Spectroscopic apparatus, Raman spectroscopy measuring apparatus, and spectroscopic method

Abstract

A spectroscopic device 5 is for receiving light L1 that has undergone wavelength-decomposition in a predetermined direction by a spectroscopic optical system 4 including a spectroscopic element, and outputting spectroscopic spectral data of the light L1. The spectroscopic device 5 comprises: a CMOS image sensor that has a pixel unit 11 which has a plurality of pixels 21 for receiving the wavelength-decomposed light L1 and converting the same into an electrical signal, and in which the plurality of pixels 21 are arranged in a row direction along a wavelength decomposition direction and in a column direction perpendicular to the row direction; an identification unit 14 that identifies, as specific pixels 21K among the plurality of pixels 21, pixels 21 on which a spectroscopic spectral image 31 of the light L1 is formed; and a generation unit 15 that adds up the pixel values of the specific pixels 21K belonging to the same column, and that generates spectroscopic spectral data based on the result of the adding.

Description

[Technical Field]

[0001] This disclosure relates to a spectroscopic apparatus, a Raman spectroscopy apparatus, and a spectroscopic method. [Background technology]

[0002] A conventional spectrometer is, for example, the spectrometer described in Patent Document 1. This conventional spectrometer is a so-called Raman spectrometer. The spectrometer comprises means for irradiating excitation light in a line, a movable stage on which a sample is placed, an objective lens for focusing Raman light from the excitation light irradiation area, a slit provided at the imaging position of the Raman light, a spectrometer for dispersing the light passing through the slit, a CCD detector for detecting the Raman spectral image, and a control device for controlling mapping measurement by synchronizing the movable stage and the CCD detector. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2016-180732 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] In fields of spectroscopic measurement such as Raman spectroscopy, fluorescence spectroscopy, and plasma spectroscopy, vertical binning of CCD image sensors is used to acquire spectral data in order to improve the signal-to-noise ratio (SNR). Vertical binning in a CCD image sensor involves adding up the charges generated at each pixel over multiple stages. In a CCD image sensor, readout noise is generated only in the final stage amplifier and does not increase during the vertical binning process. Therefore, the more stages of vertical binning are increased, the better the signal-to-noise ratio of the signal can be improved.

[0005] As image sensors, in addition to CCDs, CMOS image sensors are also known. However, at present, the spread of CMOS image sensors in the field of spectroscopic measurement has not advanced. In a CMOS image sensor, an amplifier is arranged for each pixel, and the charge is converted into a voltage for each pixel. When performing vertical binning with a conventional CMOS image sensor, as the number of stages of vertical binning increases, the read noise is also integrated, resulting in a problem that the signal-to-noise ratio is lower than when using a CCD image sensor.

[0006] The present disclosure has been made to solve the above problems, and an object thereof is to provide a spectroscopic apparatus, a Raman spectroscopic measurement apparatus, and a spectroscopic method capable of acquiring spectroscopic spectral data with an excellent signal-to-noise ratio.

Means for Solving the Problems

[0007] The gist of the spectroscopic apparatus, Raman spectroscopic measurement apparatus, and spectroscopic method according to one aspect of the present disclosure is as follows [1] to

[14] .

[0008] [1] A spectroscopic apparatus that receives light wavelength-dispersed in a predetermined direction by a spectroscopic optical system including a spectroscopic element and acquires spectroscopic spectral data of the light, the spectroscopic apparatus having a plurality of pixels that receive the wavelength-dispersed light and convert it into an electrical signal, the plurality of pixels having a pixel portion arranged in a row direction along the wavelength-dispersion direction and a column direction perpendicular to the row direction, a CMOS image sensor, a specifying unit that specifies pixels in which a spectroscopic spectral image of the light is formed among the plurality of pixels as specific pixels, and an integrating unit that integrates pixel values of the specific pixels belonging to the same column and generates spectroscopic spectral data based on the integration result.

[0009] This spectrometer identifies specific pixels in which the spectral image of wavelength-resolved light is formed, and generates spectral data by integrating the pixel values ​​of specific pixels belonging to the same column. By excluding other pixels in which the spectral image is not formed from the integration of pixel values, the influence of readout noise during pixel value integration can be sufficiently reduced. Therefore, this spectrometer can acquire spectral data with an excellent signal-to-noise ratio.

[0010] [2] The spectroscopic apparatus according to [1], wherein the specific unit excludes pixels whose readout noise exceeds a threshold from the specific pixels. This further reduces the influence of readout noise when integrating pixel values. Therefore, the signal-to-noise ratio of the spectral data can be further improved.

[0011] [3] The threshold for the readout noise is 0.1[e - rms] above 1.0[e - A spectrometer as described in [1] or [2], set to a threshold value of less than or equal to [rms]. By setting such a threshold, the influence of readout noise when integrating pixel values ​​can be further reduced. Therefore, the signal-to-noise ratio of the spectral data can be further improved.

[0012] [4] The spectroscopic apparatus according to any one of [1] to [3], wherein the identifying unit identifies pixels as the identifying pixels, the pixels whose imaging area of ​​the spectral image is 50% or more of the area of ​​the light-receiving surface. In this case, by excluding pixels that make little contribution to the acquisition of the spectral image from the identifying pixels, the influence of readout noise when integrating pixel values ​​can be reduced even more sufficiently. Therefore, the signal-to-noise ratio of the spectral data can be further improved.

[0013] [5] A spectroscopic apparatus according to any one of [1] to [3], wherein the identifying unit identifies the integration ratio of the specific pixel based on the aberration information of the light, and the generating unit integrates the pixel values ​​of the specific pixel using the integration ratio. With such a configuration, even if distortion due to aberration occurs in the wavelength-resolved spectral image of the light, it is possible to obtain spectral data with a good signal-to-noise ratio.

[0014] [6] The spectroscopic apparatus according to any one of [1] to [5], wherein the pixel section comprises a first pixel region and a second pixel region divided in the column direction, a first reading unit for reading each pixel belonging to the first pixel region, and a second reading unit for reading each pixel belonging to the second pixel region. In this case, the first pixel region and the second image region can be used separately depending on the characteristics of the spectral image. Therefore, spectral data of various types of light can be acquired with a good signal-to-noise ratio.

