multiple pixels at multiple reference light intensities to a value obtained from the measurement signal of the pixel. In an embodiment of the present specification, the correction coefficient can be expressed as a linear combination of the above ratios and weighting coefficients at multiple reference light intensities.

[0082] In actual use, the main controller 18 has predetermined correction coefficients Rd and f specific to each pixel 13 and uses the correction coefficients Rd and f of each pixel 13 to correct their measurement signals Sx to obtain an estimated value So^ of the actual light detection signal. The main controller 18 may store other coefficients to calculate the coefficient f.

[0083] A method of determining the correction coefficient f will be described. For example, the main controller 18 of the image sensor 10 or a manufacturing apparatus may determine the correction coefficient f. Figure 7 This is a signal flow chart illustrating a calculation method for reducing noise in the embodiment of this specification.

[0084] Figure 7 The flowchart of FIG. 1 shows a method for calculating the correction coefficient f of a selected pixel 13 and a method for correcting the measurement signal Sx of the pixel 13 using the correction coefficient Rd and f. The following description is based on the main controller 18 executing Figure 7 The assumptions in the treatment. Figure 4 The description provided for a reference signal applies to Figure 7 The processing of each reference light intensity in .

[0085] The main controller 18 acquires dark-state measurement signals Rd and measurement signals Rl1 to Rln under first to nth intensities (n is an integer greater than 1) of reference light (uniform light) from all pixels 13. The measurement signals Rd and Rl1 to Rln may be acquired from only some of the pixels 13.

[0086] The main controller 18 subtracts the measurement signal Rd from the measurement signal Rl1 to obtain R1 for each pixel 13 (351):

[0087] R1 = Rl1 – Rd (9).

[0088] This process removes additive FPN from the measurement signal Rl1 when the sensor device 10 is illuminated with uniform light.

[0089] The main controller 18 further calculates the average value of R1 of all pixels 13 <r1>(352). The main controller 18 will average <r1>Divide the signal R1 (353) of the selected pixel 13 by the signal R2 (354) of the pixel 12 adjacent to the selected pixel 13:

[0090] <r1> / R1 (10).

[0091] A statistical value such as a median can be used instead of the average.

[0092] The main controller 18 performs the above-described processing of the signal Rl on the signals R2 to Rn under the other reference light. For example, the main controller 18 performs the processing 354, 355, and 356 on the measurement signal R2, and performs the processing 357, 358, and 359 on the measurement signal Rn.

[0093] Next, the main controller 18 calculates the signals R2 to Rn using the weight coefficients kl to kn that are calculated and stored in advance. <r1> / R1 to <rn>a weighted average of Rn (360), assuming the weight coefficients k1 to kn are normalized and their sum is 1:

[0094] Σkm* <rm>Rm (11),

[0095] where m is each number from 1 to n.

[0096] This weighted average is used as the correction factor f. As will be understood from the present specification, using measurement signals under reference light having different intensities enables more appropriate correction of measurement signals Sx that can employ different intensities. Moreover, assigning weight coefficients to each reference light intensity enables more appropriate correction of measurement signals Sx. Although the values of the weight coefficients depend on the image sensor 10, at least some of the weight coefficients are typically different values.

[0097] The main controller 18 subtracts the dark state measurement signal Rd of the selected pixel 13 from the measurement signal Sx to obtain a signal S1 (365):

[0098] S1 = Sx - Rd (12).

[0099] This process removes additive FPN from the measurement signal Sx to be corrected.

[0100] Next, the main controller 18 multiplies the signal S1 by the coefficient f to calculate an estimate So^ of the true photo-detection signal of the selected pixel 13 (366):

[0101] So^ = S1 * f (13).

[0102] As described above, the embodiments of the present specification obtain a multiplicative noise factor specific to each pixel from a plurality of reference signals under uniform light having different intensities, and correct an unknown measurement signal of each pixel using the factor. Therefore, it is possible to effectively reduce noise over a wide range of illumination intensities.

[0103] Next, a method of determining the weight coefficients k1 to kn is described. The embodiments of the present specification determine the weight coefficients k1 to kn to minimize the effective voltage of the total noise in the signals from all pixels illuminated with uniform reference light. The weight coefficients can be appropriately determined depending on the design of the image sensor 10. The main controller 18 or a manufacturing device of the image sensor 10 can determine the weight coefficients k1 to kn. The following description is based on the assumption that the main controller 18 determines the weight coefficients k1 to kn.

