WO2023273412A1 - 一种光谱反射率的确定方法、装置及设备 - Google Patents

一种光谱反射率的确定方法、装置及设备 Download PDF

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WO2023273412A1
WO2023273412A1 PCT/CN2022/080525 CN2022080525W WO2023273412A1 WO 2023273412 A1 WO2023273412 A1 WO 2023273412A1 CN 2022080525 W CN2022080525 W CN 2022080525W WO 2023273412 A1 WO2023273412 A1 WO 2023273412A1
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target point
target
reflectance
depth map
reflection plate
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PCT/CN2022/080525
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English (en)
French (fr)
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师少光
吕晓波
刘敏
张雅琴
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奥比中光科技集团股份有限公司
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Publication of WO2023273412A1 publication Critical patent/WO2023273412A1/zh
Priority to US18/373,888 priority Critical patent/US20240020883A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G06T7/593—Depth or shape recovery from multiple images from stereo images
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
    • G06T7/85—Stereo camera calibration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G06T2207/10012—Stereo images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image

Definitions

  • the present application belongs to the field of optical technology, and in particular relates to a method, device and equipment for determining spectral reflectance.
  • an indirect measurement method When measuring the spectral reflectance, an indirect measurement method can be used.
  • the indirect measurement method directly uses the ratio of the target gray value detected by the spectral detection equipment to the gray value of the reference diffuse reflection plate to calculate the spectral reflectance.
  • an important prerequisite is that the irradiance received by the object to be measured should be equal to the irradiance received by the diffuse reflector, that is, the diffuse reflector should be as close as possible to the object to be measured, so as to obtain the final measurement results.
  • the structural changes on the surface of the object to be measured cannot be ignored, and the distance changes between different parts of the object to be measured and the light source cannot be ignored.
  • the object to be measured cannot be regarded as a uniform plane, so it cannot A diffuse reflector with a fixed attitude and position is used to obtain the irradiance received by different parts of the object to be measured. That is to say, in actual measurement, the irradiance received by the object to be measured and the irradiance received by the diffuse reflector are quite different in some scenarios, and the difference in irradiance between the diffuse reflector and the surface of the object will lead to There is an error in spectral reflectance.
  • the embodiment of the present application provides a method, device and equipment for determining spectral reflectance, which can solve the above problems.
  • the embodiment of the present application provides a method for determining spectral reflectance, including:
  • the depth information of the target point, the first internal parameter of the imaging spectrum device, and the first coordinate information of the target point in the target spectrum image calculate and obtain the coordinates corresponding to the target point in the imaging spectrum device
  • the three-dimensional coordinate information under the system
  • said obtaining the registration depth map includes:
  • the initial depth map is converted into a registered depth map based on the target extrinsic parameter, the first intrinsic parameter of the imaging spectroscopy device and the second intrinsic parameter of the 3D measurement device.
  • the acquisition of the registration depth map and target spectral image it also includes:
  • a target spectral image is obtained according to the initial spectral image and the dark field image.
  • the preset full-illumination model of the diffuse reflection plate before inputting the three-dimensional coordinate information and the normal vector information into the preset full-illumination model of the diffuse reflection plate to obtain the second gray value, it also includes:
  • sample data of each preset position and attitude at the target wavelength includes sample gray values of sample points, sample normal vector information, and sample three-dimensional coordinate information
  • Fitting processing is performed on the sample data to obtain a preset full-illumination model of a diffuse reflection plate.
  • calculating the reflectance of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value and the second grayscale value ,Also includes:
  • a spectral reflectance curve of the object to be measured is determined according to the reflectance of all the target points in the registration depth map.
  • the determining the normal vector information corresponding to the target point according to the neighborhood points of the target point includes:
  • a space surface formed by the neighborhood points is determined according to the neighborhood points of the target point, and normal vector information corresponding to the target point is acquired according to the space surface.
  • the embodiment of the present application provides a device for determining spectral reflectance, including:
  • a first acquisition unit configured to acquire a registration depth map and a target spectral image
  • a second acquiring unit configured to acquire depth information of the target point from the registration depth map, and acquire a first gray value of the target point from the target spectral image
  • the first calculation unit is configured to calculate and obtain the position of the target point at the target point according to the depth information of the target point, the first internal parameters of the imaging spectrum device, and the first coordinate information of the target point in the target spectral image.
  • a determining unit configured to determine normal vector information corresponding to the target point according to the neighbor points of the target point
  • a first processing unit configured to input the three-dimensional coordinate information and the normal vector information into a preset full-illumination model of a diffuse reflection plate to obtain a second gray value
  • a second calculation unit configured to acquire the reflectivity of the diffuse reflection plate, and calculate the reflectivity of the target point according to the reflectivity of the diffuse reflection plate, the first grayscale value, and the second grayscale value .
  • the first acquisition unit is specifically used for:
  • the initial depth map is converted into a registered depth map based on the target extrinsic parameter, the first intrinsic parameter of the imaging spectroscopy device and the second intrinsic parameter of the 3D measurement device.
  • the device for determining the spectral reflectance also includes:
  • a third acquisition unit configured to acquire an initial spectral image and a dark field image
  • the second processing unit is configured to obtain a target spectral image according to the initial spectral image and the dark field image.
  • the device for determining the spectral reflectance also includes:
  • the third acquisition unit is configured to acquire sample data of each preset position and attitude at the target wavelength;
  • the sample data includes sample gray value of sample point, sample normal vector information and sample three-dimensional coordinate information;
  • the third processing unit is configured to perform fitting processing on the sample data to obtain a preset full-illumination model of the diffuse reflection plate.