[0015] [7] The spectroscopic apparatus described in [6], wherein the first exposure time for each pixel belonging to the first pixel region is shorter than the second exposure time for each pixel belonging to the second pixel region. With this configuration, for example, spectral images of light with different intensities depending on the wavelength can be obtained in the first pixel region and the second pixel region with different exposure times. By combining the saturation wavelength band of spectral data obtained with a short exposure time in the first pixel region and the unsaturation wavelength band of spectral data obtained with a long exposure time in the second pixel region, spectral data with a good signal-to-noise ratio can be obtained with a high dynamic range.

[0016] [8] The spectroscopic apparatus according to [7], wherein multiple frames of image data are acquired in the first pixel region during the period in which one frame of image data is acquired in the second pixel region. In this case, even if different exposure times are set in the first pixel region and the second pixel region, the readout noise of specific pixels in each column can be made equal between the first pixel region and the second pixel region. Therefore, the signal-to-noise ratio of the spectral data can be stably improved.

[0017] [9] The spectroscopic apparatus according to [6], wherein the saturation charge of each pixel belonging to the first pixel region and the saturation charge of each pixel belonging to the second pixel region are different from each other. In this case, it is possible to acquire spectral data with a good signal-to-noise ratio and a high dynamic range while keeping the exposure time of each pixel belonging to the first pixel region and the exposure time of each pixel belonging to the second pixel region equal.

[0018]

[10] The pixel portion has a mask that makes the light-receiving area of ​​the first pixel region equal to the light-receiving area of ​​the second pixel region. [9] Spectroscopic apparatus as described above. If it is desired to increase the difference between the saturation charge amount of the first pixel region and the saturation charge amount of the second pixel region in order to expand the dynamic range, it is conceivable that the size difference between the light-receiving area of ​​the first pixel region and the light-receiving area of ​​the second pixel region will increase due to the configuration of the image sensor. In contrast, by using a mask that makes the area of ​​the light-receiving area of ​​the first pixel region equal to the area of ​​the light-receiving area of ​​the second pixel region, the amount of light received per unit time of both can be made equal. This makes it possible to acquire spectral data with a good signal-to-noise ratio in a higher dynamic range while keeping the exposure time of each pixel belonging to the first pixel region and the exposure time of each pixel belonging to the second pixel region equal.

[0019]

[11] A spectroscopic apparatus according to any one of [1] to

[10] , further comprising an analysis unit for analyzing the spectral data. In this case, the spectroscopic apparatus is equipped with a function for analyzing spectral data, thereby improving convenience.

[0020]

[12] A spectroscopic apparatus according to any one of [1] to

[11] , further comprising the spectroscopic optical system including the spectroscopic element. In this case, the spectroscopic apparatus is equipped with a wavelength resolution function for light, thereby improving convenience.

[0021] A Raman spectrometer comprising one of the spectrometers described in

[13] [1] to

[12] , a light source unit that generates light to be irradiated onto a sample, and a light guide optical system that guides the Raman scattered light generated by the irradiation of the sample with the light to the spectrometer.

[0022] This Raman spectrometer identifies specific pixels in which the spectral image of wavelength-resolved Raman scattered light is formed, and generates spectral data by integrating the pixel values ​​of specific pixels belonging to the same column. By excluding other pixels in which the spectral image is not formed from the integration of pixel values, the influence of readout noise from each pixel during the integration of pixel values ​​can be sufficiently reduced. Therefore, this Raman spectrometer can acquire spectral data of Raman scattered light with an excellent signal-to-noise ratio.

[0023]

[14] A spectroscopic method for receiving wavelength-decomposed light in a predetermined direction and acquiring spectral data of the light, comprising: a light receiving step using a CMOS image sensor, receiving the wavelength-decomposed light with a plurality of pixels arranged in a row direction along the wavelength-decomposition direction and a column direction perpendicular to the row direction and converting it into an electrical signal; a identification step for identifying a pixel from the plurality of pixels on which a spectral image of the light is formed as a specific pixel; and a generation step for integrating the pixel values ​​of the specific pixels belonging to the same column and generating spectral data based on the integration result.

[0024] In this spectroscopic method, pixels that form a spectral image of wavelength-resolved light are identified as specific pixels, and spectral data is generated by integrating the pixel values ​​of specific pixels belonging to the same column. By excluding other pixels that do not form a spectral image from the integration of pixel values, the influence of readout noise from each pixel during the integration of pixel values ​​can be sufficiently reduced. Therefore, spectral data can be obtained with an excellent signal-to-noise ratio using this spectroscopic method. [Effects of the Invention]

[0025] According to this disclosure, spectral data can be obtained with an excellent signal-to-noise ratio. [Brief explanation of the drawing]

[0026] [Figure 1] This is a block diagram showing the configuration of a Raman spectrometer according to one embodiment of the present disclosure. [Figure 2] This figure shows an example of the structure of an imaging sensor. [Figure 3] This is a schematic diagram showing the relationship between the exposure time of each pixel belonging to the first imaging region and the exposure time of each pixel belonging to the second imaging region. [Figure 4] This is a schematic diagram showing an example of a specific pixel map. [Figure 5] This is a schematic diagram showing the details of a specific pixel map. [Figure 6] This is a schematic diagram showing the details of the readout noise map. [Figure 7] This flowchart shows a spectroscopic method according to one embodiment of the present disclosure. [Figure 8] (a) is a schematic diagram showing an example of a spectral image with aberrations, and (b) is a schematic diagram showing an example of spectral data obtained based on the spectral image shown in (a). [Figure 9] This is a schematic diagram showing an example of an accumulation ratio map. [Figure 10] This is a schematic graph showing spectral data obtained by vertical binning using an integrated ratio map. [Figure 11] (a) to (c) are schematic graphs showing how spectral data is generated in modified examples. [Figure 12] This is a schematic diagram showing a modified pixel section. [Modes for carrying out the invention]

[0027] Hereinafter, with reference to the drawings, preferred embodiments of a spectroscopic apparatus, a Raman spectroscopy apparatus, and a spectroscopic method relating to one aspect of this disclosure will be described in detail.