[0104] Figure 8 is a signal flowchart illustrating a method of determining weight coefficients in the embodiments of the present specification. The main controller 18 subtracts the measurement signal Rd from the measurement signal Rl1 to obtain R1 with respect to each pixel 13 (401):

[0105] R1 = Rl1 - Rd (14).

[0106] Next, the main controller 18 calculates the average value of R1 of all pixels 13 <r1>(402). In addition, the main controller 18 subtracts the average value from the signal R1 of each pixel 13 <r1>(403) The main controller 18 calculates the signal R1 for each pixel 13 and the average value <r1>The square of the difference between (R1- <r1>) 2 (404).

[0107] The main controller 18 performs the foregoing processing of signal R1 on other signals R2 to Rn at other reference light intensities. For example, the main controller 18 performs processing 405 to 408 on signal R2 and processing 409 to 412 on signal Rn.

[0108] Next, the main controller 18 uses signals R1 to Rn at all reference light levels from all pixels to calculate a weighted average of the squared deviations from the average (415). More specifically, the main controller 18 calculates (Rm- <rm>) 2 The sum of products (linear combination) of and weight coefficients km, and further the sum of the values ​​obtained from all pixels 13 is calculated:

[0109] ΣΣkm*(Rm- <rm>) 2 (15),

[0110] Wherein m is each of integers 1 to n, and the weight coefficients are normalized.

[0111] In formula (15), the first Σ represents the SUM of all pixels. The second Σ represents the SUM of all n reference light intensities at each pixel 13. The main controller 18 determines the weight coefficients k1 to kn through an optimization loop to minimize the value (416) obtained by formula (15).

[0112] Hereinafter, the effect of the correction of the measurement signal from the pixel 13 in the embodiment of the present specification is described. Figure 9 An example of raw measurement data of pixel 13 before noise removal is provided. Figure 9 In the graph of , the horizontal axis represents the pixel position and the vertical axis represents the output voltage (V) from the pixel 13. Figure 9 Measurement signals R11 to R14 are provided in response to four different intensities of illumination light. The brightness (au) of the light source is 120, 160, 200 and 240.

[0113] This measurement supplies the pixel array with pseudo optical signals generated by optical modulation films, each made of one or two transparent PET films. Figure 9 The prominent peak in indicates that the intensity of light is reduced due to the end face of the film. When the output voltage is low, it means that the illuminance is high.

[0114] Figure 10 Provided according to reference Figure 4 The result of the calibration of the related art is described. The reference light is Rl1 and its intensity is 120. Figure 11 Provided according to the reference Figure 7 and Figure 8 Results of the calibration of the described embodiment: All four intensities of light Rl1 to Rl4 are reference lights used to determine the correction coefficients.

[0115] Figure 12 Shown by Figure 10 The rectangular area 501 enclosed by the dotted line and the Figure 11 The relationship between the intensity of the irradiated light and the effective voltage of the noise in the rectangular area 502 surrounded by the dotted line in FIG. Figure 12 In the graph, the horizontal axis represents the intensity of the reference light, and the vertical axis represents the effective voltage (V) of the noise. A dotted line 511 represents noise corrected according to the related art, and a solid line 512 represents noise corrected according to an embodiment of the present disclosure. As described above, the intensities of the irradiation lights Rl1 to Rl4 are 120, 160, 200, and 240.

[0116] like Figure 12 As shown in FIG. 1 , the correction result according to the related art shows that as the intensity of the irradiation light deviates from the intensity of the reference light Rl1, the effective voltage of the noise increases. On the other hand, the correction result according to the embodiment of the present specification shows that it has a large noise reduction effect in a wide range of irradiation intensity. Figure 12 As can be appreciated, the correction according to this embodiment can effectively reduce noise over a wide range of illumination intensities.

[0117] Implementation Method 2

[0118] The following describes signal processing for reducing noise in the measurement signal from a photodiode in another embodiment of this specification. The noise reduction described below adaptively determines a correction factor for reducing multiplicative FPN based on the intensity of the measurement signal. This configuration effectively reduces noise across a wide range of illumination intensities.