  • the device for determining the spectral reflectance also includes:
  • the fourth processing unit is configured to determine the spectral reflectance curve of the object to be measured according to the reflectance of all the target points in the registration depth map.
  • the determining unit is specifically used for:
  • a space surface formed by the neighborhood points is determined according to the neighborhood points of the target point, and normal vector information corresponding to the target point is acquired according to the space surface.
  • an embodiment of the present application provides a device for determining spectral reflectance, including a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the When the processor executes the computer program, the method for determining the spectral reflectance as described in the first aspect above is realized.
  • an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and it is characterized in that, when the computer program is executed by a processor, the above-mentioned first aspect can be implemented.
  • the registration depth map and target spectral image are obtained; the depth information of the target point is obtained from the registration depth map, and the first gray value of the target point is obtained; according to the depth information of the target point, the imaging spectrum device
  • the first internal parameter of the target point and the first coordinate information of the target point in the target spectral image are calculated to obtain the three-dimensional coordinate information of the target point; the normal vector information corresponding to the target point is determined according to the neighborhood points of the target point; the three-dimensional coordinate Input the information and normal vector information into the preset full-illumination model of the diffuse reflection plate to obtain the second gray value; obtain the reflectivity of the diffuse reflection plate, according to the reflectance of the diffuse reflection plate, the first gray value and the second gray value Calculate the reflectivity of the target point.
  • Fig. 1 is the schematic diagram of the shooting scene of the prosthetic human face provided by the present application.
  • Fig. 2 is a schematic flowchart of a method for determining spectral reflectance provided in the first embodiment of the present application
  • Fig. 3 is a schematic flowchart of refinement of S104 in a method for determining spectral reflectance provided in the first embodiment of the present application;
  • FIG. 4 is a schematic diagram of a first line segment and a first included angle in a method for determining spectral reflectance provided in the first embodiment of the present application;
  • FIG. 5 is a schematic flowchart of another method for determining spectral reflectance provided in the second embodiment of the present application.
  • Fig. 6 is a schematic diagram of a device for determining spectral reflectance provided by a third embodiment of the present application.
  • Fig. 7 is a schematic diagram of a device for determining spectral reflectance provided by a fourth embodiment of the present application.
  • references to "one embodiment” or “some embodiments” or the like in the specification of the present application means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application.
  • appearances of the phrases “in one embodiment,” “in some embodiments,” “in other embodiments,” “in other embodiments,” etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean “one or more but not all embodiments” unless specifically stated otherwise.
  • the terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless specifically stated otherwise.
  • the methods that can be used are: direct measurement method and indirect measurement method.
  • Direct measurements are generally only used in laboratories. Precisely control the experimental environment and experimental conditions during the measurement, use sophisticated optical instruments to measure the reflected optical power and received optical power at each wavelength of the target surface, and use the ratio of the two to calculate the spectral reflectance.
  • the direct measurement method has strict requirements on the measurement and is not widely used.
  • the indirect measurement method directly uses the ratio of the target gray value (DN value) detected by the spectral detection equipment to the gray value of the reference diffuse reflection plate to calculate the spectral reflectance.
  • the indirect measurement method is widely used because of its simple operation and low requirements on the measurement environment and equipment.
  • Figure 1 shows the shooting scene (700nm image) of a prosthetic face. The spectral images of each band of the scene are taken by an imaging spectrometer.
  • a piece of Diffuse reflector In addition to the object to be measured, a piece of Diffuse reflector. Diffuse reflective panels have a Lambertian emission characteristic with a known reflectivity and reflective brightness is the same in all directions.
  • the following operations are performed:
  • DN 0 and DN 1 are gray values that have been subtracted from the dark background
  • the indirect measurement method uses the ratio of the gray value to calculate the reflectance, and its theoretical derivation is as follows:
  • the irradiance E0 received by the object to be measured is equal to the irradiance E1 received by the diffuse reflection plate, which is also the reason why the diffuse reflection plate in the indirect measurement method is as far as possible The reason for the proximity of the object.
  • the structural changes on the surface of the object to be measured are omitted by the scale, and only the macroscopic observation characteristics are shown. can be considered as a uniform plane.
  • the distance between the object to be measured and the light source is long, the illumination in the scene is relatively uniform.
  • the irradiance received by the diffuse reflector and the object to be measured can be considered to be the same.
  • the structural changes on the surface of the object to be measured cannot be ignored, and the distance changes between different parts of the object to be measured and the light source cannot be ignored.
  • the object to be measured cannot be regarded as a uniform plane, so it cannot A diffuse reflector with a fixed attitude and position is used to obtain the irradiance received by different parts of the object to be measured.
  • the irradiance received by the object to be measured and the irradiance received by the diffuse reflector are quite different in some scenarios, and the difference in irradiance between the diffuse reflector and the surface of the object will lead to There is an error in spectral reflectance.
  • FIG. 2 is a schematic flowchart of a method for determining spectral reflectance provided in the first embodiment of the present application.
  • a method for determining spectral reflectance in this embodiment is executed by a device having a function of determining spectral reflectance.
  • the hardware equipment used to implement the method including: imaging spectrum equipment, 3D measurement equipment, and lighting equipment.
  • the imaging spectrometer device can be a common imaging spectrometer at present, such as a grating type, a rotating filter type, a frame type, etc.; it can also be some new imaging spectrometers, such as a filter array type. Its characteristic is that it can output spectral images of each band/channel.