[0028] Figure 1 is a block diagram showing the configuration of a Raman spectrometer according to one embodiment of the present disclosure. The Raman spectrometer 1 is a device for measuring the physical properties of a sample S using Raman scattered light Lr. In the Raman spectrometer 1, light L1 from the light source 2 is irradiated onto the sample S, and the Raman scattered light Lr generated by the interaction between the light L1 and the sample S is detected by the spectrometer 5 to acquire spectral data of the Raman scattered light Lr. By analyzing the spectral data acquired by the spectrometer 5 with the computer 6, various physical properties of the sample S, such as molecular structure, crystallinity, orientation, and strain, can be evaluated. Examples of samples S include semiconductor materials, polymers, cells, and pharmaceuticals.

[0029] As shown in Figure 1, the Raman spectroscopy apparatus 1 comprises a light source unit 2, a light guide optical system 3, a spectroscopic optical system 4, a spectrometer 5, a computer 6, and a display unit 7. For convenience, in the following description, the light incident on the spectrometer 5 via the spectroscopic optical system 4 may be referred to as light L1 to distinguish it from Raman scattered light Lr. In the spectrometer 5 incorporated into the Raman spectroscopy apparatus 1, light L1 refers to Raman scattered light Lr.

[0030] The light source unit 2 is the part that generates the light L0 that is irradiated onto the sample S. As the light source constituting the light source unit 2, for example, a laser light source or light-emitting diode can be used as an excitation light source for Raman spectroscopy. The light guide optical system 3 is the part that guides the Raman scattered light Lr generated by the irradiation of the sample S with light L0 to the spectrometer 5. The light guide optical system 3 is configured with, for example, a collimating lens, one or more mirrors, a slit, and the like.

[0031] The spectroscopic optical system 4 is the part that wavelength-resolves the light L1 in a predetermined direction. The spectroscopic optical system 4 is composed of a spectroscopic element that spectrally separates the light L1 in a predetermined wavelength-resolving direction. As the spectroscopic element, for example, a prism, diffraction grating, concave diffraction grating, crystal spectroscopic element can be used. The Raman scattered light Lr is spectrally separated by the spectroscopic optical system 4 and input to the spectrometer 5.

[0032] In Figure 1, the spectroscopic optical system 4 is configured separately from the spectrometer 5, but the spectroscopic optical system 4 may be incorporated as a component of the spectrometer 5. That is, the spectrometer 5 may further include a spectroscopic optical system 4 that includes a spectroscopic element that spectrally separates light L1 in the wavelength-resolved direction. In this case, the wavelength-resolved function of light L1 in the spectrometer 5 improves convenience. The spectrometer 5 is the part that receives light L1 that has been wavelength-resolved in a predetermined direction and outputs spectral data of the light L1. In this embodiment, the spectrometer 5 receives Raman scattered light Lr that has been spectrally separated in a predetermined wavelength-resolved direction by the spectroscopic optical system 4 and outputs spectral data of the Raman scattered light Lr to the computer 6.

[0033] Computer 6 physically includes memory devices such as RAM and ROM, a processor (arithmetic circuit) such as a CPU, and a communication interface. For example, a personal computer, a cloud server, or a smart device (smartphone, tablet terminal, etc.) can be used as Computer 6. Computer 6 is connected to the light source unit 2 and the spectrometer 5 of the Raman spectroscopy measuring apparatus 1 so as to be able to communicate with each other and comprehensively control these components. Computer 6 also functions as an analysis unit 8 that analyzes the physical properties of the sample S based on the spectral data received from the spectrometer 5 (generation unit 15). Computer 6 outputs information showing the analysis results from the analysis unit 8 to the display unit 7.

[0034] As shown in Figure 1, the spectrometer 5 comprises a pixel unit 11, a conversion unit 12, a readout unit 13, a identification unit 14, and a generation unit 15. The pixel unit 11, the conversion unit 12, and the readout unit 13 are composed of an imaging sensor 10. An example of an imaging sensor 10 is a CMOS (Complementary Metal Oxide Semiconductor) image sensor.

[0035] In this embodiment, the spectrometer 5 is configured as a camera equipped with an imaging sensor 10, a specific unit 14, and a generation unit 15. Here, the spectrometer 5 is separate from the computer 6, but the spectrometer 5 may be configured as an integrated unit including a camera equipped with an imaging sensor 10, a specific unit 14, and a generation unit 15, and a computer 6 (analysis unit 8) that is electrically or wirelessly connected to the camera for mutual information communication. In this case, the spectrometer 5 is equipped with a function for analyzing spectral data, improving convenience.

[0036] Figure 2 shows the structure of the image sensor. As shown in the figure, in the pixel section 11 of the image sensor 10, multiple pixels 21 are arranged in the row direction and in the column direction perpendicular to the row direction. Here, the row direction is aligned with the wavelength resolution direction of light L1 or Raman scattered light Lr from the spectroscopic optical system 4, and the column direction is aligned with the vertical binning direction, which will be described later. In Figure 2, for the sake of explanation, a 6x7 pixel arrangement 21 is shown as an example, but in the actual pixel section 11, n rows x m columns of pixels 21 are arranged.

[0037] Each pixel 21 is a portion that captures a spectral image of light L1 or Raman scattered light Lr, which is imaged by the spectroscopic optical system 4. Each pixel 21 has a photodiode 22 and an amplifier 23. The photodiode 22 stores electrons (photoelectrons) generated by the input of light L1 as electric charge. The amplifier 23 converts the charge stored in the photodiode 22 into an electrical signal (for example, a signal indicating a voltage value) and amplifies it.

[0038] The electrical signal amplified by the amplifier 23 is transferred to the vertical signal lines 25 connecting the pixels 21 in the row direction by switching the selection switch 24 of each pixel 21. A CDS (correlated double sampling) circuit 26 is placed on each of the vertical signal lines 25. The CDS circuit 26 reduces readout noise between each pixel 21 and temporarily stores the electrical signal transferred to the vertical signal lines 25.

[0039] The conversion unit 12 is the part that converts the voltage values ​​output from each of the amplifiers 23 of the multiple pixels 21 into digital values. In this embodiment, the conversion unit 12 is composed of an A / D converter 27. The A / D converter 27 converts the voltage values ​​stored in the CDS circuit 26 into digital values. The converted digital values ​​(pixel values) are output to the generation unit 15 via the reading unit 13. When outputting the pixel values ​​to the generation unit 15, the reading unit 13 outputs instruction information to the identification unit 14 instructing it to start processing.

