JP5672029B2 - Reflectance calculating device, reflectance calculating method and program - Google Patents

Description

  The present invention relates to a reflectance calculating apparatus, a reflectance calculating method, and a program for executing a reflectance calculating method for calculating the reflectance of an object by photographing the object illuminated with natural light.

  Currently, hyperspectral cameras (hereinafter referred to as HS cameras) capable of performing spectral imaging for each wavelength in each of a plurality of wavelength bands (ultraviolet light to visible light to far infrared light) are used in various fields. ing. Data of a photographed image photographed by the HS camera includes the reflection spectrum of the measurement object for each pixel. Therefore, the characteristic of the measurement object can be estimated using the characteristic index obtained from the reflection spectrum of the measurement object.

  For example, a system for estimating the characteristics of a measurement object captures a certain area of a paddy field using an HS camera mounted on a satellite or the like, and uses the reflection spectrum of each pixel of the captured image to capture the paddy field The degree of rice growth in the area can be estimated. In this case, the light intensity of the illumination light incident on the measurement object and the spectrum of the light intensity vary depending on the photographing time or the like. Therefore, the system separately obtains a light intensity spectrum that is a spectral characteristic of illumination light at the time of photographing, and calculates the reflectance of the measurement object from the photographed reflection spectrum and the light intensity spectrum of the illumination light at the time of photographing. And the characteristic index is calculated using the obtained reflectance spectrum.

In general, when calculating the reflectance of an object to be measured, photographing data of a white board (white reference data of a white board) having a reflectance of 1 photographed with the same illumination light under the same photographing conditions as the object is used for the illumination light. Used as spectral characteristics (light intensity spectrum).
For example, from the distribution ratio of the protein content obtained by photographing the field from obliquely above with a camera installed on the ground, a threshold for sorting the received ginger by the protein content of the ginger is set. A method of sorting is known.
In this method, the reflectance of the rice plant is determined by photographing the reflected light of natural light from the rice plant and the reference plate in the field and simultaneously measuring the amount of reflected light from the rice plant and the reference plate in the field.

JP 2006-101768 A

  In the above method, since the object is relatively flat like a rice plant in a field, no shadow is generated on the object. However, in the case of a measurement object that has surface irregularities such as one vegetable or about ten vegetables and is shaded by illumination light, the light intensity of the illumination light in the shadow portion cannot be obtained. Even if the reflectance is calculated using a plate, it is difficult to calculate an accurate reflectance spectrum. In addition, the light intensity spectrum of the shadow portion is not a uniform reduction of the light intensity spectrum of the illumination light in the non-shadow portion over the entire wavelength range, so the reflectance of the shadow portion cannot be accurately calculated.

  Therefore, the present invention provides a reflectance calculating apparatus and a reflectance that can accurately calculate the reflectance of a shadow portion of a measurement object without photographing a reference plate such as a white plate by a method different from the above method. It is an object to provide a calculation method and a program.

One aspect of the present invention is a reflectance calculation apparatus that calculates the reflectance of an object by photographing the object illuminated with natural light. The reflectance calculation device is
An image acquisition unit that acquires captured image data of an object illuminated with natural light, including a reflection spectrum of the object for each pixel;
The white reference data of the white reference model that acquires the captured image data as reference image data of the object, and further has a shape that simulates the shape of the object and has the same shadow under the same illumination conditions as the image capturing Of the reference image data, the first partial reference image data corresponding to the shadow part on the white reference model, and the second corresponding to the non-shadow part adjacent to the shadow part on the white reference model. An attenuation rate calculation unit that calculates the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object based on the difference between the partial reference image data and the value of the white reference data corresponding to the shadow portion When,
A data correction unit that corrects the white reference data representing the light intensity spectrum of the illumination light at the time of photographing the object using the attenuation rate of the light intensity;
A reflectance calculating unit that calculates the reflectance of the object using the corrected white reference data and the captured image data;

Another aspect of the present invention is a reflectance calculation method in a reflectance calculation apparatus that calculates the reflectance of an object by photographing the object illuminated with natural light.
The reflectance calculation device is
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow portion on the white reference model and a second partial reference image corresponding to a non-shadow portion adjacent to the shadow portion on the white reference model. Based on the difference between the data and the value of the white reference data corresponding to the shadow portion, the light intensity attenuation rate of the illumination light corresponding to the shadow portion of the object is calculated,
For white reference data representing the spectrum of the light intensity of the illumination light at the time of photographing the object, correction is performed using the attenuation rate of the light intensity,
The reflectance of the object is calculated using the corrected white reference data and the captured image data.

Yet another embodiment of the present invention is a program for causing a computer to execute a reflectance calculation method for calculating a reflectance spectrum distribution of an object by photographing the object illuminated with natural light. The program is
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow part on the white reference model of the white reference data, and a non-shadow near the shadow part on the white reference model of the white reference data Based on the difference from the second partial reference image data corresponding to the portion and the value of the white reference data corresponding to the shadow portion, the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object is calculated. Calculate
For white reference data representing the spectrum of the light intensity of the illumination light at the time of photographing the object, correction is performed using the attenuation rate of the light intensity,
A computer is caused to execute a process of calculating the reflectance of the object using the corrected white reference data and the captured image data.

  The reflectance calculation apparatus, the reflectance calculation method, and the program according to the above-described aspect can accurately calculate the reflectance for the shadow portion of the object without photographing a reference plate such as a white plate.

It is a figure explaining the reflectance calculation system using the reflectance calculation apparatus of this embodiment. It is a figure which shows the example of the white reference model which simulates the measuring object produced in this embodiment. It is a figure which shows the structure of the imaging device used with the reflectance calculation system of this embodiment, and the reflectance calculation apparatus of this embodiment. It is a figure explaining the reflectance calculation module in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the reference image obtained in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the reference image data obtained in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the white reference data obtained in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the reference image data obtained in the reflectance calculation apparatus of this embodiment. It is a figure explaining the example of the search of the pixel of the non-shadow part performed in the reflectance calculation apparatus of this embodiment. It is a figure explaining the example of the search of the pixel of the non-shadow part performed in the reflectance calculation apparatus of this embodiment. It is a figure explaining the other example of the search of the pixel of the non-shadow part performed in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the white reference data obtained in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the two partial reference image data obtained in the reflectance calculation apparatus of this embodiment. It is a figure which shows an example of the attenuation factor of the light intensity calculated in the reflectance calculation apparatus of this embodiment. (A)-(c) is a figure explaining the imaging | photography condition and measurement condition used in the reflectance calculation apparatus of this embodiment. It is a flowchart which shows the first half part of the flow of an example of the reflectance calculation method of this embodiment. It is a flowchart which shows the latter half part of the flow of an example of the reflectance calculation method of this embodiment.