  • the 3D measurement device can be a structured light sensor, a TOF sensor or a binocular sensor, etc. Its characteristic is that it can output depth images.
  • Lighting equipment can be a point light source with a small geometric size that emits light uniformly in all directions in space, or it can be a surface light source or a complex form of light source, or even a combination of various complex light sources.
  • the light source needs to maintain a stable luminous intensity during the measurement period or the light source combination cannot change greatly.
  • the lighting device is a point light source.
  • the camera calibration method calibrates the internal parameters of the 3D measurement equipment, the internal parameters of the imaging spectrum equipment, and the external parameters between the two, and accurately measure the distance between the point light source and the imaging spectrum equipment.
  • the distance information of that is, the translation vector from the light source to the measurement coordinate system of the imaging spectroscopy equipment.
  • the method for determining the spectral reflectance as shown in Figure 2 may include:
  • S101 Acquire a registered depth map and a target spectral image.
  • the device acquires a registered depth map and target spectral image.
  • the registration depth map is a depth map obtained by observing the imaging spectrum equipment.
  • the target spectral image may be a spectral image after subtracting dark field data.
  • the device when obtaining the registration depth map, the device obtains the initial depth map output by the 3D measurement device; according to the external parameters of the target, the first internal parameter of the imaging spectrum device, and the second internal parameter of the 3D measurement device, the The initial depth map is converted to a registered depth map.
  • the external parameters of the target, the first internal parameters of the imaging spectrum device and the second internal parameters of the 3D measurement device are obtained through calibration during hardware calibration.
  • the off-target parameter is the distance information between the point light source and the imaging spectroscopy equipment, that is, the translation vector from the light source to the measurement coordinate system of the imaging spectroscopy equipment.
  • the device converts the initial depth map output by the 3D measurement device into the registration depth map observed by the imaging spectrum device, which actually realizes the pixel-by-pixel registration of spectral data and 3D data.
  • K d is the second internal parameter of the 3D measurement device
  • K s is the first internal parameter of the imaging spectroscopy device
  • the external parameters of the target include the rotation matrix and translation vector from the 3D measurement device to the spectral measurement device, which are denoted as R d2s and T d2s
  • d d is the depth value corresponding to a point [u d , v d ] in the initial depth map output by the 3D measurement equipment, which can be read from the initial depth map
  • d s is the registered depth map of the converted imaging spectrum equipment Depth value corresponding to point [u s ,v s ].
  • the device can acquire the initial spectral image and the dark field image; the target spectral image is obtained according to the initial spectral image and the dark field image.
  • the imaging spectrometer is used to collect the spectral image of the scene; the lens of the imaging spectrometer is blocked, and the dark field data is taken to obtain a dark field image; the image data of the initial spectral image of each band is subtracted The dark field data of the field image is obtained to obtain the target spectral image after subtracting the dark field.
  • the device obtains the depth information of the target point and the depth information of the diffuse reflection plate from the registration depth map.
  • the depth information of the target point and the depth information of the diffuse reflector can be directly read from the registration depth map. For example, assuming that the coordinates of point A in the target spectral image are (m, n), then directly read the depth value of the point with coordinates (m, n) in the registration depth map, which is the depth information of point A .
  • the target point is any point on the object to be measured in the target spectral image of a certain band.
  • the device acquires the first grayscale value of the target point and the second grayscale value of the diffuse reflection plate from the target spectral image, and the first grayscale value of the target point and the second grayscale value of the diffuse reflection plate can be obtained from the target spectral image read directly.
  • S104 Correct the second grayscale value according to the depth information of the target point and the depth information of the diffuse reflection plate to obtain a third grayscale value.
  • the device corrects the second grayscale value according to the depth information of the target point and the depth information of the diffuse reflector to obtain the third grayscale value.
  • the device can calculate the three-dimensional coordinates of the target point and the three-dimensional coordinates of the diffuse reflection plate according to the depth information of the target point and the depth information of the diffuse reflection plate, and then the device obtains the three-dimensional coordinates of the points in the neighborhood of the target point. , modify the second gray value to obtain the corrected third gray value.
  • the irradiance received by the object surface is inversely proportional to the distance between the object and the point light source, and proportional to the cosine of the angle between the light direction and the normal. It can be seen from this that because the distance between point C and point A is different from the light source, and the angle between the illumination direction and the normal line of the two points is different, the irradiance received at point C is different from the irradiance received at point A. In the same way, there will be errors in calculating the reflectance by using the gray value obtained from point C observation. Using the three-dimensional coordinate data, the gray value of point C can be corrected.
  • This problem can be described as: given the gray value observed by the diffuse reflector at a known position and attitude, find the gray value observed by the diffuse reflector at a specified position and attitude (same as the pose of the target point A). Using the inverse square law of the distance of the irradiance of the point light source, the correction coefficient of the irradiance of the diffuse reflector after changing the pose can be obtained. Due to the proportional relationship between the irradiance and the gray value, this coefficient is the correction of the observed gray value coefficient.
  • S104 may include S1041-S1043, as shown in FIG. 3 , and details of S1041-S1043 are as follows:
  • S1041 Calculate a first distance between a point light source and a first line segment between the target point according to the depth information of the target point, and calculate a first distance between the first line segment and a normal line corresponding to the target point. The first angle of an included angle.
  • the device calculates the first distance of the first line segment between the point light source and the target point according to the depth information of the target point, and calculates the first angle of the first angle between the first line segment and the corresponding normal of the target point .