[0040] In this embodiment, as shown in Figure 2, the pixel unit 11 has a first pixel region 21A and a second pixel region 21B divided in the column direction, a first reading unit 13A that reads each pixel 21 belonging to the first pixel region 21A, and a second reading unit 13B that reads each pixel 21 belonging to the second pixel region 21B. In the example in Figure 2, the first pixel region 21A and the second pixel region 21B are divided in the center in the column direction. That is, pixels 21 on one side of the center in the column direction belong to the first pixel region 21A, and pixels 21 on the other side of the center in the column direction belong to the second pixel region 21B.

[0041] The first reading unit 13A and the second reading unit 13B are arranged independently of each other. The first reading unit 13A is connected to an A / D converter 27 corresponding to the vertical signal line 25 of each pixel 21 belonging to the first pixel area 21A. The first reading unit 13A outputs the pixel value of each pixel 21 belonging to the first pixel area 21A to the generation unit 15. The second reading unit 13B is connected to an A / D converter 27 corresponding to the vertical signal line 25 of each pixel 21 belonging to the second pixel area 21B. The second reading unit 13B outputs the pixel value of each pixel 21 belonging to the second pixel area 21B to the generation unit 15.

[0042] In this embodiment, the first exposure time T1 of each pixel 21 belonging to the first pixel region 21A and the second exposure time T2 of each pixel 21 belonging to the second pixel region 21B are different from each other. More specifically, as shown in Figure 3, the first exposure time T1 of each pixel 21 belonging to the first pixel region 21A is shorter than the second exposure time T2 of each pixel 21 belonging to the second pixel region 21B. Therefore, during the period in which one frame of image data is acquired in the second pixel region 21B, multiple frames of image data are acquired in the first pixel region 21A. The generation unit 15 integrates the pixel values ​​corresponding to the multiple frames of image data in the first pixel region 21A and generates image data based on the integrated pixel values. In the example in Figure 3, the second exposure time T2 is an integer multiple of the first exposure time T1.

[0043] The identification unit 14 and the generation unit 15 are physically composed of a computer system equipped with a storage device such as RAM or ROM, a processor (arithmetic circuit) such as a CPU, a communication interface, etc. The identification unit 14 and the generation unit 15 may be composed of a PLC (programmable logic controller) or an FPGA (field-programmable gate array).

[0044] The identification unit 14 is the part that identifies the pixel 21 from among the multiple pixels 21 in which the spectral image of light L1 is formed as the specific pixel 21K. When the identification unit 14 receives instruction information from the reading unit 13, it generates specific information indicating the specific pixel 21K and outputs it to the generation unit 15. The identification unit 14 may also hold a specific pixel map M1 for the pixel unit 11 as specific information. The specific pixel map M1 can be acquired in advance, for example, by simulation data or measured data when light L1 or Raman scattered light Lr is guided to the spectroscopic optical system 4.

[0045] FIG. 4 is a schematic diagram showing an example of a specific pixel map. In the example of FIG. 4, for a horizontally long pixel portion 11 where the number of pixels in the row direction is larger than the number of pixels in the column direction, five wavelength - decomposed spectral images 31 (31A to 31E from the short - wavelength side) are imaged. The spectral images 31A to 31E all linearly extend in the column direction of the pixels 21 and are imaged on the pixel portion 11 while being spaced apart from each other in the row direction.

[0046] For such a spectral image 31, in the specific pixel map M1, for example, pixels 21 where the imaging area of the spectral image 31 is 50% or more of the area of the light - receiving surface are specified as specific pixels 21K. In FIG. 5, three rows × three columns of arbitrary pixels 21 in the specific pixel map M1 are exemplified, and the ratio of the imaging area of the spectral image 31 to the area of the light - receiving surface 21a of each pixel 21 is shown.

[0047] In the example of FIG. 5, for the three pixels 21 at the coordinates (x n , y m+1 ), (x n , y m ), and (x n , y m-1 ) located in the center, the imaging areas of the spectral image 31 are all 100% of the area of the light - receiving surface 21a. For the three pixels 21 at the coordinates (x n-1 , y m+1 ), (x n-1 , y m ), and (x n-1 , y m-1 ) located on the left side, the imaging areas of the spectral image 31 are 15%, 40%, and 65% respectively. For the three pixels 21 at the coordinates (x n+1 , y m+1 ), (x n+1 , y m ), and (x n+1 , y m-1 ) located on the right side, the imaging areas of the spectral image 31 are 15%, 40%, and 65% respectively. Among these pixels 21, for the coordinates (x n , y m+1 ), (x n , y m ), and (x n,y m-1 ), coordinates (x n-1 ,y m-1 ), coordinates (x n+1 ,y m-1 The five pixels 21 of ) become candidates for the specific pixel 21K.

[0048] The identification unit 14 excludes pixels 21Fa whose readout noise exceeds a threshold from the identified pixels 21K. The identification unit 14 may also maintain a readout noise map M2 for the pixel unit 11. The readout noise map M2 is created, for example, by measuring the readout noise of each pixel 21 of the pixel unit 11 before incorporating the imaging sensor 10 into the spectrometer 5. In this embodiment, the readout noise map M2 is superimposed and integrated with the identified pixel map M1 (see Figure 4).

[0049] In the readout noise map M2, the readout noise threshold is 0.1[e - rms] above 1.0[e - It is set to a range of less than or equal to rms. The specific unit 14 determines that the read noise is 0.1[e based on the read noise map M2. - Pixels 21Fa exceeding [rms] are excluded from the candidates for specific pixels 21K. In this embodiment, the readout noise threshold is 1.0[e - It is set to rms. The readout noise threshold is 0.5[e - It may also be set to rms, and 0.3[e - It may be set to rms. The readout noise threshold is 0.1[e - rms] 0.3[e - It may be set to a range of less than or equal to rms. In this case, the readout noise threshold is 0.2[e - It may be set to [rms].

