JP6756288B2 - Image processing system, multi-band filter, and imaging device - Google Patents

Description

The present invention relates to an image processing system, a multi-band filter, and an imaging device.

Image processing using a color measurement technique using a multi-band filter composed of a plurality of filters has already been used in the field of imaging devices because it can capture the features of an object with high accuracy. In the color measurement technique using this multi-band filter, studies have been made on the arrangement of the filters in order to improve the color measurement accuracy.

For example, Patent Document 1 discloses the contents regarding the wavelength range of the transmission spectrum and the position of the peak wavelength for six filters provided at equal intervals in the visible light wavelength region.

However, in the color measurement technique using a multi-band filter, if the transmission spectrum shifts due to the influence of manufacturing variation, the influence of the shift increases as the number of filters increases, and as a result, the color measurement accuracy is not stable. Patent Document 1 does not consider the influence of manufacturing variation, and it is clear how to specifically set the filter to reduce the influence of manufacturing variation while maintaining the color measurement accuracy. It wasn't.

The image processing system according to the present invention includes a plurality of filters and a signal processing unit that generates a color signal based on the transmission spectrum of the filter, and the plurality of filters are based on the XYZ color matching function. The transmission spectrum of the filter belonging to the second filter group, which includes a filter belonging to the first filter group and a filter belonging to a second filter group different from the first filter group, is the first filter group. This is an image processing system in which the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the filter group is shifted in the wavelength direction.

According to the present invention, the influence of manufacturing variation can be reduced while maintaining the color measurement accuracy.

It is a figure which shows an example of the basic structure of the image processing system which concerns on one Embodiment of this invention. It is a figure which shows another example of the basic structure of the image processing system which concerns on one Embodiment of this invention. It is a figure which shows an example of the hardware structure of the image processing system which concerns on one Embodiment of this invention. It is a figure which shows an example of the functional structure of the image processing system which concerns on one Embodiment of this invention. It is a figure which shows an example of the cross section of the image pickup mechanism which mounted the multi-band filter which concerns on one Embodiment of this invention. It is a figure which shows an example of the arrangement of the multi-band filter and the image pickup device which concerns on one Embodiment of this invention. It is a graph which shows the XYZ color matching function defined by the XYZ colorimeter by the International Commission on Illumination (CIE). It is a graph which shows an example of the transmission spectrum of the multi-band filter which concerns on one Embodiment of this invention. It is a flowchart which shows an example of information processing of the image processing system which concerns on one Embodiment of this invention. It is a figure which shows an example of the level setting of the multi-band assigned to the L18 orthogonal array. It is a graph which shows an example of the result of approximating the first filter constituting the multi-band filter shown in FIG. 8 with a Gaussian distribution. It is a graph which shows an example of the result of simulating the degree of agreement with the Z color matching function by making the standard deviation σ variable. It is a graph which shows an example of the result of simulating the degree of agreement with the Z color matching function by making the peak wavelength μ variable. It is a graph which shows an example of the relationship between the arrangement of a filter in the multi-band filter which concerns on one Embodiment of this invention, and each parameter. It is a graph which shows an example of the result of simulating the degree of agreement with the Z color matching function by making the standard deviation σ variable. It is a graph which shows an example of the result of simulating the degree of agreement with the Z color matching function by making the peak wavelength μ variable. It is a graph which shows an example of the relationship between the arrangement of a filter in the multi-band filter which concerns on one Embodiment of this invention, and each parameter. It is a graph which shows another example of the relationship between the arrangement of a filter and each parameter in the multi-band filter which concerns on one Embodiment of this invention. It is a graph which shows an example of the calculation method of the diagonal component of the correction matrix L.

Hereinafter, modes for carrying out the invention will be described with reference to the drawings.

● Image processing system ●
● Overall Configuration FIG. 1 is a diagram showing an example of a basic configuration of an image processing system according to an embodiment of the present invention. The image processing system 100 includes an image processing unit 300, a filter setting unit 400, and a multi-band filter 500. The figure shows that the image pickup apparatus 110 includes an image pickup mechanism 200, an image processing unit 300, and a filter setting unit 400. Further, the figure shows that the image pickup mechanism 200 includes a lens 210, an image pickup element 220, and a multi-band filter 500. In this way, the image processing system 100 constitutes a part of the image pickup apparatus 110. The image pickup device 110 is a digital still camera, a digital video camera, a scanner, a colorimeter, or the like.

The image pickup mechanism 200 is attached to a lens 210, an image pickup element 220 that photoelectrically converts an image of a subject imaged by the lens 210 and outputs an image signal, and a plurality of light receiving units arranged in two dimensions of the image pickup element 220. Further, it has a multi-band filter 500 that transmits light in a specific wavelength band. The image signal output from the image sensor 220 is subjected to predetermined processing by the image processing unit 300.

The light receiving unit of the image sensor 220 photoelectrically converts the light transmitted through the multi-band filter 500 attached to each of them, and outputs a signal corresponding to the intensity thereof. The image pickup device 220 is configured as, for example, a CCD (Charge-Coupled Device) or a CMOS (Complementary metal oxide semiconductor). The image sensor 220 is arranged on the light emitting side of the multi-band filter 500.

The multi-band filter 500 is a filter corresponding to tristimulus values of colors having spectral transmittance based on a color matching function of the XYZ color system (hereinafter referred to as XYZ color matching function). That is, the multi-band filter 500 is composed of a plurality of filters having different spectral transmittances based on the XYZ color matching function. A description of the XYZ color matching function will be described later.

The image processing unit 300 processes the image signal output from the image pickup mechanism 200. The filter setting unit 400 sets the multi-band filter 500. The functions of the image processing unit 300 and the filter setting unit 400 will be described later.

FIG. 2 is a diagram showing another example of the basic configuration of the image processing system according to the embodiment of the present invention. The difference from FIG. 1 is that the filter setting unit 400 is composed of an external device 120 provided outside the image pickup device 110. For example, in the image processing system 100 shown in FIG. 2, the multi-band filter 500 included in the image pickup mechanism 200 is set by the external device 120 constituting the filter setting unit 400 at the time of shipment of the image pickup device 110.

The external device 120 is, for example, a management device used at the time of manufacturing or maintenance of the image pickup device 110, and is composed of a PC (Personal Computer), a tablet terminal, a smartphone, a server, and the like. Therefore, the image pickup apparatus 110 in FIG. 2 may have a configuration including an image pickup mechanism 200 and an image processing unit 300.

● Hardware Configuration of Image Processing System FIG. 3 is a diagram showing an example of a hardware configuration of an image processing system according to an embodiment of the present invention. The image processing system 100 in FIG. 3 is provided inside the image pickup device 110 as shown in FIG. 1, but the image processing system according to the embodiment of the present invention includes the image pickup device 110 as shown in FIG. It may be composed of an external device 120. The external device 120 has a general computer configuration, and has a configuration obtained by removing the configuration of the imaging mechanism 200 from the hardware configuration of the imaging device 110 of FIG. The external device 120 may have the same hardware configuration as the image pickup device 110.

The image pickup device 110 includes an image pickup mechanism 200, an image processing unit 310, an image pickup control unit 410, a CPU (Central Processing Unit) 601 and a ROM (Read Only Memory) 602, a RAM (Random Access Memory) 603, a storage 604, and a display unit 605. It is composed of a communication unit 606, an input / output I / F (Interface) 607, a bus 608, and the like.

The image pickup mechanism 200 is connected to the image processing unit 310 and the image pickup control unit 410.

The image processing unit 310 takes in the image signal output from the image sensor 220 and performs image processing. The image pickup control unit 410 performs an image pickup process on an object in the image pickup mechanism 200 and a setting process of the multi-band filter 500. The image pickup control unit 410 corresponds to the filter setting unit 400 shown in FIG.

The image processing unit 310 and the image pickup control unit 410 are connected to the CPU 601 via the bus 608. The image processing unit 310 and the imaging control unit 410 are programmable devices (PD) such as FPGAs (Field Programmable Gate Arrays) and ASICs that implement some or all of the functions realized by the image processing unit 310 and the imaging control unit 410. (Application Specific Integrated Circuit) may be configured.