Hereinafter, the reflectance calculation apparatus, the reflectance calculation method, and the program of the present invention will be described.
FIG. 1 is a diagram illustrating a reflectance calculation system (hereinafter referred to as a system) 10 using the reflectance calculation apparatus of the present embodiment.

(Reflectance calculation system)
The reflectance calculation system 10 illustrated in FIG. 1 includes an imaging device 12 and a reflectance calculation device 14. The imaging device 12 images the measurement object S using one cabbage growing in the field as the measurement object S and natural light as illumination light. The imaging device 12 has an HS camera. When the measurement object S is illuminated with natural light, the HS camera divides the reflected light reflected on the surface of the measurement object S into a plurality of wavelength bands, for example, several tens of bands or more using a bandpass filter or the like. An imaging device. Therefore, each pixel of the image photographed by the photographing device 12 has a spectrum of reflected light for each wavelength, that is, a reflection spectrum. Image data obtained by photographing with the photographing device 12 is sent to the reflectance calculating device 14.

The reflectance calculation device 14 obtains image data of a photographed image of the measurement object S photographed by the photographing device 12, while converting the white reference data representing the light intensity spectrum of the illumination light at the time of photographing the measurement object S. On the other hand, correction is performed in accordance with the shadow portion A (see FIG. 1) generated in the measuring object S. The reflectance calculation unit 14 further calculates the reflectance of the measuring object S for each pixel in the captured image using the corrected white reference data and the image data of the captured image. Since the reflectance of the measurement object S calculated in this way is a spectrum having a value for each wavelength, this reflectance estimates characteristics of the measurement object S, for example, cabbage maturity and sweetness characteristics. Used to do.
Since the reflectance calculation device 14 corrects the white reference data according to the shadow portion A (see FIG. 1) generated in the measurement object S, the illumination light on the surface including the shadow portion A of the measurement object S The spectrum of the light intensity can be obtained with high accuracy. For this reason, the reflectance in the shadow part A as well as the non-shadow part (bright part) of the measurement object S can be obtained with high accuracy, and the characteristics of the measurement object S can be estimated with high accuracy.

In such a system 10, in order to correct the white reference data, the attenuation rate R of the light intensity of the illumination light is calculated for each pixel as will be described later. The light intensity attenuation rate R is calculated as a spectrum having a distribution for each wavelength, and is used when calculating the light intensity spectrum of the illumination light in the shadow portion A from the white reference data data. In order to calculate the attenuation rate R of the light intensity, reference image data of the measurement object S obtained by photographing the measurement object S in advance with the photographing device 12 and white reference data of a white reference model are used. The white reference model is a model that simulates the shape of the measurement object S so as to have the same shadow under the same illumination conditions (light source altitude and direction) as in the previous shooting. The white reference model is a model in which the reflectance of the surface is 1, that is, the incident light is completely reflected on the surface. FIG. 2 shows a white reference model S ′ simulating the measurement object S.
Hereinafter, the reflectance calculation device 14 of the present embodiment and the method for calculating the reflectance by correcting the white reference data will be described in detail.

(Reflectance calculation device)
FIG. 3 is a diagram illustrating the configuration of the imaging device 12 and the reflectance calculation device 14.
The photographing apparatus 12 includes HS cameras (hereinafter simply referred to as cameras) 12a and 12b that photograph the measurement object S from different directions. The imaging object S is imaged from different directions using the cameras 12a and 12b in order to acquire the three-dimensional information of the measuring object S and create a white reference model S ′ as shown in FIG. is there.
Each of the cameras 12a and 12b acquires GPS position acquisition units 16a and 16b for acquiring information on the shooting positions of the cameras 12a and 12b, and information on the shooting date and time, in addition to the imaging device that images the measurement object S. Date and time acquisition units 17a and 17b. The cameras 12a and 12b send the photographed image data of the photographed measurement object S, the information on the obtained photographing position, and the information on the photographing date and time to the reflectance calculating device 14.

The reflectance calculation device 14 is formed by a computer having a CPU 20, a ROM 22, a RAM 24, a storage unit 26, and an input unit 28. In addition, the reflectance calculation device 14 is connected to an input operation system including a mouse and a keyboard (not shown) and a display (not shown) that displays a captured image and data and information during reflectance calculation on a screen.
The ROM 22 stores an OS and various types of software that are executed by the computer when activated.
The RAM 24 stores various processing data generated in the process of calculating reflectance described later. The storage unit 26 stores a program for calculating the reflectance of the measurement object S as will be described later, and stores data of the calculated reflectance. Furthermore, the memory | storage part 26 memorize | stores the white reference data measured in various measurement date and time and a measurement position, and the solar altitude table | surface and solar direction information in various date and time.
The input unit 28 is connected to the cameras 12a and 12b and a weather database 31 described later, and receives image data and various types of information. The CPU 20 controls and manages the operation of each part of the reflectance calculation device 14, and further controls and manages the processing of the reflectance module 30.

  The CPU 20 generates the reflectance calculation module 30 by executing the program stored in the storage unit 26. That is, the reflectance calculation module 30 is a software module that is generated when the CPU 26 reads and executes a program stored in the storage unit 26. As will be described later, the reflectance calculation module 30 includes an image acquisition unit 32, a white model creation unit 34, an attenuation rate calculation unit 36, a white reference data extraction unit 38, a data correction unit 40, and a reflectance calculation unit. 42. Therefore, when the CPU 20 executes the program, the CPU 20 performs the image acquisition unit 32, the white model creation unit 34, the attenuation rate calculation unit 36, the white reference data extraction unit 38, the data correction unit 40, and the reflectance calculation. The function of the unit 42 is substantially assumed.

  FIG. 4 is a diagram for explaining the reflectance calculation module 30. As shown in FIG. 4, the reflectance calculation module 30 includes an image acquisition unit 32, a white model creation unit 34, an attenuation rate calculation unit 36, a white reference data extraction unit 38, a data correction unit 40, and a reflectance. And a calculation unit 42.