[0050] Figure 6 illustrates the 3x3 pixel 21 shown in Figure 5, and shows the readout noise values ​​for each pixel 21. In the example in Figure 6, the coordinate (x n-1 ,y m Readout noise and coordinate (x) of pixel 21 of ) n+1 ,y m-1The readout noise of pixel 21 of ) is 1.4[e - rms], 1.1[e - The readout noise threshold is 1.0[e - When set to [rms], these two pixels 21 become pixels 21Fa where the readout noise value exceeds the threshold. Coordinate (x n+1 ,y m-1 Pixel 21 of ) is a candidate for specific pixel 21K in the example of Figure 5, but since it is pixel 21Fa whose readout noise exceeds the threshold, it is excluded from the list of candidates for specific pixel 21K. Therefore, in the range of pixel 21 shown in Figures 5 and 6, the coordinate (x n ,y m+1 ), coordinates (x n ,y m ), coordinates (x n ,y m-1 ), coordinates (x n-1 ,y m-1 The four pixels 21 of ) are ultimately identified as specific pixels 21K.

[0051] The identification unit 14 may pre-store area information indicating areas in the pixel unit 11 where there is no input of light L1 or Raman scattered light Lr, and exclude pixels 21 corresponding to the area information from the candidates for the identification pixel 21K. The area information is generated in advance, for example, based on the specifications or arrangement of the spectroscopic elements in the spectroscopic optical system 4. The area information may be superimposed on the identification pixel map M1. In the example in Figure 4, pixels 21 located at both ends of each row belong to area R where there is no input of light L1. Pixels 21Fb belonging to area R are excluded from the candidates for the identification pixel 21K.

[0052] The generation unit 15 is the part that integrates the pixel values ​​of specific pixels 21K belonging to the same column and generates spectral data based on the integration result. The integration of the pixel values ​​of multiple specific pixels 21K belonging to the same column is a process equivalent to so-called vertical binning. The spectral data may be a two-dimensional image representing the pixel value of each specific pixel 21K, or it may be a histogram plotting the pixel values. The generation unit 15 outputs the generated spectral data to the computer 6 (analysis unit 8).

[0053] In this embodiment, as described above, the pixel section 11 is divided into a first pixel region 21A and a second pixel region 21B. Furthermore, the first exposure time T1 of each pixel 21 belonging to the first pixel region 21A is shorter than the second exposure time T2 of each pixel 21 belonging to the second pixel region 21B (see Figures 2 and 3). The generation unit 15 generates first spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same row in the first pixel region 21A, and second spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same row in the second pixel region 21B.

[0054] The first spectral data was acquired in the first pixel region 21A with a relatively short first exposure time T1, and for example, all wavelength bands are below the saturation level. The second spectral data was acquired in the second pixel region 21B with a relatively long second exposure time T2, and for example, some wavelength bands are above the saturation level.

[0055] The generation unit 15 divides the wavelength band of the entire spectrum into a saturation wavelength band and a non-saturation wavelength band for the second spectral data. In the saturation wavelength band, the second spectral data is above the saturation level, and the first spectral data is below the saturation level. In the non-saturation wavelength band, the second spectral data is below the saturation level and has a better signal-to-noise ratio than the first spectral data. The generation unit 15 combines the first spectral data in the saturation wavelength band and the second spectral data in the non-saturation wavelength band to generate spectral data to be output to the computer 6.

[0056] Figure 7 is a flowchart showing a spectroscopic method according to one embodiment of the present disclosure. This spectroscopic method involves receiving wavelength-resolved light in a predetermined direction and acquiring spectral data of the light. The spectroscopic method according to this embodiment is carried out using the spectroscopic apparatus 5 described above. As shown in Figure 7, this spectroscopic method comprises a light receiving step (step S01), a identification step (step S02), a generation step (step S03), and an analysis step (step S4).

[0057] In the light receiving step S01, the imaging sensor 10 (CMOS image sensor) is used to receive wavelength-decomposed light L1 or Raman scattered light Lr with multiple pixels 21 arranged in rows along the wavelength resolution direction and in columns perpendicular to the row direction, and convert them into electrical signals. In this embodiment, the light L1 or Raman scattered light Lr is received in the first pixel region 21A and the second pixel region 21B with different exposure periods. The pixel values ​​of each pixel 21 belonging to the first pixel region 21A and the pixel values ​​of each pixel 21 belonging to the second pixel region 21B are then output to the generation unit 15.

[0058] In the identification step S02, among the multiple pixels 21, the pixel 21 on which the spectral image 31 of light L1 or Raman scattered light Lr is imaged is identified as the specific pixel 21K. In this embodiment, the identification unit 14 has a specific pixel map M1 in advance and identifies the pixel 21K on which the imaging area of ​​the spectral image 31 is 50% or more of the area of ​​the light-receiving surface 21a. In this embodiment, the readout noise is a threshold of 1.0[e - Pixels 21Fa exceeding [rms] are excluded from the specified pixel 21K.

[0059] In generation step S03, the pixel values ​​of specific pixels 21K belonging to the same column are integrated, and spectral data based on the integration result is generated. In this embodiment, the generation unit 15 generates first spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same column in the first pixel region 21A, and second spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same column in the second pixel region 21B. Then, the first spectral data in the saturated wavelength band and the second spectral data in the unsaturated wavelength band are combined to generate spectral data to be output to the computer 6.

[0060] In analysis step S04, the sample S is analyzed based on the spectral data generated in generation step S03. For example, the waveform, peak position, and full width at half maximum of the spectral data are analyzed to evaluate various physical properties of the sample S, such as molecular structure, crystallinity, orientation, and strain.

[0061] As explained above, the spectrometer 5 identifies the pixel 21 that forms the spectral image 31 of the wavelength-resolved light L1 as a specific pixel 21K, and generates spectral data by integrating the pixel values ​​of the specific pixel 21K belonging to the same column. By excluding other pixels 21 that do not form the spectral image 31 from the integration of pixel values, the influence of readout noise when integrating pixel values ​​can be sufficiently reduced. Therefore, the spectrometer 5 can acquire spectral data with an excellent signal-to-noise ratio.

[0062] In the spectrometer 5, pixels 21Fa whose readout noise exceeds a threshold are excluded from the specific pixels 21K. The readout noise threshold is 0.1[e - rms] above 1.0[e - It is set to a range of less than or equal to [rms]. This further reduces the influence of readout noise when integrating pixel values. Therefore, the signal-to-noise ratio of the spectral data can be further improved.