  • point A is the target point
  • point B is the point light source
  • point C is the center point of the diffuse reflection plate.
  • the line segment AB is the first line segment between the point light source and the target point
  • the first distance marking the first line segment AB is d 0
  • the first included angle between the first line segment AB and the normal line corresponding to the target point A is ⁇ 0 .
  • the device calculates the first distance of the first line segment between the point light source and the target point according to the depth information of the target point.
  • the device can calculate the coordinates of the point light source and the target point, and obtain the first distance according to the coordinate information of the two.
  • the device calculates the first three-dimensional coordinates of the target point in the coordinate system corresponding to the imaging spectrum device according to the depth information of the target point, the first internal parameters of the imaging spectrum device, and the first coordinate information of the target point in the target spectrum image ; Specifically, the following formula can be used:
  • (X, Y, Z) are the first three-dimensional coordinates of the target point in the coordinate system corresponding to the imaging spectrum equipment, (u s , v s ) are the image coordinates of the point in the target spectral image, and K s is the imaging spectrum
  • the first internal parameter of the device, d s is the depth value of this point.
  • the device obtains the depth information of the point light source from the registration depth map, and calculates Obtain the second three-dimensional coordinates of the point light source in the coordinate system corresponding to the imaging spectrum device; the calculation method of the second three-dimensional coordinates can refer to the relevant description in the calculation method of the first three-dimensional coordinates, which will not be repeated here.
  • the device calculates the first distance of the first line segment between the point light source and the target point according to the first three-dimensional coordinates and the second three-dimensional coordinates.
  • [(XX 1 ) 2 +(YY 1 ) 2 +(ZZ 1 ) 2 ] 1/2 .
  • the device When calculating the first angle between the first line segment and the first angle corresponding to the normal of the target point, the device obtains the space surface formed by the neighbor points of the target point, and obtains the normal vector corresponding to the target point according to the space surface ; Calculate the target vector between the point light source and the target point according to the first three-dimensional coordinates and the second three-dimensional coordinates; determine the first included angle between the first line segment and the normal line corresponding to the target point according to the normal vector and the target vector an angle.
  • the device needs to obtain the neighborhood points of the target point first, and the neighborhood of the target point is not specifically limited. For example, you can choose to center on the target point, 21*21 pixel window, or 31*31 pixels, or 71* 71 pixels, as the neighborhood of the target point. Among them, when determining the neighborhood, a window with an odd width is generally selected.
  • the space surface formed by the neighborhood points of the target point is the surface contour formed by these neighborhood points, which can be determined by determining the three-dimensional coordinates of these neighborhood points.
  • the method of calculating the three-dimensional coordinates of the neighborhood points can be referred to above
  • the calculation method of the first three-dimensional coordinates in this article will not be repeated here.
  • the depth value of the neighborhood is also read from the registration depth map according to its pixel coordinates.
  • the three-dimensional coordinates constitute the point cloud data of the neighborhood of point A, which is the spatial surface formed by the neighborhood points of the target point.
  • the device can analyze and calculate the space surface according to the principal component analysis algorithm, and obtain the normal vector corresponding to the target point.
  • the device determines the first angle of the first angle between the first line segment and the corresponding normal of the target point according to the normal vector and the target vector.
  • the normal vector is n
  • the target vector is m
  • S1042 Calculate the second distance of the second line segment between the point light source and the center point of the diffuse reflection plate according to the depth information of the diffuse reflection plate, and calculate the correspondence between the second line segment and the diffuse reflection plate The second angle of the second angle between the normals.
  • S1043 Correct the second grayscale value according to the first distance, the second distance, the first angle, and the second angle to obtain the third grayscale value.
  • the device corrects the second grayscale value according to the first distance, the second distance, the first angle and the second angle to obtain the third grayscale value, which can be corrected according to the following formula:
  • DN 2 is the third gray value
  • DN 1 is the second gray value
  • ⁇ 0 is the first angle
  • ⁇ 1 is the second angle
  • d 0 is the first distance
  • d 1 is the second distance.
  • S105 Acquire the reflectance of the diffuse reflection plate, and calculate the reflectance of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value, and the third grayscale value.
  • the device obtains the reflectance of the diffuse reflection plate, and calculates the reflectance of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value DN 0 , and the third grayscale value. It is known that the reflectance of the diffuse reflection plate is ⁇ r and the target point reflectance ⁇ A is calculated by using the corrected second gray value DN 2 as follows:
  • the device can perform the above calculation for each target point on the object to be measured to obtain the reflectance of all target points, repeat the above operation for all bands, and then, the device determines the spectral reflectance of all points of the object to be measured according to the reflectance of all target points rate curve.
  • the registration depth map and the target spectral image are obtained; the depth information of the target point and the depth information of the diffuse reflection plate are obtained from the registration depth map; the first gray value of the target point is obtained from the target spectral image and the second grayscale value of the diffuse reflection plate; modify the second grayscale value according to the depth information of the target point and the depth information of the diffuse reflection plate to obtain the third grayscale value; obtain the reflectivity of the diffuse reflection plate, according to the diffuse
  • the reflectance of the reflective plate, the first grayscale value and the third grayscale value are used to calculate the reflectance of the target point.
  • the lighting equipment when measuring the spectral reflectance, by correcting the gray value of a diffuse reflector with a determined position and attitude, a 3D image that is exactly the same as the three-dimensional shape of the object to be measured is obtained.
  • the "diffuse reflector" is placed in the exact same position as the object to be measured.