[0119] The main controller 18 in this embodiment corrects the measurement signal Sx from each pixel 13 similarly to the main controller 18 in Embodiment 1 to obtain an estimate of the true signal Sx:

[0120] So^ = (Sx - Rd)*f (16).

[0121] In formula (16), the measurement signal Sx and correction coefficient Rd of additive FPN are the same as those in formula (8) in embodiment 1. In other words, Rd is the measurement signal of each pixel 13 in the dark state. The difference between this embodiment and embodiment 1 lies in the method of obtaining the correction coefficient f of multiplicative FPN. The rest is the same as embodiment 1. The method of obtaining the correction coefficient f is described below.

[0122] As in Embodiment 1, noise reduction in this embodiment uses multiple reference signals acquired in response to multiple reference lights having different intensities to determine correction coefficients. The example described below uses reference signals acquired in response to two uniform reference lights having different intensities. Measurement signals acquired in response to three or more reference lights having different intensities may also be used. As in Embodiment 1, main controller 18 acquires the following signals:

[0123] The measured signal Sx to be corrected for a selected pixel,

[0124] The measurement signal Rl1 of each pixel under reference light 1,

[0125] The measurement signal Rl2 of each pixel under reference light 2, and

[0126] The measured signal Rd of each pixel in the dark state.

[0127] The main controller 18 subtracts the dark state measurement signal Rd of the selected pixel from the measurement signal Sx of the same pixel to obtain a signal S1:

[0128] S1 = Sx - Rd (17).

[0129] This process removes additive FPN from the measurement signal Sx.

[0130] The main controller 18 subtracts the measurement signal Rd from the measurement signal Rl1 to obtain Rl for each pixel 13. This process removes additive FPN from the measurement signal Rl1 under uniform light:

[0131] R1 = Rl1 – Rd (18).

[0132] Furthermore, the main controller 18 subtracts the measurement signal Rd from the measurement signal Rl2 to obtain R2 for each pixel 13. This process removes additive FPN from the measurement signal Rl2 under uniform light:

[0133] R2 = Rl2 – Rd (19).

[0134] The main controller 18 determines the average value of the signal R1 of all pixels 13 <r1>and the average value of the signals R2 of all pixels 13 <r2>As in Embodiment 1, the value to be determined may be an average value of some pixels or another statistical value such as a median. Next, the main controller 18 calculates a weight coefficient that varies according to the signal S1 having an unknown intensity by the following formula. The following formula determines the coefficient by linear interpolation. Assuming <r1>Greater than <r2>, when the unknown signal S1 is equal to <r1>At time t, k1 = KMAX, k2 = KMIN. When the unknown signal S1 is equal to <r2>When k1=KMIN,k2=KMAX. <r1> >S1> <r2>When , k1 and k2 take values ​​between KMAX and KMIN.

[0135] k1=KMIN+(S1- <r2>)*(KMAX-KMIN) / ( <r1> - <r2>),and

[0136] k2 = KMAX- (S1 - <r2>)*(KMAX - KMIN) / ( <r1> - <r2>) (20),

[0137] Where KMAX and KMIN are constants, and KMAX>KMIN.

[0138] The main controller 18 calculates the correction coefficient f for the multiplicative FPN according to the following formula:

[0139] f = (k1* <r1> / R1 + k2* <r2> / R2) / (k1 + k2) (21).

[0140] The main controller 18 multiplies the signal S1 by the correction coefficient f to calculate an estimated value So^ of the true photodetection signal of the selected pixel 13:

[0141] So^ = S1*f (22).

[0142] For the simplest example, when determining <r1>is the highest exposure condition and <r2>KMAX, and 0 to KMIN, k1 and k2 take values between 0 and 1. However, the values of KMAX and KMIN are not limited to 1 and 0. In assigning 1 to KMAX, 0 to KMIN, and determining <r2>is greater than the minimum exposure condition, when S1 is less than <r2>When the value of , k1 can take a negative value.

[0143] The weight coefficients k1 and k2 must be positive values, so in this case, for example, negative values ​​of k1 are avoided by assigning 1 to KMIN and 2 to KMAX. In addition, values ​​optimized to minimize the effective voltage of the total noise can be assigned to KMAX and KMIN.