[0063] In the spectrometer 5, pixels 21 whose imaging area of ​​the spectral image 31 is 50% or more of the area of ​​the light-receiving surface 21a are identified as specific pixels 21K. By excluding pixels 21 that contribute little to the acquisition of the spectral image 31 from the specific pixels 21K, the influence of readout noise when integrating pixel values ​​can be further reduced. Therefore, the signal-to-noise ratio of the spectral data can be further improved.

[0064] In the spectrometer 5, the pixel unit 11 has a first pixel region 21A and a second pixel region 21B divided in the column direction, a first reading unit 13A that reads each pixel 21 belonging to the first pixel region 21A, and a second reading unit 13B that reads each pixel 21 belonging to the second pixel region 21B. With this configuration, the first pixel region 21A and the second pixel region 21B can be used separately depending on the characteristics of the spectral image. Therefore, spectral data of various types of light can be acquired with a good signal-to-noise ratio.

[0065] In the spectrometer 5, the first exposure time T1 for each pixel 21 belonging to the first pixel region 21A is shorter than the second exposure time T2 for each pixel 21 belonging to the second pixel region 21B. With this configuration, for example, a spectral image 31 of light L1 with different intensity depending on the wavelength can be obtained in the first pixel region 21A and the second pixel region 21B with different exposure times. In this embodiment, the saturation wavelength band of the spectral data obtained with a relatively short first exposure time T1 in the first pixel region 21A and the unsaturated wavelength band of the spectral data obtained with a relatively long second exposure time T2 in the second pixel region 21B are combined to generate the final spectral data. This makes it possible to obtain spectral data with a good signal-to-noise ratio with a high dynamic range.

[0066] In the spectrometer 5, the second exposure time T2 is longer than the first exposure time T1, so that multiple frames of image data are acquired in the first pixel region 21A during the period in which one frame of image data is acquired in the second pixel region 21B. As a result, even if different exposure times are set in the first pixel region 21A and the second pixel region 21B, the readout noise of specific pixels 21K in each column can be matched between the first pixel region 21A and the second pixel region 21B. Therefore, the signal-to-noise ratio of the spectral data can be stably improved.

[0067] In the Raman spectroscopy measurement device 1, which incorporates the spectroscopic device 5 described above, the pixel 21 on which the spectral image 31 of wavelength-resolved Raman scattered light Lr is imaged is identified as a specific pixel 21K, and spectral data is generated by integrating the pixel values ​​of the specific pixel 21K belonging to the same column. By excluding other pixels 21 on which the spectral image 31 is not imaged from the integration of pixel values, the influence of readout noise when integrating pixel values ​​can be sufficiently reduced. Therefore, the Raman spectroscopy measurement device 1 can acquire spectral data with an excellent signal-to-noise ratio.

[0068] This disclosure is not limited to the embodiments described above, and various modifications can be applied. As described above, the spectroscopic optical system 4 is configured to include a spectroscopic element that spectrally separates light L1 or Raman scattered light Lr in the wavelength resolution direction. However, the spectral image actually formed on the pixel section 11 via the spectroscopic optical system 4 may not be linear due to the influence of optical system aberrations, as is the case with Czernitus-Turner type spectroscopy, for example.

[0069] For example, in the example shown in Figure 8(a), the spectral image 31C located in the center of the pixel 11 is linear in the column direction (vertical binning direction), but spectral images 31A, 31B and spectral images 31D, 31E all exhibit pincushion-type distortion, where the image curves toward the center of the pixel 11. The amount of distortion in spectral image 31 increases with distance from the center of the pixel 11. The amount of distortion in spectral images 31A and 31E is greater than the amount of distortion in spectral images 31B and 31D.

[0070] If vertical binning of the pixel values ​​of specific pixels 21K in each column is performed with such distortion, as shown in Figure 8(b), the wavelength resolution in the row direction may decrease depending on the degree of distortion in the spectral data 32A to 32E based on spectral images 31A to 31E, excluding spectral image 31C, specifically in the spectral data 32A, 32B, 32D, and 32E based on spectral images 31A, 31B, 31D, and 31E. Furthermore, a decrease in the peak value of spectral data 32A, 32B, 32D, and 32E may result in a decrease in the signal-to-noise ratio.

[0071] To address such problems, the identification unit 14 may identify the integration ratio of specific pixels 21K used for pixel count integration based on the aberration information of light L1 or Raman scattered light Lr in the spectroscopic optical system 4, and the generation unit 15 may integrate the pixel values ​​of specific pixels 21K using the integration ratio. Specifically, the identification unit 14 may have an integration ratio map M3 for the pixel unit 11, as shown in Figure 9. In the example in Figure 9, the integration ratio map M3 is superimposed on and integrated with the specific pixel map M1. The aberration information used to generate the integration ratio map M3 can be obtained in advance from simulation data or measured data when light L1 or Raman scattered light Lr is guided into the spectroscopic optical system 4. When using measured data, aberration information can be obtained based on the spectral data of multiple light images, assuming there is no local distortion.

[0072] The specific unit 14 may refer to the integration ratio map M3 and perform sub-pixel processing based on the integration ratio of multiple specific pixels 21K adjacent in the row direction during vertical binning of pixel values. Figure 9 shows extracted integration ratios of some specific pixels 21K corresponding to spectral images 31B and 31E from the overall integration ratio map M of the pixel unit 11. As described above, the distortion of spectral image 31E is greater than the distortion of spectral image 31B. Therefore, in the example in Figure 9, during vertical binning of the pixel values ​​of specific pixels 21K corresponding to spectral image 31B, sub-pixel processing is performed based on the integration ratio of two specific pixels 21K adjacent in the row direction. Also, during vertical binning of pixels 21 corresponding to spectral image 31E, sub-pixel processing is performed based on the integration ratio of three specific pixels 21K adjacent in the row direction.