The image acquisition unit 32 acquires captured image data input to the input unit 28. The photographed image data of the measuring object S photographed by the camera 12a is acquired as reference image data and distributed to the white model creating unit 34, and is also acquired as photographed image data used for calculating the reflectance and the reflectance calculating unit. 42. The image data of the measuring object S photographed by the camera 12b is distributed to the white model creation unit 34 as another reference image data.
The white model creation unit 34 creates a white reference model S ′ shown in FIG. 2 using the reference image data of the measurement object S photographed by the cameras 12a and 12b. Specifically, since the cameras 12a and 12b capture the measurement object S from different directions, the three-dimensional position information of the measurement object S is obtained from the image data of the two reference images captured by the cameras 12a and 12b. Can be obtained.

A well-known method is used for the calibration performed in advance in order to acquire the three-dimensional position information of the measuring object S. For example, calibration is performed using a method described in Japanese Patent Application Laid-Open No. 2006-250889. Moreover, the following method may be used as an example of calibration. In other words, a checkerboard is photographed in advance using the cameras 12a and 12b, and two-dimensional position coordinate sequences in the photographing space at the intersection of the checkers and two-dimensional position coordinate sequences in each photographed image are used. A matrix and a conversion parameter value for converting the two-dimensional position coordinates in the two photographed images into the three-dimensional position coordinates in the photographing space are identified.
The matrix and the value of the conversion parameter obtained by calibration are stored in the storage unit 26.

The white model creation unit 34 reads the stored matrix and conversion parameter values, and obtains a three-dimensional position from the two-dimensional position coordinates of each position of the measuring object S in the two reference images captured by the cameras 12a and 12b. Calculate the coordinates.
The white model creation unit 34 obtains the external shape of the measuring object S by connecting the points in the imaging space defined by the calculated three-dimensional position coordinates by straight lines or curves. The appearance shape can be a smooth appearance shape simulating the measuring object S by creating an interpolation point in the middle of the straight line or curve connecting the points. Thus, a virtual model simulating the measuring object S is obtained.

5A and 5B are diagrams illustrating an example of the reference image G _ref and the reference image data of the measurement object S obtained by photographing the measurement object S with the camera 12a. 5A and 5B exemplify a case where a reference image to be photographed has a size of 10 pixels × 10 pixels and each pixel has a reflection spectrum of wavelengths λ _{1 to} λ ₁₅ for easy understanding. The actual number of pixels of the reference image and the number of spectral wavelengths are larger than 10 pixels × 10 pixels and 15 wavelengths.
The upper left pixel of the reference image G _ref of the measured measurement object S shown in FIG. 5A is P (1,1), the lower right pixel is P (10,10), and the upper right pixel is P ( 10 and 1), when the positions of the respective pixels are determined, the pixels P (1,1) to P (10,10) have wavelengths λ _{1 to} λ ₁₅ for each pixel as shown in FIG. 5B. Has a value. In the example shown in FIG. 5B, each pixel is sampled with 8-bit gradation and has a value of 0 to 255 (value 255 is the highest gradation value).

The white model creation unit 34 further gives the reflectance 1 to the surface of the three-dimensional virtual model having the appearance shape of the measurement object S.
On the other hand, the attribute information (shooting date and time, shooting position) of the shooting condition of the reference image G _ref is sent from the cameras 12a and 12b and stored in the storage unit 26. Using the solar altitude table and the information on the solar orientation stored in the storage unit 26, the solar altitude and the solar orientation that are closest to the imaging conditions are obtained. The white model creation unit 34 determines the extracted solar altitude and solar orientation as the same illumination condition as the illumination condition of the measurement object S when the reference image G _ref is acquired, and for the created three-dimensional virtual model Then, shadow processing is performed using a well-known ray tracing method. For example, when shading processing is performed with 8-bit gradation (0 to 255), each pixel in the non-shadow part (bright part) on the virtual model has a constant value of 255 (maximum gradation value) at each wavelength. . Each pixel in the shaded area on the virtual model has a constant value of 255 (maximum gradation value) or less at each wavelength. The virtual model subjected to the shading process is a model simulating the shape of the measurement object S, and the white reference model S ′ having the same shadow by reproducing the illumination condition at the time of photographing the reference image G _ref. It has become. That is, the white reference model S ′ shown in FIG. 2 is obtained by the shading process.

The white model creation unit 34 renders the three-dimensional virtual model on which the shading process has been performed so as to be a two-dimensional image viewed from one of the cameras 12a and 12b, for example, the field of view of the camera 12a. In this way, rendering is performed so that a two-dimensional image viewed in the field of view of the camera 12a is obtained, and the field of view of the camera 12a is used as a reference field of view as the field of view of the captured image when obtaining the reflectance of the measurement object S. Because. Therefore, when the field of view of the camera 12b is used as the field of view of the captured image when determining the reflectance of the measurement object S, rendering is performed so that a two-dimensional image viewed in the field of view of the camera 12b is obtained.
Thus, the white model creation unit 34 obtains the white reference data D _w is the image data of the two-dimensional image of the white reference model S 'as seen from the camera 12a. The acquired white reference data _Dw is stored in the storage unit 26.

On the right side of Figure 5A, an example of the rendered two-dimensional images G _w to view a virtual model of a three dimensional shading process has been performed in the field of view of the camera 12a it is shown. Further, FIG. 6 shows an example of a white reference data D _w of the two-dimensional image G _w is shown. The light intensity of the illumination light applied to the white reference model S ′ is set so that the gradation value is the highest (255 for 8-bit gradation) in any of the wavelengths λ _{1 to} λ _{15 in} the non-shadow portion. Has been.
Accordingly, the white reference data D _w is the same value at the wavelength lambda ₁ to [lambda] ₁₅ in any of the pixel. In white reference data D _w shown in FIG. 6, the pixel P (3,2) ~ pixel P (5,2) is not in a highest gray level value, a shadow portion.