The CPU 601 is an arithmetic unit that realizes each function of the image processing system 100 by reading a program or data stored in a ROM 602, a storage 604, or the like on a RAM 603 and executing processing.

The ROM 602 is a non-volatile memory that can hold programs and data even when the power is turned off. The RAM 603 is a volatile memory used as a work area or the like of the CPU 601. The storage 604 is composed of, for example, a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a flash ROM. The storage 604 stores an OS (Operation System), an application program, various data, and the like.

The display unit 605 displays, for example, data related to processing executed by the image processing system 100.

The communication unit 606 is a wireless communication function for performing wireless LAN (Local Area Network) communication such as, for example, IEEE802.11a / b / g / n / ac, and is, for example, an antenna, a wireless unit, and a MAC (Media Access). Control) part etc. are included. The input / output I / F 607 inputs / outputs information to / from a network such as a communication unit 606, a recording device such as a ROM 602 or a storage 604, or an input / output device such as a mouse, a keyboard, a button, or a display unit 605.

The bus 608 is connected to each of the above components and transmits an address signal, a data signal, various control signals, and the like. The CPU 601, ROM 602, RAM 603, storage 604, display unit 605, communication unit 606, and input / output I / F 607 are connected to each other via the bus 608.

The hardware configuration of the image processing system 100 shown in FIG. 3 is an example of a configuration for realizing the function according to the embodiment of the present invention, and is not limited thereto.

● Functional Configuration of Image Processing System FIG. 4 is a diagram showing an example of the functional configuration of an image processing system according to an embodiment of the present invention. As shown in FIG. 4, the functions realized by the image processing system 100 are the signal acquisition means 611, the signal processing means 612, the filter setting control means 621, the storage control means 622, the test pattern acquisition means 623, and the filter correction means 624. Including the functions to be realized. The signal acquisition means 611 and the signal processing means 612 are means corresponding to the image processing unit 300 shown in FIG. 1, and the filter setting control means 621, the storage control means 622, the test pattern acquisition means 623, and the filter correction means 624 are shown in FIG. This is a means corresponding to the filter setting unit 400 shown in 1.

The signal acquisition means 611 is a means for acquiring a spectrum signal which is an image signal output from the image sensor 220. The signal acquisition means 611 is realized by, for example, a program executed by the CPU 601 or the image processing unit 310 in FIG.

The signal processing means 612 is a means for generating a color signal based on the spectral signal acquired by the signal acquisition means 611. The signal processing means 612 is realized by, for example, a program executed by the CPU 601 or the image processing unit 310 in FIG. The signal processing means 612 performs white balance processing, noise removal, color interpolation processing, color matrix processing, and the like on the acquired spectrum signal. The signal processing means 612 is an example of a signal processing unit.

The filter setting control means 621 sets the multi-band filter 500. The filter setting control means 621 is realized by, for example, a program executed by the CPU 601 in FIG. 3 or the image pickup control unit 410. The filter setting control means 621 sets a filter for transmitting light in a specific wavelength band among the light images of the subject imaged by the lens 210. The light transmitted through the multi-band filter 500 having the filter set by the filter setting control means 621 is received by the light receiving unit of the image sensor 220.

The memory control means 622 uses the reference spectrum of the XYZ color matching function, the reference information of the tristimulus values set by the International Commission on Illumination (CIE), and the filter information set by the filter setting control means 621 in the ROM 602 of FIG. It is a means to store in the storage 604. The storage control means 622 is realized by, for example, a program executed by the RAM 603 and the storage 604 of FIG. 3 and the CPU 601 of FIG.

The test pattern acquisition means 623 is a means for acquiring spectral information of the test pattern imaged by the imaging mechanism 200. The test pattern acquisition means 623 is realized, for example, by a program executed by the CPU 601 or the imaging control unit 410 in FIG. Here, the test pattern is, for example, a standard RGB image. The test pattern acquisition means 623 acquires the spectrum information of the standard RGB image captured by the imaging mechanism 200.

The filter correction means 624 is a means for correcting each filter of the multi-band filter 500 based on the spectrum information of the test pattern acquired by the test pattern acquisition means 623 and the reference spectrum of the XYZ color matching function stored in advance. is there. The filter correction means 624 is realized, for example, by a program executed by the CPU 601 or the imaging control unit 410 in FIG.

The filter correction means 624 calculates the tristimulus value of the color of the test pattern from the spectrum information of the test pattern acquired by the test pattern acquisition means 623. The color tristimulus value of the test pattern is an integral value of the acquired spectral information multiplied by the XYZ color matching function.

The filter correction means 624 calculates the correction value of each filter based on the calculated color tristimulus value of the test pattern and the color tristimulus value as reference information. Thereby, the image processing system 100 can quantitatively measure, for example, how close the color information obtained through the image pickup apparatus 110 is to that seen by the human eye. The color tristimulus value as the reference information is the tristimulus value determined by the International Commission on Illumination (CIE) shown in FIG. The color tristimulus values as reference information are stored in advance in the ROM 602 and the storage 604 of FIG.

The filter correction means 624 corrects each filter based on the calculated correction value. The specific filter correction process will be described later.

● Multi-band filter ●
FIG. 5 is a diagram showing an example of a cross section of an imaging mechanism on which a multi-band filter according to an embodiment of the present invention is mounted. The imaging mechanism 200 shown in FIG. 5 includes a light receiving unit 221, a substrate layer 222, a wiring layer 223, an insulating layer 224, a multi-band filter 500, a moisture-proof layer 225, and a lens 210.

The multi-band filter 500 has a structure in which a low refractive index dielectric material of silicon oxide (SiO2) and a high refractive index dielectric material of titanium oxide (TiO2) are alternately laminated, and the cavity layer is sandwiched between mirror layers. I am doing. Here, the mirror layer has an optical film thickness nd = λ / 4, where n is the refractive index of the dielectric material, d is the physical film thickness of the dielectric material, and λ is the reference wavelength of the transmission wavelength band. There is.

The multi-band filter 500 can change the multiple interference optical paths and change the peak wavelength position of the transmission spectrum by changing the film thickness of the cavity layer. That is, the multi-band filter 500 can incident light having a transmission spectrum having a different peak wavelength for each light receiving unit 221 by changing the film thickness of the cavity layer on the light receiving unit 221.

In this embodiment, an example in which silicon oxide (SiO2) is used as the low refractive index dielectric material and titanium oxide (TiO2) is used as the high refractive index dielectric material of the multi-band filter 500 has been described. However, the low refractive index dielectric material of the multi-band filter according to the embodiment of the present invention is not limited to this.

FIG. 6 is a diagram showing an example of an arrangement of a multi-band filter and an image pickup device according to an embodiment of the present invention. FIG. 6 is a schematic view of an image sensor 220 in a Bayer array on which a multi-band filter 500 is mounted.

The multi-band filter 500 has regions having different film thicknesses of the cavity layer, and is mounted in a one-to-one combination with respect to the light receiving portion 221. In the example of FIG. 6, four filters corresponding to R (red), G (green), and B (blue) are implemented. The multi-band filter 500 is formed directly on the image sensor 220 and mounted by a lithography process and an etching process.

The multi-band filter 500 includes a plurality of filters corresponding to tristimulus values of colors having spectral transmittance based on the XYZ color matching function. The light transmitted through the multi-band filter 500 is received by the light receiving unit 221.

Note that FIG. 6 is an array of a total of four filters of 2 × 2 per pixel and four light receiving units 221. However, this embodiment is not limited to this, and may be, for example, an arrangement of a total of 9 filters of 3 × 3 per pixel and 9 light receiving units.

Further, the multi-band filter 500 is preferably configured by forming a film as shown in FIG. 5 from the viewpoint of miniaturization of the imaging mechanism 200, but is configured to separately provide a rotation mechanism and provide the multi-band filter on the rotation mechanism. You may. In this case, the movable part of the rotation mechanism rotates, and a filter having a specific wavelength band is arranged on the optical axis to acquire a spectral signal having the spectral wavelength.