  • the irradiance received by each part of the "diffuse reflector” is exactly the same as that of the same part of the object to be measured, and then the spectral reflectance is calculated. This avoids the large difference between the irradiance received by the object to be measured and the irradiance received by the diffuse reflector in some scenarios, and further avoids possible errors in the calculation of spectral reflectance. Apps provide more accurate data sources.
  • FIG. 5 is a schematic flowchart of another method for determining spectral reflectance provided in the second embodiment of the present application. A method for determining spectral reflectance in this embodiment is executed by a device having a function of determining spectral reflectance.
  • the method for determining the spectral reflectance as shown in Figure 5 may include:
  • S201 Acquire a registered depth map and a target spectral image.
  • the device acquires a registered depth map and target spectral image.
  • the registration depth map is a depth map obtained by observing the imaging spectrum equipment.
  • the target spectral image may be a spectral image after subtracting dark field data.
  • the initial depth map output by the 3D measurement device is obtained; according to the target external parameters, the first internal parameter of the imaging spectrum device and the second internal parameter of the 3D measurement device, the initial The depth map is converted to a registered depth map.
  • the device When acquiring the target spectral image, the device acquires the initial spectral image and the dark field image; the target spectral image is obtained according to the initial spectral image and the dark field image.
  • S202 Acquire depth information of a target point from the registration depth map, and acquire a first gray value of the target point from the target spectral image.
  • the device selects the target point, which is any point on the object to be measured in the target spectral image of a certain band.
  • the device obtains the depth information of the target point from the registration depth map.
  • the depth information of the target point can be directly read from the registered depth map. For example, assuming that the coordinates of point A in the target spectral image are (m, n), then directly read the depth value of the point with coordinates (m, n) in the registration depth map, which is the depth information of point A .
  • the device acquires the first gray value of the target point from the target spectral image, and the first gray value of the target point can be directly read from the target spectral image.
  • S203 According to the depth information of the target point, the first internal parameter of the imaging spectrum device, and the first coordinate information of the target point in the target spectrum image, calculate and obtain the corresponding position of the target point in the imaging spectrum device The three-dimensional coordinate information in the coordinate system of .
  • S204 Determine the normal vector information corresponding to the target point according to the neighbor points of the target point.
  • the device determines the normal vector information corresponding to the target point according to the neighborhood points of the target point.
  • the device first determines the neighborhood points of the target point, and the neighborhood of the target point is not specifically limited.
  • the target point can be selected as the center, 21* 21-pixel window, or 31*31 pixels, or 71*71 pixels, as the neighborhood of the target point.
  • a window with an odd width is generally selected.
  • the device can determine the normal vector information corresponding to the target point according to the neighborhood points of the target point, and can use the preset algorithm to calculate the coordinates of the neighborhood points to obtain the normal vector information corresponding to the target point.
  • the device determines the space surface formed by the neighborhood points according to the neighborhood points of the target point, and obtains the normal vector information corresponding to the target point according to the space surface.
  • the spatial surface formed by the neighborhood points of the target point is the surface contour formed by these neighborhood points, which can be determined by determining the three-dimensional coordinates of these neighborhood points.
  • the method for calculating the three-dimensional coordinates of the neighborhood points can be the first The method for calculating the first three-dimensional coordinates in the embodiment will not be repeated here.
  • the device can analyze and calculate the space surface according to the principal component analysis algorithm, and obtain the normal vector information corresponding to the target point.
  • S205 Input the three-dimensional coordinate information and the normal vector information into a preset full-illumination model of a diffuse reflection plate to obtain a second gray value.
  • the device stores the preset full-illumination model of the diffuse reflection plate, wherein the input of the preset full-illumination model of the diffuse reflection plate is three-dimensional coordinate information and normal vector information, and the output of the three-dimensional coordinate information and the normal vector information is the corrected Second grayscale value.
  • the preset diffuse reflector full-illumination model can be pre-trained directly by the device, or it can be ported to the local device after pre-training by other devices.
  • the device inputs the three-dimensional coordinate information and normal vector information into the preset full-illumination model of the diffuse reflection plate to obtain the second gray value.
  • the second grayscale value is the observed grayscale value of the diffuse reflector at the same distance and attitude as the target point A under the current complex lighting conditions.
  • the device may perform modeling in advance, and obtain a preset full-illumination model of the diffuse reflection plate by fitting the acquired data.
  • the modeling stage first fix a certain wavelength, set it as the target wavelength, and obtain the data of a certain position and posture.
  • the device obtains the sample data of each preset position and posture under the target wavelength, and performs fitting processing on the sample data to obtain the preset full-illumination model of the diffuse reflection plate.
  • the sample data includes the sample gray value of the sample point, the sample normal vector information and the sample three-dimensional coordinate information.
  • the sample gray value DN of the center point C of the diffuse reflection plate is extracted from the sample gray value DN of the center point C of the diffuse reflection plate, the sample three-dimensional coordinate information (X, Y, Z) of the center point C of the diffuse reflection plate, and the sample of the diffuse reflection plate Normal vector information [m,n,k], to obtain a set of data [DN,X,Y,Z,m,n,k]; extract the data of each preset position and posture at this wavelength.
  • the specific form of the fitting function is not limited, and can be expressed uniformly as follows:
  • the model can output the observed gray value of the diffuse reflector at that position and attitude by the imaging spectrometer.
  • the full-illumination model of the diffuse reflection plate can be obtained, that is, the preset full-illumination model of the diffuse reflection plate.