Attenuation rate calculating section 36, shade portion from the white reference data D _w extracts (gradation value portion not 255), further, the shade of the white reference model S 'of the reference image data of the reference image G _ref the partial reference image data D _sp1 corresponding to the portion, to calculate the difference between the partial reference image data D _sp2 corresponding to Hikage portion on the white reference model S 'adjacent to the shadow portion. Based on the calculation result of the difference, the attenuation rate calculation unit 36 calculates the attenuation rate R of the light intensity of the illumination light incident on the shadow portion of the measurement object S. Specific calculation of the light intensity attenuation rate R will be described later. The calculated light intensity attenuation rate R is stored in the storage unit 26.

Partial reference image data D _sp1 and partial reference image data D _sp2 is because it is the image data of the captured reference image G _ref by the camera 12a, as shown in Figure 5B, includes a reflection spectrum for each pixel. Accordingly, the light intensity attenuation rate R calculated using the partial reference image data _Dsp1 and the partial reference image data _Dsp2 also has a value for each wavelength for each pixel.

FIG. 7 shows an example of the reference image data D _ref of the reference image G _ref used for calculating the light intensity attenuation rate R. White reference data D _w shown in FIG. 6, the pixel P (3,2) ~ pixel P (5,2) is an anion moiety. Therefore, in the reference image data D _ref shown in FIG. 7, the data of the pixels P (3, 2) to P (5, 2) corresponding to the shadow portion on the white reference model S ′ is the partial reference image data D _sp1. It becomes. FIG. 7 shows a state in which the data of the pixel P (3, 2) is extracted as the partial reference image data _Dsp1 .
On the other hand, the pixel corresponding to the non-shadow part adjacent to the shadow part is selected as follows. When there are a plurality of pixels such as the pixel P (3, 2) to the pixel P (5, 2) as the shadow portion, a non-shadow portion pixel adjacent to each pixel is selected. Hereinafter, an example of selecting a pixel in the non-shadow part on the white reference model S ′ adjacent to the pixel P (3, 2) that is a shadow part, that is, a pixel having the highest gradation value on the white reference model S ′. explain. The pixel P (4,2) and the pixel P (5,2) are also selected in the same manner in the non-shadow area.

As shown in FIGS. 9A and 9B, the attenuation rate calculation unit 36 is a peripheral pixel centered on the pixel P (3, 2) and has the highest gradation value in the white reference data _Dw . Search for a pixel. In this case, first, the pixel P (3, 1) and the pixel P (2, 2) are extracted as adjacent non-shadowed pixels. At this time, the attenuation rate calculation unit 36 determines whether or not the reflection spectra of the pixel P (3, 1) and the pixel P (2, 2) are similar to the reflection spectrum of the pixel P (3, 2). That is, a pixel that is a non-shadow part approximate to the pixel P (3, 2) located on the white reference model S ′ and closest to the pixel P (3, 2) is searched. The similarity determination of the reflection spectrum is performed by calculating the following similarity.

The value at each wavelength of the reflection spectrum of the pixel P (3,2) is SP1 _{P (3,2) λi} (i = 1 to an integer of 1 to 15), and the reflection spectrum of the pixel P (j, k) whose similarity is to be examined. When the value at each wavelength is SP1 _{P (j, k) λi} (i = 1 to an integer of 1 to 15), the attenuation rate calculation unit 36 calculates the similarity according to the following equation (1). In the following formula (1), N is the number of wavelengths, and when wavelengths λ _{1 to} λ ₁₅ are used, N = 15. That is, the similarity is obtained by summing the absolute values of the difference between the values of the same wavelengths between the reflection spectrum of the partial reference image data SP1 and the reflection spectrum of the partial reference image data SP2.

The attenuation rate calculation unit 36 determines whether there is similarity based on whether the calculated similarity is equal to or greater than a preset threshold value. When the similarity is equal to or greater than the threshold value, the pixels are determined to be similar. The threshold is set to 0.01, for example. For example, the similarity value between the pixel P (3,2) and the pixel P (3,1) shown in FIGS. 8A and 8B is 0.0055, and the similarity is set when 0.01 is set as the threshold value. Since the degree is less than 0.01, it is determined that they are not similar. The similarity value between the pixel P (3, 2) and the pixel P (2, 2) shown in FIGS. 8A and 8B is also 0.0055, which is less than 0.01 set as the threshold value. It is determined not to.
In this way, the attenuation rate calculation unit 36 searches for pixels in the non-shadow part similar to the pixel P (3, 2) in order from the pixel close to the pixel P (3, 2). In FIG. 9, as a result of the search, the pixel P (6, 2) is a non-shadowed pixel similar to the pixel (3, 2) and is selected as the closest pixel. The similarity between the pixel P (3, 2) and the pixel P (6, 2) is 0.020, which is equal to or greater than 0.01 set as the threshold, and thus exceeds the threshold. In this way, by pixel closest Hikage portion to the pixel of the shade portion P (3,2) P (6,2) is selected, partial reference image data D _sp2 is selected.

In addition, although the order of the pixel to search is performed in the order close | similar to pixel P (3, 2), when the some pixel to search leaves the same distance from pixel P (3, 2), the order of the search with respect to several pixels Is not particularly limited. For example, the search may be performed preferentially from the pixel number having the smallest column number, or the search may be performed preferentially from the pixel position having the smallest row number, and may be determined by other methods. Searches may be performed in the order in which they were found. The column number of the pixel position is 3 in the case of the pixel P (3, 1), for example, and the row number of the pixel position is 1 in the case of the pixel P (3, 1), for example.
In this manner, the attenuation rate calculating unit 36 may select the partial reference image data D _sp2 of Hikage part on the measuring object S near the shadow portion.
In the present embodiment, the similarity determination between the pixels is performed using Expression (1), but the similarity determination may be performed using a correlation coefficient. Similar determinations can also be made using other known methods for calculating similarity.