Next, the XYZ color matching function will be described. FIG. 7 is a graph showing the XYZ color matching function defined by the XYZ color system by the International Commission on Illumination (CIE). Human retina cells have sensory tissues corresponding to R (red), G (green), and B (blue) for reflected light from an object, and transmit signals to the brain according to their intensity. That is, human beings perceive the color of an object according to the ratio of each signal of R (red), G (green), and B (blue).

The sensitivity of the sensory tissue corresponding to R (red), G (green), and B (blue) has the characteristics shown in FIG. 7, and this characteristic is called a color matching function. The X color function having a large peak near 600 nm detects red, the Y color function having a peak near 555 nm detects green, and the Z color function having a peak near 450 nm detects blue.

The degree of agreement between the artificially created multi-band filter and the XYZ color matching function defined by the CIE is expressed using a q-factor, and there are a total of three q-factors for each of X, Y, and Z. The q-factor takes a value from 0 to 1, and the closer it is to 1, the higher the degree of agreement with the human eye. Further, the index value indicating the degree of agreement of all three, not each of X, Y, and Z, is ν-factor. The multi-band filter 500 is a filter based on the XYZ color matching function shown in FIG. 7, and is set so as to match the XYZ color matching function.

Next, the transmission spectrum of the multi-band filter according to the embodiment of the present invention will be described. FIG. 8 is a graph showing an example of the transmission spectrum of the multi-band filter according to the embodiment of the present invention.

The multi-band filter 500 that transmits the transmission spectrum shown in FIG. 8 has five filters. The multi-band filter 500 includes a first filter, a second filter, a third filter, a fourth filter, and a fifth filter. The first filter is a filter based on the Z color matching function. The second filter is a filter in which the transmission spectrum is shifted to the short wavelength side with respect to the transmission spectrum of the first filter. The third filter is a filter in which the transmission spectrum is shifted to the longer wavelength side with respect to the transmission spectrum of the first filter. The fourth filter is a filter based on the Y color matching function. The fifth filter is a filter based on the X color matching function.

Here, the first filter, the fourth filter, and the fifth filter are examples of filters belonging to the first filter group. For example, the filter belonging to the first filter group is a filter based on the XYZ color matching function. Further, the transmission spectrum of the first filter has a peak wavelength on the shortest wavelength side among the filters belonging to the first filter group. The first filter is a filter based on the Z color matching function among the XYZ color matching functions shown in FIG. 7.

FIG. 8 shows that the transmission spectrum of the first filter is narrower than the wavelength range of the transmission spectra of the fourth filter and the fifth filter. The wavelength range of the transmission spectrum means the peak width of the spectrum. The length of the wavelength range of the transmission spectrum of the first filter is calculated by the value of the standard deviation obtained by approximating the spectral transmittance characteristics of the first filter with a Gaussian distribution, that is, the approximation formula by the Gaussian distribution of the color matching function described later. It is the value of the standard deviation σ.

Further, FIG. 8 shows that the transmission spectra of the second filter and the third filter are shifted in the wavelength direction with respect to the transmission spectra of the first filter. The second filter and the third filter are filters based on the Z color matching function in which the peak wavelength is changed with respect to the reference peak wavelength of the first filter based on the Z color matching function.

Here, the second filter and the third filter are examples of filters belonging to the second filter group. For example, the filter belonging to the second filter group is a filter whose transmission spectrum is shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group. is there.

In the example of FIG. 8, the peak wavelength of the transmission spectrum of the first filter is 450 nm, which is the reference peak wavelength of the Z color matching function, whereas the peak wavelengths of the transmission spectra of the second filter and the third filter are respectively. It is 430 nm and 470 nm. That is, the transmission spectra of the second filter and the third filter are different in peak wavelength from the transmission spectrum of the first filter, but have substantially the same wavelength range as the transmission spectrum of the first filter.

FIG. 8 shows that the peak wavelengths of the transmission spectra of the second filter and the third filter are adjacent to the peak wavelengths of the transmission spectra of the first filter. That is, the range in which the transmission spectrum of the filter belonging to the second filter group is shifted with respect to the transmission spectrum of the first filter is the peak wavelength of the transmission spectrum of the filter belonging to the second filter group and the transmission of the first filter. The peak wavelength of the spectrum is within the adjacent range.

Further, in the example of FIG. 8, the transmission spectra of the first filter, the second filter, and the third filter detect blue (B). The transmission spectrum of the fourth filter detects green (G). The transmission spectrum of the fifth filter detects red (R). Further, in the example of the filter arrangement of FIG. 6, the fifth filter is arranged in the R region, the fourth filter is arranged in the G region, and the first filter, the second filter, and the third filter are arranged in the B region.

As shown in FIG. 8, the transmission spectrum of the first filter has spectral characteristics in a narrow wavelength range as compared with the transmission spectra of the fourth filter and the fifth filter. As a means for improving the color measurement accuracy of the multi-band filter, a filter may be added so as to cover a wavelength region that cannot be received by the existing filter. On the other hand, when the wavelength range of the transmission spectrum is narrow, if the transmission spectrum deviates due to the influence of the manufacturing variation of the filter, the color measurement accuracy is sensitively affected and the influence of the deviation increases.

The multi-band filter according to the embodiment of the present invention includes a first filter having the narrowest transmission spectrum wavelength range among filters belonging to the first filter group, and a transmission spectrum having a wavelength direction with respect to the transmission spectrum of the first filter. A filter belonging to the second filter group shifted to is provided. As a result, the multi-band filter according to the embodiment of the present invention can absorb the variation and deviation of the spectrum, and has a highly robust filter structure. That is, the multi-band filter according to the embodiment of the present invention can reduce the influence of manufacturing variations while maintaining the color measurement accuracy.

Further, the image processing system according to the embodiment of the present invention generates a color signal based on the transmission spectrum of the multi-band filter according to the embodiment of the present invention, thereby causing manufacturing variation, aging deterioration, and deterioration due to the usage environment. Even when the filter parameters deviate due to the above, the influence of manufacturing variation can be reduced while maintaining the color measurement accuracy.

Further, the imaging device according to the embodiment of the present invention has a multi-band filter according to the present invention in the imaging mechanism. Therefore, the image pickup apparatus according to the present invention can reduce the influence of manufacturing variations while maintaining the color measurement accuracy, and can capture the characteristics of the object with high accuracy.

In FIG. 8, the transmission spectrum of the second filter is shifted to the short wavelength side with respect to the transmission spectrum of the first filter. On the other hand, in the third filter, the transmission spectrum is shifted to the longer wavelength side with respect to the transmission spectrum of the first filter. The multi-band filter 500 shown in FIG. 8 has described an example of a filter configuration of five, but the multi-band filter according to the embodiment of the present invention has four filters excluding the third filter or the first filter shown in FIG. The filter configuration may be. Further, the multi-band filter according to the embodiment of the present invention may further have an arbitrary filter added to form a filter configuration of 6 or more.

Further, in the multi-band filter 500 shown in FIG. 8, the wavelength range of the transmission spectrum of the first filter is narrower than the wavelength range of the fourth filter and the fifth filter. Instead, for example, when the wavelength range of the transmission spectrum of the fourth filter is narrower than the wavelength range of the first filter and the fifth filter, the multi-band filter according to the embodiment of the present invention has a transmission spectrum of the first. A filter that is shifted in the wavelength direction with respect to the transmission spectrum of the four filters may be provided.

● Information processing flow of image processing system ●
FIG. 9 is a flowchart showing an example of the flow of information processing of the image processing system according to the embodiment of the present invention.

When the multi-band filter 500 is set by the filter setting control means 621 in step S901, the information processing of the image processing system shifts to the process of step S905. On the other hand, when the multi-band filter 500 is not set by the filter setting control means 621, the information processing of the image processing system shifts to the processing of step S902.

In step S902, the filter setting control means 621 sets a plurality of filters based on the reference spectrum of the XYZ color matching function stored in advance by the storage control means 622.

Specifically, the filter setting control means 621 sets a fifth filter, a fourth filter, and a first filter belonging to the first filter group based on the X, Y, and Z color matching functions. Further, the second filter is set based on the Z color matching function having the reference peak wavelength of 430 nm. Further, the third filter is set based on the Z color matching function having the reference peak wavelength of 470 nm.