  • S206 Acquire the reflectance of the diffuse reflection plate, and calculate the reflectance of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value, and the second grayscale value.
  • the device acquires the reflectance of the diffuse reflection plate, and calculates the reflectance of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value DN 0 , and the second grayscale value DN 2 . It is known that the reflectance of the diffuse reflection plate is ⁇ r and the target point reflectance ⁇ A is calculated by using the corrected second gray value DN 2 as follows:
  • the device can perform the above calculation for each target point on the object to be measured to obtain the reflectance of all target points, repeat the above operation for all bands, and then, the device determines the spectral reflectance of all points of the object to be measured according to the reflectance of all target points rate curve.
  • the registration depth map and target spectral image are obtained; the depth information of the target point is obtained from the registration depth map, and the first gray value of the target point is obtained; according to the depth information of the target point, the imaging spectrum device
  • the first internal parameter of the target point and the first coordinate information of the target point in the target spectral image are calculated to obtain the three-dimensional coordinate information of the target point; the normal vector information corresponding to the target point is determined according to the neighborhood points of the target point; the three-dimensional coordinate Input the information and normal vector information into the preset full-illumination model of the diffuse reflection plate to obtain the second gray value; obtain the reflectivity of the diffuse reflection plate, according to the reflectance of the diffuse reflection plate, the first gray value and the second gray value Calculate the reflectivity of the target point.
  • FIG. 6 is a schematic diagram of a device for determining spectral reflectance provided in a third embodiment of the present application. Each included unit is used to execute each step in the embodiment corresponding to FIG. 5 . For details, refer to the relevant description in the embodiment corresponding to FIG. 5 . For ease of description, only the parts related to this embodiment are shown. Referring to Fig. 6, the determining device 6 of spectral reflectance comprises:
  • a first acquisition unit 610 configured to acquire a registration depth map and a target spectral image
  • the second acquiring unit 620 is configured to acquire the depth information of the target point from the registration depth map, and acquire the first gray value of the target point from the target spectral image;
  • the first calculation unit 630 is configured to calculate and obtain the target point at Three-dimensional coordinate information in the coordinate system corresponding to the imaging spectroscopy device;
  • a determination unit 640 configured to determine the normal vector information corresponding to the target point according to the neighborhood points of the target point;
  • the first processing unit 650 is configured to input the three-dimensional coordinate information and the normal vector information into a preset full-illumination model of a diffuse reflection plate to obtain a second gray value;
  • the second calculation unit 660 is configured to obtain the reflectance of the diffuse reflection plate, and calculate the reflection of the target point according to the reflectance of the diffuse reflection plate, the first grayscale value, and the second grayscale value Rate.
  • the first acquiring unit 610 is specifically configured to:
  • the initial depth map is converted into a registered depth map based on the target extrinsic parameter, the first intrinsic parameter of the imaging spectroscopy device and the second intrinsic parameter of the 3D measurement device.
  • the determining device 6 of spectral reflectance also includes:
  • a third acquisition unit configured to acquire an initial spectral image and a dark field image
  • the second processing unit is configured to obtain a target spectral image according to the initial spectral image and the dark field image.
  • the determining device 6 of spectral reflectance also includes:
  • the third acquisition unit is configured to acquire sample data of each preset position and attitude at the target wavelength;
  • the sample data includes sample gray value of sample point, sample normal vector information and sample three-dimensional coordinate information;
  • the third processing unit is configured to perform fitting processing on the sample data to obtain a preset full-illumination model of the diffuse reflection plate.
  • the determining device 6 of spectral reflectance also includes:
  • the fourth processing unit is configured to determine the spectral reflectance curve of the object to be measured according to the reflectance of all the target points in the registration depth map.
  • the determining unit 640 is specifically configured to:
  • a space surface formed by the neighborhood points is determined according to the neighborhood points of the target point, and normal vector information corresponding to the target point is acquired according to the space surface.
  • Fig. 7 is a schematic diagram of a device for determining spectral reflectance provided by a fourth embodiment of the present application.
  • the determining device 7 of the spectral reflectance of this embodiment includes: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and operable on the processor 70, such as a spectral Procedure for determination of reflectivity.
  • the processor 70 executes the computer program 72, it implements the steps in the embodiments of the method for determining each spectral reflectance above, such as steps 201 to 206 shown in FIG. 5 .
  • functions of the modules/units in the above-mentioned device embodiments such as the functions of the modules 610 to 660 shown in FIG. 6 , are realized.
  • the computer program 72 can be divided into one or more modules/units, and the one or more modules/units are stored in the memory 71 and executed by the processor 70 to complete this application.
  • the one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program 72 in the spectral reflectance determining device 7 .
  • the computer program 72 can be divided into a first acquisition unit, a second acquisition unit, a first calculation unit, a determination unit, a first processing unit, and a second calculation unit.
  • the specific functions of each unit are as follows:
  • a first acquisition unit configured to acquire a registration depth map and a target spectral image
  • a second acquiring unit configured to acquire depth information of the target point from the registration depth map, and acquire a first gray value of the target point from the target spectral image
  • the first calculation unit is configured to calculate and obtain the position of the target point at the target point according to the depth information of the target point, the first internal parameters of the imaging spectrum device, and the first coordinate information of the target point in the target spectral image.
  • a determining unit configured to determine the normal vector information corresponding to the target point according to the neighborhood points of the target point
  • a first processing unit configured to input the three-dimensional coordinate information and the normal vector information into a preset full-illumination model of a diffuse reflection plate to obtain a second gray value
  • a second calculation unit configured to acquire the reflectivity of the diffuse reflection plate, and calculate the reflectivity of the target point according to the reflectivity of the diffuse reflection plate, the first grayscale value, and the second grayscale value .