The attenuation rate calculation unit 36 calculates the attenuation rate R of the light intensity of the illumination light corresponding to the shadow portion of the measurement object S based on the difference between the partial reference image data _Dsp1 and the partial reference image data _Dsp2. .
In the example above the pixel P (3,2), the attenuation factor calculating section 36, values SP0 λi _(i = 1~15 pixel P (3,2) value white reference data D _w shown in FIG. 10A Integer), the value SP1 _λi (integer of i = 1 to 15) of the pixel P (3, 2) of the partial reference image data D _sp1 shown in FIG. 10B and the pixel P (6, 2) of the partial reference image data D _sp2 ) Value SP2 _{P (6,2) λi} (i = 1 to 15), the light intensity attenuation rate R is calculated according to the following equation (2).
_{R λi = SP0 λi - (SP1} λi -SP2 P (6,2) λi) (2)

The pixel P (3, 2) is a shadow part of the white reference model S ′, and is therefore a shadow part on the measurement object S. If the position of the pixel P (3, 2) on the measuring object S is a non-shadow part, the pixel P (3, 2) is the pixel P (6, 2) closest to the pixel P (3, 2). Is considered to have the same reflection spectrum. For this reason, the difference between the reflection spectrum of the pixel P (3, 2) and the reflection spectrum of the pixel P (6, 2) is influenced by the shadow at the position of the pixel P (3, 2) on the measurement object S. Information that attenuates the light intensity.
Therefore, the attenuation rate calculation unit 36 can calculate the attenuation rate R of the light intensity by performing the calculation shown in the above equation (2).

FIG. 11 shows the light at the pixel P (3,2) calculated using SP0 _λi , SP1 _λi , SP2 _{P (6,2) λi} (i = 1 to 15 ₎ shown in FIGS. 10A and 10B. An example of the calculation result of the intensity attenuation rate R is shown. Such a light intensity attenuation rate R is calculated for each pixel in the shadow portion. Therefore, the attenuation rate R of the light intensity is also calculated for the pixel P (4, 2) and the pixel P (5, 2).

The white reference data extraction unit 38 extracts white reference data of illumination light when the measurement target S is photographed in order to obtain the reflectance of the measurement target S. Specifically, the white reference data extraction unit 38 selects attribute information (measurement date and time, measurement date and time, white reference data) from the white reference data measured at various dates and times stored in the storage unit 26. White reference data whose measurement position and weather information are closest to the attribute information (shooting date and time, shooting position, and weather information) of the shooting conditions at the time of shooting of the measurement object S is extracted. Since the white reference data is associated with the measurement date and time and the measurement position at which the white reference data is measured, when the measurement position and the measurement date and time are acquired, the white reference data extraction unit 38 obtains the measurement time and date from the weather database 31. Weather information such as sunny, cloudy and rainy can be acquired. Similarly, when the shooting date and time and the shooting position are acquired, the white reference data extraction unit 38 can acquire weather information such as sunny, cloudy, rainy, etc. at the time of shooting from the weather database 31. FIG. 12A shows an example of shooting conditions. Weather (cloudy) information is acquired from the weather database 31 from the shooting position and shooting date and time. FIG. 12B shows an example of measurement conditions stored in the weather database 31.
Therefore, the white reference data extraction unit 38 can extract white reference data having a measurement condition (measurement date / time, measurement position, weather information) that is closest to the attribute information (shooting date / time, shooting position, weather information) of the shooting condition. it can. In the extraction of the white reference data, the white reference data extraction unit 38 quantifies and standardizes the date and time information, for example, as the elapsed time (seconds) from a certain reference date, and converts the latitude and longitude of the shooting position into numerical values. Furthermore, for weather information, as shown in FIG. 12C, for example, as shown in FIG. 12 (c), the degree of shielding is such that the clearness is 0, the cloudiness is 0.5, and the rain is 0.3. Digitize and standardize. The white reference data extraction unit 38 also digitizes and standardizes the shooting date / time, shooting position, and weather information of the shooting conditions. Here, normalization refers to conversion so that the average value of measurement values is 0 and the standard deviation is 1.

  Further, the white reference data extraction unit 38 extracts white reference data having a numerical value that most closely approximates the numerical value that is standardized for the imaging conditions among the numerical values that are standardized for many measurement conditions. The most approximate numerical value is, for example, when a spatial coordinate system is assumed so that the above-mentioned standardized numerical values of the shooting conditions and measurement conditions correspond to the position coordinates of the points in the space, a plurality of measurements are performed in this spatial coordinate system. The coordinate value of the point closest to the position of the point corresponding to the imaging condition among a plurality of points corresponding to the condition.

  In this embodiment, three attribute information of measurement date / time, measurement position, and weather information is used to extract the white reference data. However, any attribute information of the measurement date / time, measurement position, and weather information is fixed. If there is, white reference data may be extracted using the remaining attribute information. Further, in the present embodiment, instead of the above similarity, white reference data having a measurement condition having the highest correlation coefficient between the attribute information and the attribute information of the shooting condition may be extracted. The data extraction method is not particularly limited.

The data correction unit 40 corrects the white reference data extracted by the white reference data extraction unit 38 using the light intensity attenuation rate R calculated by the attenuation rate calculation unit 36. Since the light intensity attenuation rate R relates to the shadow portion generated in the measurement object S, the light intensity of the illumination light is corrected according to the shadow portion of the photographed measurement object S.
Data correction unit 40, the wavelengths lambda _i of the white reference data SP3 extracted the value in (i = 1 to 15 integer) and SP3 _.lambda.i, each wavelength of the attenuation factor R of the light intensity λ _{i (i} = 1~ the value in integer) of 15 and R _.lambda.i time, which was the wavelength λ _{i (i} = 1~15 SP4 _λi values at integer) of the white reference data SP4 corrected, according to the following equation (3), the white reference Correct the data.
SP4 _λi = SP3 _λi -R _λi (3)

The reflectance calculation unit 42 calculates the reflectance spectrum of the measuring object S using the corrected white reference data and the captured image data captured by the camera 12a. Specifically, the captured image data has a value of the reflection spectrum for each pixel, and the light intensity of the illumination light has a value for each wavelength λ _i according to the pixel in the shadow portion of the measurement object S. The calculation unit 42 calculates the reflectance by performing, for each pixel, dividing the value at each wavelength λ _i of the reflection spectrum by the value at the corresponding wavelength λ _i of the corrected white reference data. The calculated reflectance is used, for example, for estimating the characteristics of the measurement object S.

(Reflectance calculation method)
In such a reflectance calculation device 14, a reflectance calculation method as shown in FIGS. 13A and 13B is performed.
First, in order to obtain a captured image of the measuring object S with the cameras 12a and 12b, the reflectance calculation device 14 determines whether or not the cameras 12a and 12b have captured images from two different directions (step S10). The reflectance calculation unit 14 waits until shooting by the cameras 12a and 12b is performed. The captured images acquired by shooting are sent from the cameras 12a and 12b to the image acquisition unit 32. The image acquisition unit 32 acquires the sent captured image as a captured image for calculating the reflectance or as a reference image _Gref for calculating the light intensity attenuation rate R.