In step S903, the signal acquisition means 611 acquires a spectral signal from the image pickup device 220 through a multi-band filter 500 having a filter set by the filter setting control means 621.

In step S904, the signal processing means 612 generates a color signal based on the spectral signal acquired by the signal acquisition means 611.

On the other hand, when the multi-band filter 500 has already been set by the filter setting control means 621, the process proceeds to step S905. In step S905, the test pattern acquisition means 623 acquires the spectrum information of the test pattern imaged by the imaging mechanism 200.

In step S906, the filter correction means 624 corrects each filter based on the tristimulus value of the color as the reference information stored by the memory control means 622 and the test pattern acquired by the test pattern acquisition means 623. Calculate the value.

Specifically, the filter correction means 624 calculates the tristimulus value of the color of the test pattern from the spectrum information of the test pattern acquired by the test pattern acquisition means 623. The formula for calculating the color tristimulus values is shown in Equation 1 below.

(T in Equation 1 is the color tristimulus value (3 × 1 matrix), a ^T is the translocation matrix for the conversion matrix a (b × 3 matrix), and F is the matrix notation of the transmission spectrum of the filter (n × b matrix). , F ^T is a transposed matrix for the matrix F, D is (diagonal matrix of n × n) matrix representation of the spectral sensitivity spectrum of the photo sensor (imaging device), C is the spectral sensitivity spectrum (n × 1 matrix) of the object, A is a color matching function matrix (n × 3 matrix), ^AT is a translocation matrix for matrix A, b is the number of filters, and n is the number of discrete wavelength elements.)

Then, the filter correction means 624 calculates the correction matrix L (3 × 3 diagonal matrix) using the calculated color tristimulus value of the test pattern and the color tristimulus value as reference information.

FIG. 19 is a graph showing an example of a method of calculating the diagonal component of the correction matrix L. The horizontal axis of FIG. 19 shows the color tristimulus values X, Y, and Z of the test pattern, and the vertical axis shows the color tristimulus values X ₀ , Y ₀ , and Z ₀ as reference information.

As a result of calculating Lx such that the value of Equation 2 is the minimum by the method of least squares, Lx becomes as in Equation 3. Similarly, as a result of calculating Ly and Lz, the correction matrix L of Equation 4 can be obtained.

(I in Equation 2 represents the sample number of the referenced filter (i = 1 to m, m is a natural number).)

In step S907, the filter correction means 624 corrects each filter in the multi-band filter 500 based on the calculated correction matrix L.

When the multi-band filter 500 is corrected by the filter correction means 624 in step S907, the information processing of the image processing system shifts to the process of step S903 described above. In this case, in step S903, the signal acquisition means 611 acquires the spectrum signal from the image sensor 220 through the multi-band filter 500 having the filter corrected by the filter correction means 624.

As described above, the image processing system 100 can set the filter of the multi-band filter 500 and correct each filter of the multi-band filter 500. As a result, the image processing system 100 can reduce the influence of manufacturing variations while maintaining the color measurement accuracy by generating a color signal based on the set multi-band filter 500.

● Evaluation of multi-band filter ●
● Evaluation Method and Filter Setting Next, the evaluation of the influence of the variation of the transmission spectrum in the multi-band filter according to the embodiment of the present invention will be described. FIG. 10 is a diagram showing an example of multi-band level setting assigned to the L18 orthogonal array.

In order to evaluate the influence of q-factor and ν-factor due to the variation of the transmission spectrum, as shown in FIG. 10, a situation in which the transmission spectrum of each filter varies is arbitrarily created using the L18 orthogonal array. FIG. 10 shows an example of setting the level for evaluating the influence of the variation of the transmission spectrum of the multi-band filter related to the five filters, but in the case of the multi-band filter related to the three filters and the four filters. It is also possible to use the same evaluation method for.

As shown in FIG. 10A, the case where the transmission spectrum of each filter is randomly shifted by ± 10 nm with respect to the reference peak wavelength is evaluated. Further, as shown in FIG. 10B, the reference peak wavelength of the transmission spectrum of each filter is the filter No. 1 is 450 nm, filter No. 2 is 430 nm, filter No. 3 is 470 nm, filter No. 4 is 520 nm, filter No. 5 is 620 nm.

FIG. 10 (c) shows the result of allocating the multi-band level to the L18 orthogonal array based on the setting contents shown in FIGS. 10 (a) and 10 (b).

The effect of variation in the transmission spectrum can be evaluated by calculating q-factor and ν-factor for all combinations of filters and calculating their standard deviations. In the example shown in FIG. 10, three types of filters, a reference filter and a filter shifted by ± 10 nm from the reference, were assigned to each of the five filters No. 1 to No. 5.

q-factor and ν-factor are artificially created by the transpose matrix ^AT for the Jacobian function matrix A corresponding to the XYZ color function defined by the CIE, the Jacobian function matrix A, and the matrix F of the transmission spectrum of the filter. is a parameter indicating the degree of coincidence between transposed matrix ^A'T against such Toiro function matrix A'. Specifically, the transpose matrix A ^T is the value shown in Equation 1, the transposed matrix ^A'T is a value obtained by multiplying the transposed matrix F ^T to a ^T indicated in Formula 1 for the matrix F of the transmission spectrum of the filter from the right is there. The degree of agreement is calculated by the square value R ² (0 ≦ R ² ≦ 1) of the correlation coefficient R. R ² indicates that the closer it is to 1, the higher the degree of agreement is and the closer the filter is to the human eye, and conversely, the closer it is to 0, the lower the degree of agreement is to indicate that the filter is far from the human eye.

Further, q-factor is, X of the transposed matrix ^{A T} and ^A'T, Y, because it calculates the matching degree for each Z line, qX-factor, qY-factor , 3 three parameters qZ-factor calculation Will be done. On the other hand, [nu-factor is, X of the transposed matrix ^{A T} and ^A'T, Y, is one of the parameters calculated are collectively matching degree Z line in 1 line 3n columns.

Here, for example, in the case of four filters, 81 kinds of calculations are required because three kinds of a reference filter and a ± 10 nm filter are calculated for one filter in all combinations. Similarly, in the case of five filters, 243 calculations are required, which increases the amount of calculation. On the other hand, if the L18 orthogonal array shown in FIG. 10 is used, it is expected that the calculation efficiency will be improved.

Since the variation results of q-factor and ν-factor calculated by allocating in the L18 orthogonal array are considered to be substantially the same as the variation results of the samples extracted without bias, fair variation comparison is possible.

Next, an approximation based on the XYZ color matching function will be described for the multi-band filter. FIG. 11 is a graph showing an example of the result of approximating the transmission spectrum of the first filter constituting the multi-band filter 500 shown in FIG. 8 with the Gaussian distribution of the Z color matching function.

The solid line shown in FIG. 11 is the result of approximating the transmission spectrum of the first filter constituting the multi-band filter 500 shown in FIG. 8 by a Gaussian distribution in order to match the Z color matching function. On the other hand, the point cloud shown in FIG. 11 is the transmission spectrum of the first filter constituting the multi-band filter 500 shown in FIG.

The approximation result shown by the solid line in FIG. 11 is represented by the following equation 5 representing the Gaussian distribution. The spectrum shown by the solid line in FIG. 11 has a peak transmittance A = 94.5%, a standard deviation σ = 22.5 nm, and a peak wavelength μ = 450 nm. Further, as a result of approximating the Z color matching function shown in FIG. 7 by Gaussian distribution, A is an arbitrary stimulus value, standard deviation σ = 22.5 nm, and peak wavelength μ = 450 nm.

(A in Equation 5 represents the peak transmittance (%), σ represents the standard deviation (nm), and μ represents the peak wavelength (nm).)

As shown by the point cloud in FIG. 11, the transmission spectrum of the first filter has a broad peak near 600 nm. Therefore, when the transmission spectrum of the first filter itself is used, it is not possible to accurately evaluate the influence of the variation in the transmission spectrum due to the influence of this broad peak. Therefore, in each simulation described below, as shown by the solid line in FIG. 11, the transmission spectrum of the first filter was approximated by a Gaussian distribution in order to match the Z color matching function.