  • the device for determining the spectral reflectance may include, but not limited to, a processor 70 and a memory 71 .
  • a processor 70 and a memory 71 .
  • Fig. 7 is only an example of the determination device 7 of spectral reflectance, and does not constitute a limitation to the determination device 7 of spectral reflectance, and may include more or less components than those shown in the figure, or a combination
  • Certain components, or different components, for example, the device for determining the spectral reflectance may also include an input and output device, a network access device, a bus, and the like.
  • the so-called processor 70 can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.
  • the memory 71 may be an internal storage unit of the device 7 for determining spectral reflectance, for example, a hard disk or memory of the device 7 for determining spectral reflectance. Described memory 71 also can be the external storage device of the determining device 7 of described spectral reflectance, for example the plug-in hard disk equipped on the determining device 7 of described spectral reflectance, smart memory card (Smart Media Card, SMC), Secure Digital (Secure Digital, SD) card, flash memory card (Flash Card), etc. Further, the device for determining spectral reflectance 7 may also include both an internal storage unit of the device for determining spectral reflectance 7 and an external storage device. The memory 71 is used to store the computer program and other programs and data required by the device for determining spectral reflectance. The memory 71 can also be used to temporarily store data that has been output or will be output.
  • the embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and operable on the at least one processor, and the processor executes The computer program implements the steps in any of the above method embodiments.
  • the embodiment of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in each of the foregoing method embodiments can be realized.
  • An embodiment of the present application provides a computer program product.
  • the computer program product When the computer program product is run on a mobile terminal, the mobile terminal can implement the steps in the foregoing method embodiments when executed.
  • the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the procedures in the methods of the above embodiments in the present application can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a computer-readable storage medium.
  • the computer program When executed by a processor, the steps in the above-mentioned various method embodiments can be realized.
  • the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form.
  • the computer-readable medium may at least include: any entity or device capable of carrying computer program codes to the photographing device/terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium.
  • ROM read-only memory
  • RAM random access memory
  • electrical carrier signal telecommunication signal and software distribution medium.
  • U disk mobile hard disk
  • magnetic disk or optical disk etc.
  • computer readable media may not be electrical carrier signals and telecommunication signals under legislation and patent practice.
  • the disclosed device/network device and method may be implemented in other ways.
  • the device/network device embodiments described above are only illustrative.
  • the division of the modules or units is only a logical function division.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

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Abstract

本申请适用于光学技术领域，提供了一种光谱反射率的确定方法，包括：获取配准深度图和目标光谱图像；从配准深度图中获取目标点的深度信息，并获取目标点的第一灰度值；根据目标点的深度信息、成像光谱设备的第一内参数和目标点在所述目标光谱图像中的第一坐标信息，计算得到目标点的三维坐标信息；根据目标点的邻域点确定目标点对应的法线向量信息；将三维坐标信息和法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值和第二灰度值计算目标点的反射率。上述方法，避免了待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异大，避免了光谱反射率在计算时的误差。

Description