When shooting with the cameras 12a and 12b is performed, the white model creation unit 34 acquires shooting conditions sent from the cameras 12a and 12b, specifically, shooting date and position information (step S20).
Further, the white model creation unit 34 obtains the solar altitude and azimuth at the time of shooting from the shooting date and time and the shooting position from the solar altitude table and the information on the sun azimuth stored in the storage unit 26 (step S30). The storage unit 26 includes a table in which information on the solar altitude table and solar orientation at various dates and times and various positions is recorded. A well-known expression for automatically calculating the solar altitude and orientation from the imaging date and time and the location. May be used to determine the solar altitude and orientation during shooting.

Next, the white model creation unit 34 performs three-dimensional measurement modeling (step S40). Specifically, the white model creation unit 34 uses a reference image G _ref taken from two different directions photographed by the cameras 12a and 12b, and has a three-dimensional virtual model having a smooth external shape simulating the measurement object S. Create Creation of the virtual model is performed by the method described above.
The white model creation unit 34 further applies a shading process to the three-dimensional virtual model using the solar altitude and orientation obtained in step S30 so as to have the same shadow as the measurement object S, thereby obtaining a white reference model. Create S '. White model creation unit 34 creates the white reference data D _w from the white reference model S '(step S50). The white reference data _Dw is data of a two-dimensional image related to the white reference model S ′ having a field of view when the measurement object S is photographed from the position of the camera 12a.

Next, the attenuation rate calculation unit 36 determines whether or not the attenuation rate R of the light intensity has been calculated for all the pixels in the shadow portion of the reference image G _ref of the measurement object S photographed by the camera 12a (step S60). ). When the result of the determination is negative (NO in step S60), the attenuation rate calculation unit 36 determines that the attenuation rate calculation unit 36 does not calculate the attenuation rate R of the light intensity, and is a partial reference image of a shadow pixel. Data _Dsp1 is extracted (step S70). In the example shown in FIG. 7, the data of the pixels P (3, 2) to P (5, 2) is the target of the reference image data _Dsp1 .
Further, the attenuation rate calculation unit 36 selects a non-shadow portion pixel adjacent to the currently focused pixel of the shadow portion for which the light intensity attenuation rate R has not been calculated (step S80), and the selected pixel portion. Reference image data _Dsp2 is extracted (step S90). Further, the attenuation rate calculation unit 36 calculates the similarity between the partial reference image data _Dsp1 and the partial reference image data _Dsp2 (step S100). The calculation of the similarity is performed by the method described above.

Next, the attenuation rate calculation unit 36 determines whether or not the calculated similarity value is greater than or equal to a preset threshold value (step S110). Thereby, it is determined whether or not the selected pixel is a non-shadow portion pixel on the measurement object S. When the similarity value is equal to or greater than a preset threshold value (YES in step S110), the attenuation rate calculation unit 36 uses the partial reference image data _Dsp2 of the selected pixel together with the partial reference image data _Dsp1. Then, the attenuation rate R of the light intensity for each wavelength caused by the shadow is calculated according to the above equation (2) (step S120). If the similarity value is less than the preset threshold value (NO in step S110), attenuation factor calculation unit 36 changes the selected pixel (step S130) and returns to step S80.
Such processing of step S60 to step S130 is repeated for each pixel in the shadow portion until the light intensity attenuation rate R is calculated for all the pixels in the shadow portion.
When the light intensity attenuation rate R is calculated for all the pixels in the shadow portion (YES in step S60), the image acquisition unit 32 acquires the captured image data of the measurement object S, and proceeds to the reflectance calculation process. . First, the white reference data extraction unit 38 acquires shooting conditions (shooting date and time, shooting position) when the measuring object S is shot with the camera 12a (step S140). The shooting conditions are those sent from the camera 12a to the reflectance calculation device 14 during shooting.
The white reference data extraction unit 38 extracts the weather information at the time of shooting based on the shooting date and time and the shooting position acquired from the weather database 31 and measures the measurement conditions (measurement) closest to the shooting date and time, the shooting position, and the weather at the time of shooting. White reference data having date and time, measurement position, and weather at the time of measurement) is extracted (step S150). The extraction of the white reference data is performed by the method described above.

  Next, the data correction unit 40 corrects the white reference data according to the above equation (3) using the extracted white reference data and the light intensity attenuation rate R obtained in step S120 (step S160). The correction is performed on the pixels in the shadow portion of the measuring object S.

  Finally, the reflectance calculation unit 42 calculates the reflectance using the corrected white reference data and the reflection spectrum of the captured image captured by the camera 12a (step S170). The reflectance has a value for each wavelength. Therefore, the characteristic of the measuring object S at the time of photographing can be estimated from the reflectance of the measuring object S using the characteristic index of the measuring object S.

In the present embodiment, the measurement object S is one object, but the measurement object S is not limited to one object. For example, a measurement object may be obtained by distributing a plurality of similar objects. In FIG. 1, one cabbage is cited as the measurement object S, but a plurality of growing cabbages planted in the field may be photographed as one measurement object S using a fixed point camera. In such a case, the white reference model S ′ can be a simple model in which a plurality of ellipsoids are arranged on a horizontal plane so as to correspond to the cabbage distribution. Using such a measuring object S is effective in that the reflectance of a plurality of objects can be calculated simultaneously and relatively accurately, and the characteristics of the plurality of objects can be estimated at once. .
In the present embodiment, the weather information is acquired from the weather database 31. However, the illuminance of the illumination light may be directly measured with the illuminometer when the measurement object S is photographed, and used when extracting the white reference data. . In this case, the illuminance information is used together with the shooting date / time and shooting position information, and one white reference data from among a large number of white reference data in which the measurement date / time, measurement position, and illuminance information at the time of measurement are associated as measurement conditions. Data is extracted.

In the present embodiment, the white reference model S ′ is photographed by the cameras 12a and 12b to create a three-dimensional virtual model that simulates the shape of the measurement object S. to prepare a three-dimensional white reference model by taking an image of the white reference model shaded may obtain white reference data D _w.