FIG. 12 is a graph showing an example of the result of simulating the degree of agreement with the Z color matching function by making the standard deviation σ variable. FIG. 12A is a graph showing an example in which one of the transmission spectra of the three filters is approximated by a Gaussian distribution.

Specifically, among the transmission spectra of the first filter, the fourth filter, and the fifth filter shown in FIG. 8, the transmission spectrum of the first filter is a Gaussian distribution for matching the Z color matching function as shown in FIG. The approximation was made by. In FIG. 12A, the peak wavelength of the transmission spectrum of the first filter was fixed at μ = 450 nm, and qX-factor, qY-factor, qZ-factor, and ν-factor were calculated while changing the standard deviation σ.

FIG. 12B is a graph showing an example in which two of the transmission spectra of the four filters are approximated by a Gaussian distribution. Specifically, among the transmission spectra of the first filter, the second filter, the fourth filter, and the fifth filter shown in FIG. 8, the transmission spectra of the first filter and the second filter are Z-equalized as shown in FIG. An approximation was made with a Gaussian distribution to match the function.

In FIG. 12B, the peak wavelength of the transmission spectrum of the first filter is fixed at μ = 450 nm, the peak wavelength of the transmission spectrum of the second filter is fixed at μ = 430 nm, and qX-factor and qY are changed while changing the standard deviation σ. -Factor, qZ-factor, ν-factor were calculated.

FIG. 12 (c) is a graph showing an example in which two of the transmission spectra of the four filters are approximated by a Gaussian distribution. Specifically, among the transmission spectra of the first filter, the third filter, the fourth filter, and the fifth filter shown in FIG. 8, the transmission spectra of the first filter and the third filter are Z-equalized as shown in FIG. An approximation was made with a Gaussian distribution to match the function.

In FIG. 12 (c), the peak wavelength of the transmission spectrum of the first filter is fixed at μ = 450 nm, the peak wavelength of the transmission spectrum of the third filter is fixed at μ = 470 nm, and qX-factor and qY are changed while changing the standard deviation σ. -Factor, qZ-factor, ν-factor were calculated.

FIGS. 12 (a), 12 (b) and 12 (c) show that qZ-factor and ν-factor have maximum values when the standard deviation σ = 22.5. On the other hand, the figure shows that even if the standard deviation σ changes in the range of 12.5 to 32.5 nm, qX-factor and qY-factor are not significantly affected.

FIG. 13 is a graph showing an example of the result of simulating the degree of agreement with the Z color matching function by making the peak wavelength μ variable. The figure shows an example in which one of the transmission spectra of the three filters is approximated by a Gaussian distribution.

Specifically, among the transmission spectra of the first filter, the fourth filter, and the fifth filter shown in FIG. 8, the transmission spectrum of the first filter is a Gaussian distribution for matching the Z color matching function as shown in FIG. The approximation was made by. In FIG. 13, qX-factor, qY-factor, qZ-factor, and ν-factor were calculated while changing the peak wavelength μ of the transmission spectrum of the first filter.

As shown in FIG. 13, it is shown that qZ-factor and ν-factor take the maximum values when the peak wavelength μ = 450 nm. On the other hand, the figure shows that even if the peak wavelength μ changes in the range of 420 nm to 480 nm, qX-factor and qY-factor are not significantly affected.

As described above, from the results of FIGS. 12 and 13, when the standard deviation or the peak wavelength changes, the values of qZ-factor and ν-factor are affected. The error in color measurement accuracy becomes smaller as the value of qZ-factor or ν-factor approaches 1.

● Color Measurement Accuracy of Multi-Band Filter FIG. 14 is a graph showing an example of the relationship between the arrangement of filters and each parameter in the multi-band filter according to the embodiment of the present invention. The figure shows the average value of q-factor and ν-factor, the variation of q-factor and ν-factor, q-factor and ν-factor of each multi-band filter assigned by the L18 orthogonal array shown in FIG. The coefficient of variation of is shown.

In FIG. 14, (A) is a multi-band filter having the first filter, the fourth filter, and the fifth filter shown in FIG. 8, and (B) is the first filter, the second filter, and the fourth filter shown in FIG. A multi-band filter having a fifth filter, (C) is a first filter, a third filter, a fourth filter, and a multi-band filter having a fifth filter shown in FIG. 8, and (D) is a first filter shown in FIG. A multi-band filter having a filter, a second filter, a third filter, a fourth filter, and a fifth filter is shown.

Here, the first filter, the fourth filter, and the fifth filter are examples of filters belonging to the first filter group. In FIG. 14, the first filter is a filter for matching the Z color matching function, the fourth filter is a filter for matching the Y color matching function, and the fifth filter is the X color matching function. It is a filter for matching.

The second filter and the third filter are examples of filters belonging to the second filter group. The transmission spectra of the second filter and the third filter are shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group.

FIG. 14A is a graph showing an example of the relationship between the average values of q-factor and ν-factor of multi-band filters having different filter arrangements. In FIG. 14A, the average values of qZ-factor and ν-factor of (B), (C), and (D) are closer to 1 as compared with (A), and high color measurement accuracy is obtained. Shows that it has.

That is, by adding the second filter or the third filter shown in FIG. 8 to the multi-band filter having the three filters of the first filter, the fourth filter, and the fifth filter shown in FIG. 8, the color measurement accuracy can be improved. Can be improved.

FIG. 14B is a graph showing an example of the relationship between the multi-band filters having different filter arrangements and the variations of q-factor and ν-factor. FIG. 14 (c) is a graph showing an example of the relationship between the coefficient of variation of q-factory and ν-factory of multi-band filters having different filter arrangements.

In FIGS. 14 (b) and 14 (c), in (B), (C) and (D), the variation and coefficient of variation of qZ-factor and ν-factor are smaller than those in (A). It shows that the variation in color measurement accuracy is improved.

As shown in FIG. 14, the multi-band filter 500 having at least one of the second filter and the third filter has improved qZ-factor and ν-factor. That is, the multi-band filter according to the embodiment of the present invention includes filters belonging to the second filter group (first filter, fourth filter, fifth filter) in addition to the filters belonging to the first filter group (first filter, fourth filter, fifth filter). By setting at least one filter out of (2 filters, 3rd filter), it is possible to reduce the influence of manufacturing variations while maintaining the color measurement accuracy.

FIG. 15 is a graph showing an example of the result of simulating the degree of agreement with the Z color matching function by making the standard deviation σ variable. FIG. 10A shows the average value of qZ-factor and ν-factor of each multi-band filter assigned in the L18 orthogonal array shown in FIG. 10, and FIG. 10B shows the variation of qZ-factor and ν-factor. (C) shows the coefficient of variation of qZ-factor and ν-factor.

Specifically, the transmission spectra of the first filter, the second filter, and the third filter shown in FIG. 8 were approximated by a Gaussian distribution to match the Z color matching function shown in FIG. Then, the standard deviation σ of the approximate Gaussian distribution is made variable in the range of 12.5 nm to 32.5 nm, and the result is that the allocation is performed in the L18 orthogonal array shown in FIG.

In FIG. 15, the multi-band filter having the first filter, the fourth filter, and the fifth filter shown in FIG. 8 is 3 bands, and the multi-band having the first filter, the second filter, the fourth filter, and the fifth filter shown in FIG. The filter is referred to as 4band−, and the multiband filter having the first filter, the third filter, the fourth filter, and the fifth filter shown in FIG. 8 is referred to as 4band +.

Here, the first filter, the fourth filter, and the fifth filter are examples of filters belonging to the first filter group. In FIG. 15, the first filter is a filter for matching the Z color matching function, the fourth filter is a filter for matching the Y color matching function, and the fifth filter is the X color matching function. It is a filter for matching.

The second filter and the third filter are examples of filters belonging to the second filter group. The transmission spectra of the second filter and the third filter are shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group.