[0073] In the example in Figure 9, the pixel value of a specific pixel 21K with coordinates (x,y) is denoted as P(x,y). If the x-coordinate reference for the specific pixel 21K corresponding to spectral image 31B is 300 and the y-coordinate is -512 to +512, then the vertical binning of the pixel value of the specific pixel 21K corresponding to spectral image 31B is given by the following equation (1). If the x-coordinate reference for the specific pixel 21K corresponding to spectral image 31E is 700 and the y-coordinate is -512 to +512, then the vertical binning of the pixel value of the specific pixel 21K corresponding to spectral image 31E is given by the following equation (2).

number

number

[0074] Figure 9 shows four pixels, coordinates (300,-500), (301,-500), (300,-501), and (301,-501), as part of the specific pixel 21K corresponding to the spectral image 31B. For these four pixels, the integration ratio of P(300,-500) is 80%, the integration ratio of P(301,-500) is 20%, the integration ratio of P(300,-501) is 90%, and the integration ratio of P(301,-501) is 10%. Therefore, in equation (1), α(300,-500) is obtained by equation (3) below, and α(300,-501) is obtained by equation (4) below. α(300,-500)=(80×P(300,-500)+20×P(301,-500)) / 100…(3) α(300,-501)=(90×P(300,-501)+10×P(301,-501)) / 100…(4)

[0075] Furthermore, Figure 9 shows nine pixels as part of the specific pixels 21K corresponding to the spectral image 31E: coordinates (699,350), (700,350), (701,350), (699,349), (700,349), (701,349), (699,348), (700,348), and (701,348). For these nine pixels, the integration ratios are as follows: P(699,350) is 15%, P(700,350) is 70%, P(701,350) is 15%, P(699,349) is 20%, P(700,349) is 70%, P(701,349) is 10%, P(699,348) is 25%, P(700,348) is 70%, and P(701,348) is 5%.

[0076] Therefore, in equation (2), β(700,350) can be found using equation (5) below, and β(700,349) can be found using equation (6) below. Also, β(700,348) can be found using equation (7) below. β(700,350)=(15×P(699,350)+70×P(700,350)+15×P(701,350))…(5) β(700,349)=(20×P(699,349)+70×P(700,349)+10×P(701,349))…(6) β(700,348)=(25×P(699,348)+70×P(700,348)+5×P(701,348))…(7)

[0077] Figure 10 is a schematic graph showing spectral data obtained by vertical binning using an integration ratio map. As shown in the figure, by integrating the number of pixels of a specific pixel 21K using an integration ratio based on the aberration information of light L1 or Raman scattered light Lr, even if distortion occurs in the spectral images 31A to 31E, the decrease in wavelength resolution in the row direction can be suppressed in each of the spectral data 32A to 32E based on the spectral images 31A to 31E. Furthermore, the decrease in peak value is also suppressed, and the signal-to-noise ratio is improved.

[0078] In the example shown in Figure 9, only the integration ratio map M3 is displayed, but the readout noise map M2 described above may be superimposed on the integration ratio map M3. Area information may also be further superimposed on the integration ratio map M3. In this case, the generation unit 15 excludes the pixels 21 identified by the readout noise map M2 and area information from the specified pixels 21K, and then performs vertical binning by subpixel processing using the integration ratio map M3.

[0079] In the above embodiment, the first exposure time T1 of each pixel 21 belonging to the first pixel region 21A is shorter than the second exposure time T2 of each pixel 21 belonging to the second pixel region 21B. However, a common exposure time may be set for both the first pixel region 21A and the second pixel region 21B. When a common exposure time is set, the saturation charge amount of each pixel 21 belonging to the first pixel region 21A and the saturation charge amount of each pixel 21 belonging to the second pixel region 21B may be different in the pixel section 11.

[0080] For example, if the saturation charge amount of each pixel 21 belonging to the first pixel region 21A is made relatively small, the readout noise of these pixels 21 will also be made relatively small. The first spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same row in the first pixel region 21A will have a good signal-to-noise ratio overall, as shown in Figure 11(a), but the wavelength band with an intensity above a certain level will be the saturation wavelength band.

[0081] On the other hand, if the saturation charge amount of each pixel 21 belonging to the second pixel region 21B is made relatively large, the readout noise of these pixels 21 also becomes relatively large. The second spectral data obtained by integrating the pixel values ​​of specific pixels 21K belonging to the same row in the second pixel region 21B, as shown in Figure 11(b), has an entire spectrum in the unsaturated wavelength band, but the signal-to-noise ratio decreases in the wavelength band where the intensity is below a predetermined level.

[0082] In this case, the generation unit 15 divides the wavelength band of the entire spectrum into a saturation wavelength band and a non-saturation wavelength band of the first spectral data. The generation unit 15 combines the first spectral data of the non-saturation wavelength band and the second spectral data of the saturation wavelength band to generate spectral data to be output to the computer 6, as shown in Figure 11(c). With this configuration, it is possible to acquire spectral data with a good signal-to-noise ratio and a high dynamic range while keeping the first exposure time T1 of each pixel 21 belonging to the first pixel region 21A and the second exposure time T2 of each pixel 21 belonging to the second pixel region 21B equal.

[0083] In order to expand the dynamic range, if it is desired to increase the difference between the saturation charge amount of the first pixel area 21A and the saturation charge amount of the second pixel area 21B, then, given the configuration of the imaging sensor 10, it is conceivable that the size difference between the light-receiving area of ​​the first pixel area 21A and the light-receiving area of ​​the second pixel area 21B will increase. In this case, as shown in Figure 12, a mask 41 may be provided in the pixel section 11 to make the area of ​​the light-receiving area V1 of the first pixel area 21A equal to the area of ​​the light-receiving area V2 of the second pixel area 21B.

[0084] This arrangement of the mask 41 makes it possible to equalize the amount of light received per unit time for both. As a result, it becomes possible to acquire spectral data with a good signal-to-noise ratio and a higher dynamic range while keeping the exposure time T1 of each pixel 21 belonging to the first pixel region 21A and the exposure time T2 of each pixel 21 belonging to the second pixel region 21B equal.

[0085] As another variation, the pixel area 11 does not necessarily have to be divided into a first pixel area 21A and a second pixel area 21B, but may consist of a single pixel area. The spectrometer 5 is not limited to application to the Raman spectroscopy measuring device 1, but may also be applied to other spectroscopic measuring devices such as fluorescence spectroscopy measuring devices, plasma spectroscopy measuring devices, and emission spectroscopy measuring devices. Furthermore, the spectrometer 5 may also be applied to other spectroscopic measuring devices such as film thickness measuring devices, optical density measuring devices, LIBS (Laser-Induced Breakdown Spectroscopy) measuring devices, and DOAS (Differential Optical Absorption Spectroscopy) measuring devices. [Explanation of symbols]

[0086] 1...Raman spectroscopy measuring device, 2...Light source unit, 3...Light guide optical system, 4...Spectroscopic optical system, 5...Spectrometer, 8...Analysis unit, 10...Imaging sensor (CMOS image sensor), 11...Pixel unit, 13A...First readout unit, 13B...Second readout unit, 14...Specification unit, 15...Generation unit, 21...Pixel, 21a...Light receiving surface, 21A...First pixel area, 21B...Second pixel area, 21K...Specific pixel, 31 (31A~31E)...Spectroscopic spectral image, 41...Mask, L1...Light, Lr...Raman scattered light, T1...First exposure time, T2...Second exposure time, V1...Light receiving area of ​​the first pixel area, V2...Light receiving area of ​​the second pixel area.