In addition, the memory | storage part 26 of the reflectance calculation apparatus 14 of this embodiment memorize | stores the following program which performs the process of the said reflectance calculation method. That is, the program
Captured image data including a reflection spectrum for each pixel is acquired as reference image data D _{ref by} capturing the measurement object S, and has the shape simulating the shape of the measurement object S, and the same illumination condition as that of the capture Obtain white reference data D _w of a white reference model S ′ having the same shadow below;
'And the first partial reference image data D _sp1 corresponding to shadow portions of the white reference model S white reference data D _w' white reference model S white reference data D _w of the reference image data D _ref on the shade and the difference between the partial reference image data D _sp2 corresponding to Hikage portion adjacent to the portion, on the basis of the white reference data D _w corresponding to the negative part, the light intensity of the illumination light in the shadow portion of the measuring object S The attenuation rate R of
The white reference data representing the spectrum of the light intensity of the illumination light at the time of photographing the measuring object S is corrected according to the shadow portion generated in the measuring object S using the light intensity attenuation rate R,
The processing includes calculating the reflectance spectrum of the measurement object using the corrected white reference data and captured image data.

As described above, the reflectance calculation apparatus 14 of the present embodiment acquires the reference image data D _ref including the reflection spectrum for each pixel by photographing the measurement object S, and further, the white reference of the white reference model S ′. Data _Dw is acquired. At this time, the reflectance calculating unit 14, the partial reference image data D _sp1 corresponding to shadow portions, and the difference between the partial reference image data D _sp2 corresponding to Hikage portion close to the shadow portion, corresponding to the negative portion Based on the value of the white reference data _Dw , the attenuation rate R of the light intensity of the illumination light is calculated. Therefore, the reflectance can be accurately calculated for the shadow portion of the measuring object S without photographing a reference plate such as a white plate as in the prior art.

Further, the attenuation rate calculating unit 36, the selection of Hikage portion, is performed based on the similarity between the reflection spectrum of the reflection spectrum and the partial reference image data D _sp2 partial reference image data D _sp1, the exact light The intensity attenuation rate R can be calculated.

The attenuation factor calculation unit 36 is based on the similarity obtained by summing the absolute values of the differences between the spectrum values of the same wavelength bands of the reflection spectrum of the partial reference image data _{Dsp1 and} the reflection spectrum of the partial reference image data _Dsp2. Thus, the selection of the non-shadow portion can be performed, so that the exact non-shadow portion can be selected.

  The attenuation factor calculation unit 36 uses the three-dimensional virtual model of the measurement object created based on the captured image obtained by photographing the measurement object S from at least two directions as the white reference model, and thus actually creates the model. Therefore, a white reference model can be easily obtained.

  The white reference data extraction unit 38 extracts the white reference data from the storage unit 26 using the shooting date and time, the shooting position, and the weather at the time of shooting. Can be extracted.

  The said embodiment discloses the content shown below.

(Appendix 1)
A reflectance calculation device that calculates the reflectance of the object by photographing the object illuminated with natural light,
An image acquisition unit that acquires captured image data of an object illuminated with natural light, including a reflection spectrum of the object for each pixel;
The white reference data of the white reference model that acquires the captured image data as reference image data of the object, and further has a shape that simulates the shape of the object and has the same shadow under the same illumination conditions as the image capturing Of the reference image data, the first partial reference image data corresponding to the shadow part on the white reference model, and the second corresponding to the non-shadow part adjacent to the shadow part on the white reference model. An attenuation rate calculation unit that calculates the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object based on the difference between the partial reference image data and the value of the white reference data corresponding to the shadow portion When,
A data correction unit that corrects the white reference data representing the light intensity spectrum of the illumination light at the time of photographing the object using the attenuation rate of the light intensity;
A reflectance calculation apparatus comprising: a reflectance calculation unit that calculates the reflectance of the object using the corrected white reference data and the captured image data.

(Appendix 2)
The attenuation factor calculation unit performs the selection of the non-shadow part based on the similarity between the reflection spectrum of the first partial reference image data and the reflection spectrum of the second partial reference image data. The reflectance calculation apparatus according to 1.

(Appendix 3)
The attenuation factor calculation unit adds the absolute values of the difference between the values of the same wavelengths between the reflection spectrum of the first partial reference image data and the reflection spectrum of the second partial reference image data. The reflectance calculation apparatus according to attachment 2, wherein the non-shadow portion is selected based on the obtained similarity.

(Appendix 4)
Any one of appendices 1 to 3, wherein the attenuation factor calculation unit uses, as the white reference model, a three-dimensional virtual model of the object created based on a captured image obtained by photographing the object from at least two directions. The reflectance calculation apparatus according to item.

(Appendix 5)
Furthermore, a database unit that records a plurality of white reference data in association with measurement conditions including at least one attribute information of date and time, position, and weather when each white reference data is measured,
Using the imaging condition including at least one attribute information of the imaging date and time, the imaging position, and the weather at the time of imaging when the object is imaged to calculate the reflectance spectrum distribution, from the database unit, the plurality of The reflectance calculation apparatus according to any one of appendices 1 to 4, further including a white reference data extraction unit that extracts one of the white reference data.

(Appendix 6)
A reflectance calculation method in a reflectance calculation apparatus for calculating the reflectance of the object by photographing the object illuminated with natural light,
The reflectance calculation device is
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow portion on the white reference model and a second partial reference image corresponding to a non-shadow portion adjacent to the shadow portion on the white reference model. Based on the difference between the data and the value of the white reference data corresponding to the shadow portion, the light intensity attenuation rate of the illumination light corresponding to the shadow portion of the object is calculated,
For white reference data representing the spectrum of the light intensity of the illumination light at the time of photographing the object, correction is performed using the attenuation rate of the light intensity,
A reflectance calculation method, wherein the reflectance of the object is calculated using the corrected white reference data and the captured image data.

(Appendix 7)
The reflectance calculation according to claim 6, wherein the non-shadow part is selected based on a similarity between a reflection spectrum of the first partial reference image data and a reflection spectrum of the second partial reference image data. Method.

(Appendix 8)
The selection of the non-shadow part is to sum the absolute value of the difference between the values of the same wavelengths between the reflection spectrum of the first partial reference image data and the reflection spectrum of the second partial reference image data. The reflectance calculation method according to claim 6, wherein the reflectance calculation method is performed based on the similarity obtained by the following.

(Appendix 9)
The reflection according to any one of appendices 6 to 8, wherein a three-dimensional virtual model of the object created based on a photographed image obtained by photographing the object from at least two directions is used as the white reference model. Rate calculation method.