[0144] In the case of n (three or more) reference signals, Lagrange interpolation can be used to determine n coefficients k1 to kn. An example of n=3 is described. Assume <r3>is the highest exposure condition, <r1>is the lowest exposure condition, the main controller 18 determines the third exposure condition <r2>, so that the condition is satisfied <r3> > <r2> > <r1>, and introduce constants KMAX and KMIN, as well as a third constant KMID that satisfies KMAX>KMID>KMIN. Under these conditions, the weight coefficients k1, k2, and k3 of the signal strength S1 can be determined by the following quadratic Lagrange interpolation:

[0145] k1={(S1-R2)(S1-R3) / (R1-R2) / (R1-R3)}KMAX

[0146] +{(S1-R1)(S1-R3) / (R2-R1) / (R2-R3)}KMID

[0147] +{(S1-R1)(S1-R2) / (R3-R1) / (R3-R2)}KMIN;

[0148] k2={(S1-R2)(S1-R3) / (R1-R2) / (R1-R3)}KMIN

[0149] +{(S1-R1)(S1-R3) / (R2-R1) / (R2-R3)}KMAX

[0150] +{(S1-R1)(S1-R2) / (R3-R1)(R3-R2)}KMIN; and

[0151] k3={(S1-R2)(S1-R3) / (R1-R2) / (R1-R3)}KMIN

[0152] +{(S1-R1)(S1-R3) / (R2-R1) / (R2-R3)}KMID

[0153] +{(S1-R1)(S1-R2) / (R3-R1) / (R3-R2)}KMAX

[0154] The main controller 18 may have <r1> 、 <r2>, R1, R2, Rd, KMAX, and KMIN. The main controller 18 can calculate weight coefficients k1 and k2 based on these values ​​and the measurement signal Sx from the pixel 13, and further calculate the correction coefficient f. As described in Embodiment 1, the main controller 18 can measure the reference light and obtain Rl1 and Rl2 for each pixel 13.

[0155] Figure 13 The relationship between the intensity of the irradiated light and the effective voltage of the noise is shown in FIG. Figure 13 In the graph, the horizontal axis represents the intensity of reference light, and the vertical axis represents the effective voltage (V) of noise. A dashed line 551 represents noise after correction according to the related art; a dashed line 552 represents noise after correction according to Embodiment 1; and a solid line 553 represents noise after correction according to Embodiment 2. In the correction according to Embodiment 2, KMAX is 1.52 and KMIN is 0.25.

[0156] like Figure 13 As shown, compared with the correction result in Embodiment 1, the correction result in Embodiment 2 shows a stable noise reduction effect in a wide range of irradiation intensity.

[0157] Other implementations

[0158] Figure 14 An example of the photoelectric conversion characteristics of a pixel including a photodiode is shown. Figure 15 An example of the noise voltage characteristic of a pixel is shown. Figure 14 As shown in , the output voltage decreases as the incident light intensity increases. Figure 15 As shown in FIG, the noise voltage increases with the increase of the incident light intensity. This means that multiplicative noise exists. As described above, the signal correction method according to the embodiment of the present specification not only effectively removes additive noise, but also removes multiplicative noise.

[0159] Hereinafter, some devices to which the processing of the correction measurement signal in the embodiments of this specification may be applied are described. The correction in the embodiments of this specification may be applied to a device including a plurality of pixels, each pixel including a photoelectric conversion element. The pixel layout may be one-dimensional or two-dimensional.

[0160] Figure 16 The cross-sectional structure of an organic light-emitting diode (OLED) panel with a sensor is schematically shown. The OLED panel with a sensor can detect the fingerprint of a finger 615. The OLED panel with a sensor includes a photosensor array 602 on a laminate film 601 on a substrate. Photosensor array 602 includes multiple PIN diodes 603. Each PIN diode 603 is included in a pixel. The noise reduction processing described in the above embodiment can be applied to the measurement signal of photosensor array 602.

[0161] Another laminate film 605 is bonded to the photosensor array 602 via an optically clear adhesive (OCA) 604. A pinhole array 606, a TFT array 607, and a plurality of light-emitting layers 608 are layered on top of the laminate film 605. Each light-emitting layer 608 is a light-emitting layer of an OLED, and the TFT array 607 controls the light emission of the light-emitting layer 608.