FIG. 15 (a) is a graph showing an example of the relationship between the average values of qZ-factor and ν-factor of multi-band filters having different filter arrangements. In FIG. 15 (a), 4band- and 4band + have an average value of qZ-factor and ν-factor approaching 1 in the range of standard deviation σ = 12.5 to 32.5 nm as compared with 3band. It shows that the color measurement accuracy is improved.

The effect of improving the color measurement accuracy is most noticeable when the standard deviation σ = 12.5 nm at 4 band−.

That is, the first filter shown in FIG. 8 has a standard deviation of σ = 12.5 to 32.5 nm when the transmission spectra of the first filter, the second filter, and the third filter shown in FIG. 8 are approximated by a Gaussian distribution. By adding the second filter or the third filter shown in FIG. 8 to the multi-band filter having three filters, the fourth filter and the fifth filter, the color measurement accuracy can be improved.

Further, by adding the second filter shown in FIG. 8 to the multi-band filter having the three filters of the first filter, the fourth filter, and the fifth filter shown in FIG. 8, the color measurement accuracy is further improved. The effect of can be obtained.

FIG. 15B is a graph showing an example of the relationship between the multi-band filters having different filter arrangements and the variations of qZ-factor and ν-factor. FIG. 15 (c) is a graph showing an example of the relationship between the coefficient of variation of qZ-factor and ν-factor of multi-band filters having different filter arrangements.

In FIGS. 15B and 15C, the variation and coefficient of variation of qZ-factor and ν-factor are smaller in the range of standard deviation σ = 12.5 to 32.5 nm in 4band- than in 3band. This indicates that the variation in color measurement accuracy has been improved.

Further, in 4band +, the variation of qZ-factor and ν-factor is smaller in the range of standard deviation σ = 22.5 to 32.5 nm as compared with 3band, and the variation of color measurement accuracy is improved. It is shown that. The effect of improving the variation in color measurement accuracy is most noticeable when the standard deviation σ = 17.5 nm at 4 band−.

As shown in FIG. 15, in addition to the filters belonging to the first filter group, by adding at least one of the second filter or the third filter having a standard deviation σ in the range of 12.5 to 32.5 nm. qZ-factor and ν-factor are improved. Here, as shown in FIGS. 11 and 5, the standard deviation σ is a value obtained by approximating the spectral transmittance characteristics of the first filter with a Gaussian distribution, and corresponds to the length of the wavelength range of the transmission spectrum of the first filter. To do.

That is, the multi-band filter 500 has a length of the wavelength range of the transmission spectrum of the first filter in the range of 12.5 to 32.5 nm, and is a filter belonging to the first filter group (first filter, fourth filter, By setting a filter belonging to the second filter group in which the length of the wavelength range is in the range of 12.5 to 32.5 nm in addition to the fifth filter), the influence of manufacturing variation while maintaining the color measurement accuracy. Can be reduced. The length of the wavelength range of the first filter and the filter belonging to the second filter group is not limited to the above range as long as the same effect can be obtained.

Preferably, the multi-band filter 500 has a wavelength range length of 17.5 nm in the transmission spectrum of the first filter and, in addition to the filters belonging to the first filter group, a wavelength range length of 17.5 nm. By setting a certain second filter, the influence of manufacturing variation can be further reduced.

FIG. 16 is a graph showing an example of the result of simulating the degree of agreement with the Z color matching function by making the peak wavelength μ variable. The multi-band filters shown in FIG. 16 show the results of the simulation. In addition to the first filter, the fourth filter, and the fifth filter shown in FIG. 8, four multi-band filters obtained by adding one of the second filter or the third filter shown in FIG. Has a filter.

Here, the first filter, the fourth filter, and the fifth filter are examples of filters belonging to the first filter group. In FIG. 16, the first filter is a filter for matching the Z color matching function, the fourth filter is a filter for matching the Y color matching function, and the fifth filter is the X color matching function. It is a filter for matching.

The second filter and the third filter are examples of filters belonging to the second filter group. The transmission spectra of the second filter and the third filter are shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group.

16A shows the average value of qZ-factor in the multi-band filter in which the peak wavelength μ of the second filter or the third filter is variable, FIG. 16B shows the variation of qZ-factor, and FIG. 16C shows the qZ-factor. The coefficient of variation of is shown.

Specifically, in order to match the transmission spectra of the first filter shown in FIG. 8 and one filter belonging to the second filter group (second filter or third filter) with the Z color matching function shown in FIG. An approximation was made by the Gaussian distribution.

Then, the peak wavelength μ of the transmission spectrum of the first filter is set as the reference peak wavelength, and the peak wavelength μ of the Gaussian distribution of the filters belonging to the approximated second filter group is variable within a range of ± 30 nm with respect to the reference peak wavelength. This is the result of the allocation in the L18 orthogonal array shown in FIG.

FIG. 16A is a graph showing an example of the relationship with the average value of qZ-factor of multi-band filters having different peak wavelengths μ of the filters belonging to the second filter group. In FIG. 16A, the average value of qZ-factory approaches 1 by adding a filter belonging to the second filter group having a peak wavelength within ± 30 nm with respect to the reference peak wavelength. It shows that the color measurement accuracy is improved.

Further, the average value of qZ-factory is substantially symmetrical on the short wavelength side and the long wavelength side with reference to the reference peak wavelength. Therefore, the filter belonging to the second filter group can be provided on either the short wavelength side or the long wavelength side with reference to the reference peak wavelength, and the effect of improving the color measurement accuracy can be obtained.

FIG. 16B is a graph showing an example of the relationship between a multi-band filter having a different peak wavelength μ of a filter belonging to the second filter group and a variation of qZ-factor. FIG. 16C is a graph showing an example of the relationship with the coefficient of variation of qZ-factor of multi-band filters having different peak wavelengths μ of filters belonging to the second filter group.

In FIGS. 16 (b) and 16 (c), by adding a filter belonging to the second filter group having a peak wavelength within ± 30 nm with respect to the reference peak wavelength, the variation and coefficient of variation of qZ-factor can be increased. It is smaller, indicating that the color measurement accuracy is improved.

The effect of reducing the variation in color measurement accuracy is more prominent by adding a filter (second filter) belonging to the second filter group on the short wavelength side with reference to the reference peak wavelength.

As shown in FIG. 16, in addition to the filter belonging to the first filter group, a filter belonging to the second filter group having a peak wavelength μ in the range of ± 30 nm with respect to the reference peak wavelength of the Z color matching function is added. By doing so, the qZ-factor is improved.

That is, the multi-band filter 500 includes a range in which the transmission spectrum is shifted with respect to the transmission spectrum of the first filter in addition to the filters belonging to the first filter group (first filter, fourth filter, fifth filter). By setting a filter belonging to the second filter group in which is 30 nm or less, the influence of manufacturing variation can be reduced while maintaining the color measurement accuracy. The range in which the transmission spectrum of the filter belonging to the second filter group is shifted with respect to the transmission spectrum of the first filter is not limited to the above range as long as the same effect can be obtained.

Further, preferably, the multi-band filter 500 belongs to a second filter group in which the transmission spectrum is shifted by 10 nm in the wavelength direction with respect to the transmission spectrum of the first filter, in addition to the filters belonging to the first filter group. By setting the filter, it is possible to reduce the influence of manufacturing variation while maintaining the color measurement accuracy.

Further, preferably, in the multi-band filter 500, in addition to the filters belonging to the first filter group, the range in which the transmission spectrum is shifted with respect to the transmission spectrum of the first filter is 30 nm or less on the short wavelength side. By setting the second filter, the influence of manufacturing variation can be further reduced.

FIG. 17 is a graph showing an example of the relationship between the arrangement of filters and each parameter in the multi-band filter according to the embodiment of the present invention. In FIG. 17, each filter for matching each of the X, Y, and Z color matching functions was calculated by changing the reference peak wavelength μ of each filter according to the allocation of the L18 orthogonal array shown in FIG. a) is the average value of q-factor and ν-factor of multi-band filters with different filter arrangements, (b) is the variation of q-factor and ν-factor, and (c) is the coefficient of variation of q-factor and ν-factor. Is shown.