Claims

1. A spectroscopic device that receives wavelength-resolved light in a predetermined direction by a spectroscopic optical system including a spectroscopic element, and acquires spectral data of said light, The system has multiple pixels that receive the wavelength-decomposed light and convert it into an electrical signal. A CMOS image sensor having a pixel section in which the plurality of pixels are arranged in a row direction along the wavelength resolution direction and in a column direction perpendicular to the row direction, A selection unit that identifies a specific pixel among the plurality of pixels in which the spectral image of the light is formed, The system comprises a generation unit that integrates the pixel values ​​of specific pixels belonging to the same column and generates spectral data based on the integration result, The specified unit identifies the integration ratio of the specified pixel based on the aberration information of the light, The generation unit is a spectroscopic device that integrates the pixel values ​​of the specific pixels using the integration ratio.

2. The spectroscopic apparatus according to claim 1, wherein the specified unit excludes pixels whose readout noise exceeds a threshold from the specified pixels.

3. The threshold for the readout noise is 0.1 [e － rms] 1.0 [e － The spectroscopic apparatus according to claim 2, wherein the range set is less than or equal to [rms].

4. The spectroscopic apparatus according to claim 1, wherein the specifying unit specifies a pixel as the specified pixel whose imaging area of ​​the spectral image is 50% or more of the area of ​​the light-receiving surface.

5. A spectroscopic device that receives wavelength-resolved light in a predetermined direction by a spectroscopic optical system including a spectroscopic element, and acquires spectral data of said light, The system has multiple pixels that receive the wavelength-decomposed light and convert it into an electrical signal. A CMOS image sensor having a pixel section in which the plurality of pixels are arranged in a row direction along the wavelength resolution direction and in a column direction perpendicular to the row direction, A selection unit that identifies a specific pixel among the plurality of pixels in which the spectral image of the light is formed, The system comprises a generation unit that integrates the pixel values ​​of specific pixels belonging to the same column and generates spectral data based on the integration result, The aforementioned pixel portion is The first pixel region and the second pixel region are divided in the column direction, A first reading unit reads each pixel belonging to the first pixel region, It includes a second reading unit that reads out each pixel belonging to the second pixel region, A spectrometer in which the saturation charge amount of each pixel belonging to the first pixel region and the saturation charge amount of each pixel belonging to the second pixel region are different from each other.

6. The spectroscopic apparatus according to claim 5, wherein the specified unit excludes pixels whose readout noise exceeds a threshold from the specified pixels.

7. The threshold for the readout noise is 0.1 [e － rms] 1.0 [e － The spectroscopic apparatus according to claim 6, set to a range of less than or equal to [rms].

8. The spectroscopic apparatus according to claim 5, wherein the specifying unit identifies a pixel as the specified pixel whose imaging area of ​​the spectral image is 50% or more of the area of ​​the light-receiving surface.

9. The spectroscopic apparatus according to claim 5, wherein the first exposure time for each pixel belonging to the first pixel region is shorter than the second exposure time for each pixel belonging to the second pixel region.

10. The spectroscopic apparatus according to claim 9, wherein, during the period in which one frame of image data is acquired in the second pixel region, a plurality of frames of image data are acquired in the first pixel region.

11. The spectroscopic apparatus according to claim 5, wherein the pixel portion has a mask that makes the area of ​​the light-receiving area of ​​the first pixel region equal to the area of ​​the light-receiving area of ​​the second pixel region.

12. The spectroscopic apparatus according to any one of claims 1 to 11, further comprising an analysis unit for analyzing the aforementioned spectral data.

13. The spectroscopic apparatus according to any one of claims 1 to 11, further comprising the spectroscopic optical system including the spectroscopic element.

14. A spectroscopic apparatus according to any one of claims 1 to 11, A light source unit that generates light to irradiate the sample, A Raman spectrometer comprising: a light guide optical system for guiding Raman scattered light generated by the irradiation of the sample with the light to the spectrometer.

15. A spectroscopic method for receiving wavelength-decomposed light in a predetermined direction and acquiring spectral data of said light, A CMOS image sensor is used to receive the wavelength-decomposed light with a plurality of pixels arranged in a row direction along the wavelength-decomposition direction and in a column direction perpendicular to the row direction, and convert it into an electrical signal; A selection step of identifying a specific pixel from among multiple pixels in which the spectral image of the light is formed, The system includes a generation step of integrating the pixel values ​​of specific pixels belonging to the same column and generating spectral data based on the integration result, In the aforementioned specific step, the integration ratio of the specific pixel is determined based on the aberration information of the light, The generation step involves a spectroscopic method that integrates the pixel values ​​of the specific pixels using the integration ratio.

16. A spectroscopic method for receiving wavelength-decomposed light in a predetermined direction and acquiring spectral data of the light, A CMOS image sensor is used to receive the wavelength-decomposed light with a plurality of pixels arranged in a row direction along the wavelength-decomposition direction and in a column direction perpendicular to the row direction, and convert it into an electrical signal; A selection step of identifying a specific pixel from among multiple pixels in which the spectral image of the light is formed, The system includes a generation step of integrating the pixel values ​​of specific pixels belonging to the same column and generating spectral data based on the integration result, In the aforementioned light receiving step, A spectroscopic method using a CMOS image sensor having a pixel portion comprising a first pixel region and a second pixel region divided in the column direction, a first reading unit for reading each pixel belonging to the first pixel region, and a second reading unit for reading each pixel belonging to the second pixel region, wherein the saturation charge amount of each pixel belonging to the first pixel region and the saturation charge amount of each pixel belonging to the second pixel region are different from each other.

Images