[0162] The light emitting layer 608 is covered by a thin film encapsulation layer 609, and a polarizing plate 610 is provided over the thin film encapsulation layer 609. A cover glass 612 is bonded to the polarizing plate 610 through an OCA 611. A finger 615 is pressed against the surface of the cover glass 612.

[0163] Figure 17 The schematic diagram shows an example of a cross-sectional structure of the photosensor array 602. The substrate SUB corresponds to Figure 16 The laminated film 601 in. Figure 17 Two TFTs and one PIN diode are shown by way of example.

[0164] The undercoat layer UC is provided on the substrate SUB, and the bottom gate electrode BG is provided on the undercoat layer UC. Figure 17 In FIG. 1 , as an example, the bottom gate electrode of one of the two TFTs is provided with a reference symbol BG. The bottom gate electrode BG is covered by the gate insulating layer GI2. The semiconductor layer OX is provided above the gate insulating layer GI2. Figure 17 In the example of , the semiconductor layer OX is made of an oxide semiconductor. The semiconductor material can be selected as desired. Figure 17 , as an example, a semiconductor layer of one of two TFTs is provided with a reference symbol OX.

[0165] Another gate insulating layer GI1 covers the semiconductor layer OX. A metal layer including a top gate electrode TG is provided above the gate insulating layer GI1. Figure 17 , as an example, a top gate electrode of one of the two TFTs is provided with reference symbol TG.

[0166] The metal layer including the top gate electrode TG is covered by the interlayer insulating layer ILD. The metal layer M2 is provided above the interlayer insulating layer ILD. The metal layer M2 includes the source electrode and the drain electrode of the TFT and also includes a contact region extending through the insulating layer ILD or the insulating layer ILD and GI1.

[0167] The metal layer M2 is covered by the passivation layer PV1. Another metal layer M3 is provided above the passivation layer PV1. The metal layer M3 includes wiring and contact areas extending through the insulating passivation layer PV1.

[0168] The metal layer M3 is covered by the planarization layer PLN. A further metal layer M4 is provided above the planarization layer PLN. The metal layer M4 comprises the lower electrode of the PIN diode and also comprises a contact region extending through the insulating planarization layer PLN.

[0169] A portion of metal layer 4 is covered by a passivation layer PV2 and another passivation layer PV3 above passivation layer PV2. A multilayer semiconductor film PIN is disposed above the lower electrode of metal layer M4 within a hole formed through passivation layers PV2 and PV3. This multilayer semiconductor film comprises a p-type semiconductor layer, an n-type semiconductor layer, and an intrinsic semiconductor layer.

[0170] An upper ITO electrode is disposed above the multilayer semiconductor film PIN. The upper ITO electrode is transmissive to the light to be detected. A common electrode COM is connected to the upper ITO electrode of the PIN diode. The common electrode COM is connected to all PIN diodes. A topmost passivation layer PV4 covers the upper ITO electrode and the common electrode COM.

[0171] Figure 18 The schematic diagram shows a cross-sectional structure of an X-ray sensor panel. The X-ray sensor panel can be used in radiographic imaging equipment in the medical and industrial nondestructive testing fields. The X-ray sensor panel includes a photosensor array 652 on a glass substrate 651. The photosensor array 652 includes multiple PIN diodes 653. Each PIN diode 653 is included in a pixel. The noise reduction processing described in the above embodiments can be applied to the measurement signal from the photosensor array 652.

[0172] The photosensor array 652 is covered with a protective insulating film 654. An X-ray conversion film (scintillator) 655 is provided above the protective insulating film 654. The X-ray conversion film 655 converts received X-rays 671 into visible light 672 detectable by the PIN diode 653. Each pixel of the photosensor array 652 measures the intensity of the visible light converted by the X-ray conversion film 655.

[0173] As described above, the embodiments of the present invention have been described; however, the present invention is not limited to the aforementioned embodiments. Those skilled in the art can easily modify, add, or convert each element of the aforementioned embodiments within the scope of the present invention. A portion of the configuration of one embodiment can be replaced with the configuration of another embodiment, or the configuration of one embodiment can be incorporated into the configuration of another embodiment. < / r1> < / r2> < / r3> < / r1> < / r1> < / r1> < / rm> < / rm> < / rm> < / rn>

Claims

1. A sensor device comprising: Multiple pixels; as well as a controller configured to correct the measurement signals of the plurality of pixels, Each of the plurality of pixels comprises: a photodetector; and a pixel circuit configured to output a signal from the photodetector, and wherein the controller is configured to: acquiring an unknown measurement signal from one of the plurality of pixels; and The unknown measurement signal of the one pixel is corrected using a correction coefficient based on a ratio between a value obtained from the measurement signal of the one pixel under a plurality of reference lights having different intensities and a statistical value obtained from values ​​obtained from the measurement signals of the plurality of pixels under a plurality of reference lights having different intensities.