Here, in FIG. 17, the first filter shown in FIG. 8 is a filter for matching the Z color matching function, and the fourth filter shown in FIG. 8 is a filter for matching the Y color matching function. , The fifth filter shown in FIG. 8 is a filter for matching the X color matching function. The first filter, the fourth filter, and the fifth filter are examples of filters belonging to the first filter group.

In FIG. 17, the peak wavelength of the transmission spectrum of the first filter is μ = 450 nm, the peak wavelength of the transmission spectrum of the second filter is μ = 430 nm, and the peak wavelength of the transmission spectrum of the third filter is μ = 470 nm. The peak wavelength of the transmission spectrum of the four filters is μ = 520 nm, and the peak wavelength of the transmission spectrum of the fifth filter is μ = 620 nm. Further, the standard deviation when the transmission spectra of the first filter, the second filter, and the third filter are approximated by a Gaussian distribution is σ = 22.5.

Here, the second filter and the third filter are examples of filters belonging to the second filter group. The transmission spectra of the second filter and the third filter are shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group.

In FIG. 17, (A) is a multi-band filter having the first filter, the fourth filter, and the fifth filter shown in FIG. 8, and (B) is the second filter, the fourth filter, and the fifth filter shown in FIG. The multi-band filter which has is shown. (C) is a multi-band filter having a third filter, a fourth filter, and a fifth filter shown in FIG. 8, and (D) is a first filter, a second filter, a fourth filter, and a fifth filter shown in FIG. The multi-band filter having (E) is the first filter, the third filter, the fourth filter, and the multi-band filter having the fifth filter shown in FIG. 8, and (F) is the first filter and the first filter shown in FIG. A multi-band filter having a second filter, a third filter, a fourth filter, and a fifth filter is shown.

FIG. 17A is a graph showing an example of the relationship between the average values of q-factor and ν-factor of multi-band filters having different filter arrangements.

As shown in (A) to (C) of FIG. 17 (a), the multi-band filter ((A)) having the first filter for matching the Z color matching function is a multi without the first filter. Compared with the band filters ((B) and (C)), the average values of qZ-factor and ν-factor are closer to 1. That is, it is shown that the color measurement accuracy is lowered when the first filter for matching the Z color matching function is not provided.

Further, as shown in (A), (D) to (F) of FIG. 17 (a), in addition to the first filter, the fourth filter, and the fifth filter belonging to the first filter group, the second filter The multi-band filters ((D)-(F)) having filters belonging to the group are qZ-factor and ν as compared with the multi-band filters ((A)) having no filters belonging to the second filter group. -The average value of factor is approaching 1.

That is, the color measurement accuracy is improved by providing a filter belonging to the second filter group in addition to the first filter, the fourth filter, and the fifth filter for matching each of the X, Y, and Z color matching functions. Indicates to do.

FIG. 17B is a graph showing an example of the relationship between the multi-band filters having different filter arrangements and the variations of q-factor and ν-factor. FIG. 17 (c) is a graph showing an example of the relationship between the coefficient of variation of q-factor and ν-factor of multi-band filters having different filter arrangements.

As shown in FIGS. 17 (b) and 17 (c) (A) to (C), the multi-band filter ((A)) having the first filter for matching the Z color matching function uses the first filter. Compared with the non-existing multi-band filters ((B) and (C)), the variation and coefficient of variation of qZ-factor and ν-factor are smaller. That is, it is shown that the variation in color measurement accuracy becomes large when the first filter for matching the Z color matching function is not provided.

Further, as shown in (A), (D) to (F) of FIGS. 17 (b) and 17 (c), in addition to the first filter, the fourth filter, and the fifth filter belonging to the first filter group, A multi-band filter ((D)-(F)) having a filter belonging to the second filter group has a qZ as compared with a multi-band filter ((A)) having no filter belonging to the second filter group. The variation and coefficient of variation of −factory and ν-factor are small.

That is, it is shown that the variation in color measurement accuracy is reduced by providing the filter belonging to the second filter group in addition to the filter belonging to the first filter group. Then, as shown in (D) and (F) of FIGS. 17 (b) and 17 (c), the effect of reducing the variation in color measurement accuracy is the first to match each of the X, Y, and Z color matching functions. It appears most prominently by providing the second filter in addition to the first filter, the fourth filter, and the fifth filter.

As shown in FIG. 17, the first filter based on the Z color matching function belonging to the first filter group, the fourth filter based on the Y color matching function, and the fifth filter based on the X color matching function. In addition, by adding a filter belonging to the second filter group, qZ-factor and ν-function are improved.

That is, the multi-band filter according to the embodiment of the present invention includes a first filter based on the Z color matching function belonging to the first filter group, a fourth filter based on the Y color matching function, and an X color matching function. In addition to the fifth filter based on the above, the color measurement accuracy is maintained by setting a filter belonging to the second filter group in which the transmission spectrum is shifted in the wavelength direction with respect to the transmission spectrum of the first filter. At the same time, the influence of manufacturing variations can be reduced.

Further, preferably, in addition to the first filter based on the Z color matching function belonging to the first filter group, the fourth filter based on the Y color matching function, and the fifth filter based on the X color matching function. By setting the second filter in which the transmission spectrum is shifted to the short wavelength side with respect to the transmission spectrum of the first filter, the influence of manufacturing variation can be further reduced.

FIG. 18 is a graph showing another example of the relationship between the arrangement of filters and each parameter in the multi-band filter according to the embodiment of the present invention.

In the correction process of each filter shown in FIG. 9, it is difficult to apply the optimum transformation matrix a shown by the number 1 for each pixel, and it is conceivable to use a fixed value for the transformation matrix a of all the pixels. Therefore, the transformation matrix a was calculated by changing the reference peak wavelength μ of each filter according to the allocation of the L18 orthogonal array shown in FIG. Then, a new transformation matrix a'was calculated as the average value of the calculated transformation matrix a, and new allocation to the L18 orthogonal array was performed based on the new transformation matrix a'.

In FIG. 18, each filter for matching each of the X, Y, and Z color matching functions is set to the reference peak of each filter according to the allocation of the L18 orthogonal table shown in FIG. 10 using a new transformation matrix a'. Calculated by changing the wavelength μ, (a) is the average value of q-factor and ν-factor of multi-band filters with different filter arrangements, (b) is the variation of q-factor and ν-factor, and (c) is. The coefficient of variation of q-factor and ν-factor is shown.

In FIG. 18, (A) is a multi-band filter having a first filter, a fourth filter, and a fifth filter shown in FIG. 8, and (B) a first filter, a second filter, a fourth filter, and a fifth filter shown in FIG. A multi-band filter having a filter, (C) is a first filter, a third filter, a fourth filter, a multi-band filter having a fifth filter shown in FIG. 8, and (D) is a first filter shown in FIG. A multi-band filter having a second filter, a third filter, a fourth filter, and a fifth filter is shown.

The values of the peak wavelength μ and the standard deviation σ of the transmission spectra of the first filter to the fifth filter in FIG. 18 are the same as the values in FIG.

FIG. 18A is a graph showing an example of the relationship between the average values of q-factor and ν-factor of multi-band filters having different filter arrangements.

As shown in (A), (B), and (D) of FIG. 18 (a), a multi-band filter ((B)) having a second filter in addition to the first filter, the fourth filter, and the fifth filter. In (D)), the average values of qZ-factor and ν-factor are closer to 1 as compared with the multi-band filter ((A)) having no second filter. That is, it is shown that the color measurement accuracy is improved by providing the second filter in addition to the first filter, the fourth filter, and the fifth filter for matching each of the X, Y, and Z color matching functions. There is.

FIG. 18B is a graph showing an example of the relationship between multi-band filters having different filter arrangements and variations of q-factor and ν-factor. FIG. 18C is a graph showing an example of the relationship between the coefficient of variation of q-factor and ν-factor of multi-band filters having different filter arrangements.

As shown in (A) to (D) of FIGS. 18 (b) and 18 (c), a multi having at least one of a second filter and a third filter in addition to the first filter, the fourth filter, and the fifth filter. The band filters ((B) to (D)) have variations and variations in qZ-factor and ν-factor as compared with the multi-band filter ((A)) composed of the first filter, the fourth filter, and the fifth filter. The coefficient is small.