(Appendix 10)
Further, the plurality of white reference data in the database unit, wherein the plurality of white reference data are recorded in association with measurement conditions including at least one attribute information of date, time, position, and weather when each white reference data is measured. Appendices 7 to 10 in which the white reference data is extracted using a shooting condition including at least one attribute information of a shooting date and time, a shooting position, and a weather at the time of shooting the object. The reflectance calculation method according to any one of the above items.

(Appendix 11)
A program for causing a computer to execute a reflectance calculation method for calculating a reflectance spectrum distribution of the object by photographing the object illuminated with natural light,
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow part on the white reference model of the white reference data, and a non-shadow near the shadow part on the white reference model of the white reference data Based on the difference from the second partial reference image data corresponding to the portion and the value of the white reference data corresponding to the shadow portion, the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object is calculated. Calculate
For white reference data representing the spectrum of the light intensity of the illumination light at the time of photographing the object, correction is performed using the attenuation rate of the light intensity,
A program that causes a computer to execute a process of calculating the reflectance of the object using the corrected white reference data and the captured image data.

  As described above, the reflectance calculation device, the reflectance calculation method, and the program according to the present invention have been described in detail. However, the present invention is not limited to the above-described embodiment, and various improvements and modifications can be made without departing from the gist of the present invention. Of course.

DESCRIPTION OF SYMBOLS 10 Reflectance calculation system 12 Imaging device 12a, 12b Hyperspectral camera 14 Reflectance calculation device 16a, 16b GPS position acquisition unit 17a, 17b Date and time acquisition unit 20 CPU
22 ROM
24 RAM
26 storage unit 28 input unit 30 reflectance calculation module 31 weather database 32 image acquisition unit 34 white model creation unit 36 attenuation rate calculation unit 38 white reference data extraction unit 40 data correction unit 42 reflectance calculation unit

Claims (6)

A reflectance calculation device that calculates the reflectance of the object by photographing the object illuminated with natural light,
An image acquisition unit that acquires captured image data of an object illuminated with natural light, including a reflection spectrum of the object for each pixel;
The white reference data of the white reference model that acquires the captured image data as reference image data of the object, and further has a shape that simulates the shape of the object and has the same shadow under the same illumination conditions as the image capturing Of the reference image data, the first partial reference image data corresponding to the shadow part on the white reference model, and the second corresponding to the non-shadow part adjacent to the shadow part on the white reference model. An attenuation rate calculation unit that calculates the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object based on the difference between the partial reference image data and the value of the white reference data corresponding to the shadow portion When,
A plurality of white reference data representing a spectrum of light intensity of illumination light at the time of photographing the object is related to a measurement condition including at least one attribute information of date and time, position, and weather when each white reference data is measured The database part recorded with
Using the imaging condition including at least one attribute information of the imaging date and time, the imaging position, and the weather at the time of imaging when the object is imaged to calculate the reflectance spectrum distribution, from the database unit, the plurality of A white reference data extraction unit for extracting one of the white reference data;
A data correction unit that corrects the white reference data extracted by the white reference data extraction unit using the attenuation rate of the light intensity;
A reflectance calculation apparatus comprising: a reflectance calculation unit that calculates the reflectance of the object using the corrected white reference data and the captured image data.   The attenuation rate calculation unit selects the non-shadow part based on a similarity between a reflection spectrum of the first partial reference image data and a reflection spectrum of the second partial reference image data. Item 2. The reflectance calculation apparatus according to Item 1.   The attenuation factor calculation unit adds the absolute values of the difference between the values of the same wavelengths between the reflection spectrum of the first partial reference image data and the reflection spectrum of the second partial reference image data. The reflectance calculation apparatus according to claim 2, wherein the non-shadow portion is selected based on the obtained similarity.   The said attenuation factor calculation part uses any one of the three-dimensional virtual model of the said object created based on the picked-up image which image | photographed the said object from at least 2 directions as said white reference model. The reflectance calculation apparatus according to item 1. A reflectance calculation method in a reflectance calculation apparatus for calculating the reflectance of the object by photographing the object illuminated with natural light,
The reflectance calculation device is
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow portion on the white reference model and a second partial reference image corresponding to a non-shadow portion adjacent to the shadow portion on the white reference model. Based on the difference between the data and the value of the white reference data corresponding to the shadow portion, the light intensity attenuation rate of the illumination light corresponding to the shadow portion of the object is calculated,
A plurality of white reference data representing a spectrum of light intensity of illumination light at the time of photographing the object is related to a measurement condition including at least one attribute information of date and time, position, and weather when each white reference data is measured From the recorded database part, using the shooting conditions including at least one attribute information of the shooting date and time, shooting position, and weather at the time of shooting the object to calculate the reflectance spectrum distribution, Extracting one of the plurality of white reference data;
The extracted white reference data is corrected using the attenuation rate of the light intensity,
A reflectance calculation method, wherein the reflectance of the object is calculated using the corrected white reference data and the captured image data. A program for causing a computer to execute a reflectance calculation method for calculating a reflectance spectrum distribution of the object by photographing the object illuminated with natural light,
The captured image data of the target object including a reflection spectrum for each pixel is acquired as reference image data by capturing the target object, and has the shape simulating the shape of the target object, and the same illumination conditions as the capturing To obtain the white reference data of the white reference model with the same shadow,
Of the reference image data, first partial reference image data corresponding to a shadow part on the white reference model of the white reference data, and a non-shadow near the shadow part on the white reference model of the white reference data Based on the difference from the second partial reference image data corresponding to the portion and the value of the white reference data corresponding to the shadow portion, the attenuation rate of the light intensity of the illumination light corresponding to the shadow portion of the object is calculated. Calculate
A plurality of white reference data representing a spectrum of light intensity of illumination light at the time of photographing the object is related to a measurement condition including at least one attribute information of date and time, position, and weather when each white reference data is measured From the recorded database part, using the shooting conditions including at least one attribute information of the shooting date and time, shooting position, and weather at the time of shooting the object to calculate the reflectance spectrum distribution, Extracting one of the plurality of white reference data;
The extracted white reference data is corrected using the attenuation rate of the light intensity,
A program that causes a computer to execute a process of calculating the reflectance of the object using the corrected white reference data and the captured image data.