2. The sensor device according to claim 1, wherein The correction coefficient is given by a linear combination of ratios between a value obtained from the measurement signal of the one pixel under the plurality of reference lights having different intensities and statistical values ​​acquired from values ​​obtained from the measurement signals of the plurality of pixels under the plurality of reference lights having different intensities.

3. The sensor device according to claim 1, wherein Each of the statistical values ​​acquired from the measurement signals of the plurality of pixels is an average value of values ​​each obtained by subtracting a measurement signal of a pixel in a dark state from the measurement signal of the pixel.

4. The sensor device according to claim 1, wherein The controller is configured to determine the correction coefficient based on statistical values ​​acquired from measurement signals of the plurality of pixels under the plurality of reference lights having different intensities and a value obtained from the measurement signal of the one pixel under the plurality of reference lights having different intensities.

5. The sensor device according to claim 4, in, When determining the correction coefficient, the controller is configured to: calculating statistical values ​​of the plurality of pixels based on values ​​obtained after subtracting signals measured in a dark state from signals measured under the plurality of reference lights having different intensities; obtaining a first difference by subtracting a signal of the one pixel measured in a dark state from signals of the one pixel measured under the plurality of reference lights having different intensities; as well as calculating a linear combination of a quotient obtained by dividing a statistical value by a first difference value of each of the plurality of reference lights and a weight coefficient of each of the plurality of reference lights, and Wherein, when correcting the unknown measurement signal of the one pixel, the controller is configured to: calculating a second difference by subtracting the signal of the one pixel measured in a dark state from the unknown measurement signal of the one pixel; and The product of the second difference and the linear combination is calculated.

6. The sensor device according to claim 5, wherein The controller is configured to determine each of the weight coefficients of the plurality of reference lights based on a statistical value of each of the plurality of reference lights having different intensities and the unknown measurement signal of the one pixel.

7. The sensor device according to claim 1, wherein The controller is configured to determine the correction coefficient based on the ratio under the plurality of reference lights having different intensities and the unknown measurement signal of the one pixel.

8. The sensor device according to claim 1, wherein The correction coefficient f is expressed by the following formula: f=Σkm* <rm> / Rm,< / rm> Wherein, m represents an identifier of the plurality of reference lights having different intensities; km represents a weight assigned to the reference light m; and Rm represents a value obtained from the measurement signal of the one pixel under the reference light m. <rm> represents statistical values ​​of the plurality of pixels under the reference light m.< / rm> 9. The sensor device according to claim 8, in, The value So^ obtained by correcting the unknown measurement signal is expressed by the following formula: So^=(Sx-Rd)*f, Wherein, Sx represents the unknown measurement signal, Rd represents the measurement signal of the one pixel in the dark state, The value Rm obtained from the measurement signal of the one pixel under the reference light m is expressed by the following formula: Rm=Rlm–Rd, Wherein, Rlm represents the measurement signal of the one pixel under the reference light m, and Among them, the statistical value under the reference light m <rm> is an average value of the values ​​of the plurality of pixels obtained after subtracting the measurement signal in the dark state from the measurement signal of each pixel under the reference light m.< / rm> 10. A method for determining correction coefficients to be used by a controller of a sensor device when correcting measurement signals of a plurality of pixels of the sensor device, Each pixel of the plurality of pixels includes a photodetector and a pixel circuit configured to output a signal from the photodetector, and The method comprises: acquiring measurement signals from the plurality of pixels under a plurality of reference lights having different intensities; determining a statistical value of measurement signals of the plurality of pixels under each of the plurality of reference lights; as well as A correction coefficient for each pixel is determined based on statistical values ​​of the measurement signals of the plurality of pixels and a measurement signal of each pixel under each of the plurality of reference lights.

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