That is, by providing at least one of the second filter and the third filter in addition to the first filter, the fourth filter, and the fifth filter for matching the X, Y, and Z color matching functions, the measurement is performed. It shows that the variation in color accuracy is reduced.

Then, as shown in (B) and (D) of FIGS. 18 (b) and 18 (c), the effect of reducing the variation in color measurement accuracy is the first to match each of the X, Y, and Z color matching functions. It appears most prominently by providing the second filter in addition to the first filter, the fourth filter, and the fifth filter.

As shown in FIG. 18, even when a fixed value is used for the transformation matrix a, the multi-band filter according to the embodiment of the present invention can reduce the influence of manufacturing variation while maintaining the color measurement accuracy. ..

● Summary ●
As described above, in the image processing system according to the embodiment of the present invention, the first filter having the narrowest wavelength range of the transmission spectrum among the filters belonging to the first filter group and the transmission spectrum of the first filter are transmitted. It has a multi-band filter according to an embodiment of the present invention, which includes a filter belonging to a second group of filters that are shifted in the wavelength direction with respect to the spectrum. As described above, the multi-band filter according to the embodiment of the present invention reduces the influence of manufacturing variations while maintaining the color measurement accuracy. Therefore, in the image processing system according to the embodiment of the present invention that generates a color signal based on the transmission spectrum of the multi-band filter according to the embodiment of the present invention, when the transmission spectrum is deviated due to the influence of manufacturing variation. In this case as well, the influence of manufacturing variation can be reduced while maintaining the color measurement accuracy.

The influence of the manufacturing variation of the transmission spectrum becomes remarkable on the color measurement accuracy when the wavelength range of the transmission spectrum is narrow. Therefore, the image processing system according to the embodiment of the present invention is provided with a filter in which the transmission spectrum of the first filter having the narrowest wavelength range of the transmission spectrum among the filters belonging to the first filter group is shifted in the wavelength direction. .. Further, the filter obtained by shifting the transmission spectrum of the first filter in the wavelength direction is provided in a range in which the peak wavelength of the transmission spectrum is adjacent to the peak wavelength of the transmission spectrum of the first filter. As a result, a filter having the same spectral characteristics as the first filter is provided within the range affected by manufacturing variations of the first filter having a narrow wavelength range of the transmission spectrum. Therefore, the image processing system according to the embodiment of the present invention. Can reduce the effects of manufacturing variations.

Further, the filter belonging to the second filter group has a second filter in which the transmission spectrum is shifted to the short wavelength side with respect to the transmission spectrum of the first filter. Further, the filter belonging to the second filter group has a third filter in which the transmission spectrum is shifted to the longer wavelength side with respect to the transmission spectrum of the first filter. Therefore, the image processing system according to the embodiment of the present invention reduces the influence of the manufacturing variation by providing at least one of the second filter and the third filter within the range of the influence of the manufacturing variation of the first filter. be able to.

Further, in the image processing system according to the embodiment of the present invention, the transmission spectrum of the filter belonging to the second filter group is the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group. On the other hand, it has a filter setting unit that sets a filter belonging to the second filter group so as to shift in the wavelength direction. As a result, the filter setting and filter correction of the multi-band filter according to the embodiment of the present invention are performed. Therefore, the image processing system according to the embodiment of the present invention is affected by manufacturing variations while maintaining the color measurement accuracy. It can be reduced.

Further, the multi-band filter according to the embodiment of the present invention is the first filter having the narrowest wavelength range of the transmission spectrum among the filters belonging to the first filter group, and the transmission spectrum with respect to the transmission spectrum of the first filter. It has a filter belonging to a second group of filters that are shifted in the wavelength direction. As a result, the multi-band filter according to the embodiment of the present invention can absorb the variation and deviation of the spectrum, and has a highly robust filter structure. That is, the multi-band filter according to the embodiment of the present invention can reduce the influence of manufacturing variations while maintaining the color measurement accuracy.

Further, the image pickup apparatus according to the embodiment of the present invention has the multi-band filter according to the present invention and the image pickup element arranged on the light emitting side of the multi-band filter, so that the manufacturing variation can be maintained while maintaining the color measurement accuracy. The influence of the above can be reduced, and the characteristics of the object can be captured with high accuracy.

Although the image processing system, the multi-band filter, and the image pickup apparatus according to the embodiment of the present invention have been described so far, the present invention is not limited to the above-described embodiment, and other embodiments, additions, and modifications are made. , Deletion, etc. can be changed within the range that can be conceived by those skilled in the art, and any aspect is included in the scope of the present invention as long as the action / effect of the present invention is exhibited.

100 Image processing system 110 Image pickup device 120 External device 200 Image pickup mechanism 210 Lens 220 Image sensor 300 Image processing unit 310 Image processing unit 400 Filter setting unit 410 Image control unit 500 Multi-band filter 611 Signal acquisition means 612 Signal processing means (signal processing unit) Example)
621 Filter setting control means 622 Memory control means 623 Test pattern acquisition means 624 Filter correction means

JP-A-2007-278950

Claims (14)

With multiple filters
It has a signal processing unit that generates a color signal based on the transmission spectrum of the filter.
The plurality of filters
Filters that belong to the first filter group based on the XYZ color matching function, and
A filter belonging to a second filter group different from the first filter group is included.
The transmission spectrum of the filter belonging to the second filter group is shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group. system. The transmission spectrum of the first filter has a peak wavelength on the shortest wavelength side of the filters belonging to the first filter group.
The image processing system according to claim 1. The peak wavelength of the transmission spectrum of the filter belonging to the second filter group is adjacent to the peak wavelength of the transmission spectrum of the first filter.
The image processing system according to claim 1 or 2. The range in which the transmission spectrum of the filter belonging to the second filter group is shifted with respect to the transmission spectrum of the first filter is within the range affected by the manufacturing variation of the first filter.
The image processing system according to any one of claims 1 to 3. The image processing according to any one of claims 1 to 4, wherein the range in which the transmission spectrum of the filter belonging to the second filter group is shifted with respect to the transmission spectrum of the first filter is 30 nm or less. system. The filter belonging to the second filter group has a second filter in which the transmission spectrum is shifted to the short wavelength side with respect to the transmission spectrum of the first filter.
The image processing system according to any one of claims 1 to 5. The filter belonging to the second filter group has a third filter in which the transmission spectrum is shifted to the longer wavelength side with respect to the transmission spectrum of the first filter.
The image processing system according to any one of claims 1 to 6. The first filter is based on the Z color matching function.
The image processing system according to any one of claims 1 to 7. The length of the wavelength range of the transmission spectrum of the first filter is a value of a standard deviation obtained by approximating the spectral transmittance characteristics of the first filter with a Gaussian distribution.
The image processing system according to claim 8. The length of the wavelength range of the transmission spectrum of the first filter is in the range of 12.5 nm to 32.5 nm.
The image processing system according to claim 9. The filter belonging to the first filter group includes a fourth filter based on the X color matching function and a fifth filter based on the Y color matching function.
The image processing system according to any one of claims 1 to 10. With multiple filters
A signal processing unit that generates a color signal based on the transmission spectra of the plurality of filters, and
It has a filter setting unit for setting the filter and
The plurality of filters
Filters that belong to the first filter group based on the XYZ color matching function, and
A filter belonging to a second filter group different from the first filter group is included.
In the filter setting unit, the transmission spectrum of the filter belonging to the second filter group is shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group. An image processing system that sets a filter belonging to the second filter group so as to perform the above. Filters that belong to the first filter group based on the XYZ color matching function, and
It has a filter belonging to a second filter group different from the first filter group.
The transmission spectrum of the filter belonging to the second filter group is a multi-band that is shifted in the wavelength direction with respect to the transmission spectrum of the first filter having the narrowest wavelength range among the filters belonging to the first filter group. filter. The multi-band filter according to claim 13 and
An image sensor arranged on the light emitting side of the multi-band filter and
An imaging device having.