一种光谱反射率的确定方法、装置及设备
本申请要求于2021年6月30日提交中国专利局，申请号为202110754926.X，发明名称为“一种光谱反射率的确定方法、装置及设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请属于光学技术领域，尤其涉及一种光谱反射率的确定方法、装置及设备。
背景技术
在进行光谱反射率的测量时，可以采用间接测量法，间接测量法直接利用光谱探测设备探测得到的目标灰度值与参考漫反射板的灰度值之比计算光谱反射率。在使用间接测量法时，一个重要的前提是待测物体接收的辐照度与漫反射板接收的辐照度要相等，也就是要求漫反射板尽可能靠近待测物体，这样才能得到最后的测量结果。
但是，在近距离观测场景下，待测物体表面的结构变化不能被忽略，且待测物体不同部位与光源的距离变化也不能被忽略，此时待测物不能被视为均一平面，因此无法用一块姿态与位置固定的漫反射板来获得待测物体不同部位所接收的辐照度。也就是说，在实际测量中，待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大，漫反射板与物体表面处辐照度不同会导致在计算光谱反射率时出现误差。
发明内容
本申请实施例提供了一种光谱反射率的确定方法、装置及设备，可以解决 上述问题。
第一方面，本申请实施例提供了一种光谱反射率的确定方法，包括：
获取配准深度图和目标光谱图像；
从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
根据所述目标点的邻域点确定所述目标点对应的法线向量信息；
将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
进一步地，所述获取配准深度图，包括：
获取由3D测量设备输出的初始深度图；
根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
进一步地，在所述获取配准深度图和目标光谱图像之前，还包括：
获取初始光谱图像和暗场图像；
根据所述初始光谱图像和所述暗场图像得到目标光谱图像。
进一步地，在所述将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值之前，还包括：
获取目标波长下各个预设的位置姿态的样本数据；所述样本数据包括样本点的样本灰度值、样本法线向量信息和样本三维坐标信息；
对所述样本数据进行拟合处理，得到预设漫反射板全光照模型。
进一步地，在所述获取所述漫反射板的反射率，根据所述漫反射板的反射 率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率之后，还包括：
根据所述配准深度图中所有所述目标点的反射率，确定所述待测物体的光谱反射率曲线。
进一步地，所述根据所述目标点的邻域点确定所述目标点对应的法线向量信息，包括：
根据所述目标点的邻域点确定所述邻域点所形成的空间曲面，并根据所述空间曲面获取所述目标点对应法线向量信息。
第二方面，本申请实施例提供了一种光谱反射率的确定装置，包括：
第一获取单元，用于获取配准深度图和目标光谱图像；
第二获取单元，用于从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
第一计算单元，用于根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
确定单元，用于根据所述目标点的邻域点确定所述目标点对应的法线向量信息；
第一处理单元，用于将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
第二计算单元，用于获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
进一步地，所述第一获取单元，具体用于：
获取由3D测量设备输出的初始深度图；
根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
进一步地，光谱反射率的确定装置，还包括：
第三获取单元，用于获取初始光谱图像和暗场图像；
第二处理单元，用于根据所述初始光谱图像和所述暗场图像得到目标光谱图像。
进一步地，光谱反射率的确定装置，还包括：
第三获取单元，用于获取目标波长下各个预设的位置姿态的样本数据；所述样本数据包括样本点的样本灰度值、样本法线向量信息和样本三维坐标信息；
第三处理单元，用于对所述样本数据进行拟合处理，得到预设漫反射板全光照模型。
进一步地，光谱反射率的确定装置，还包括：
第四处理单元，用于根据所述配准深度图中所有所述目标点的反射率，确定所述待测物体的光谱反射率曲线。
进一步地，所述确定单元，具体用于：
根据所述目标点的邻域点确定所述邻域点所形成的空间曲面，并根据所述空间曲面获取所述目标点对应法线向量信息。
第三方面，本申请实施例提供了一种光谱反射率的确定设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如上述第一方面所述的光谱反射率的确定方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如上述第一方面所述的光谱反射率的确定方法。
本申请实施例中，获取配准深度图和目标光谱图像；从配准深度图中获取目标点的深度信息，并获取目标点的第一灰度值；根据目标点的深度信息、成像光谱设备的第一内参数和目标点在所述目标光谱图像中的第一坐标信息，计算得到目标点的三维坐标信息；根据目标点的邻域点确定目标点对应的法线向量信息；将三维坐标信息和法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值和 第二灰度值计算目标点的反射率。上述方法，针对面光源或其他复杂光照条件，在进行光谱反射率的测量时，通过对一个确定位置与姿态的漫反射板的灰度值进行修正，得到一个与待测物体三维形貌完全相同的“漫反射体”，放在与待测物体完全相同的位置，此时“漫反射体”的各个部位与待测物体的相同部位接收到的辐照度完全相同，再来计算光谱反射率。这样就避免了待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大，进一步避免了光谱反射率在计算时可能出现的误差，也可以为近距光谱应用提供更精确的数据源。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1是本申请提供的假体人脸的拍摄场景的示意图；
图2是本申请第一实施例提供的一种光谱反射率的确定方法的示意流程图；
图3是本申请第一实施例提供的一种光谱反射率的确定方法中S104细化的示意流程图；
图4是本申请第一实施例提供的一种光谱反射率的确定方法中第一线段和第一夹角的示意图；
图5是本申请第二实施例提供的另一种光谱反射率的确定方法的示意流程图；
图6是本申请第三实施例提供的光谱反射率的确定设备的示意图；
图7是本申请第四实施例提供的光谱反射率的确定设备的示意图。
具体实施方式
以下描述中，为了说明而不是为了限定，提出了诸如特定系统结构、技术之类的具体细节，以便透彻理解本申请实施例。然而，本领域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本申请。在其它情况中，省略对众所周知的系统、装置、电路以及方法的详细说明，以免不必要的细节妨碍本申请的描述。
应当理解，当在本申请说明书和所附权利要求书中使用时，术语“包括”指示所描述特征、整体、步骤、操作、元素和/或组件的存在，但并不排除一个或多个其它特征、整体、步骤、操作、元素、组件和/或其集合的存在或添加。
还应当理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
另外，在本申请说明书和所附权利要求书的描述中，术语“第一”、“第二”、“第三”等仅用于区分描述，而不能理解为指示或暗示相对重要性。
在本申请说明书中描述的参考“一个实施例”或“一些实施例”等意味着在本申请的一个或多个实施例中包括结合该实施例描述的特定特征、结构或特点。由此，在本说明书中的不同之处出现的语句“在一个实施例中”、“在一些实施例中”、“在其他一些实施例中”、“在另外一些实施例中”等不是必然都参考相同的实施例，而是意味着“一个或多个但不是所有的实施例”，除非是以其他方式另外特别强调。术语“包括”、“包含”、“具有”及它们的变形都意味着“包括但不限于”，除非是以其他方式另外特别强调。
在进行光谱反射率的测量时，可以采用的方法有：直接测量法与间接测量法。
直接测量法一般只在实验室内使用。测量中精确控制实验环境与实验条件，利用精密的光学仪器测量目标表面各个波长下反射的光功率与接收的光功率，利用二者之比计算光谱反射率。直接测量法对测量要求较为苛刻，应用不够广泛。
间接测量法直接利用光谱探测设备探测得到的目标灰度值(DN值)与参考漫反射板的灰度值之比计算光谱反射率。间接测量法由于操作简便，对测量环境与设备的要求低，因而应用十分广泛。举例来说，图1为假体人脸的拍摄场景(700nm图像)，利用成像光谱仪拍摄场景各个波段的光谱图像，场景中除了有待测物体之外，在靠近待测物体处还放置了一块漫反射板。漫反射板具有朗伯发射特性，其反射率已知且在各个方向上反射的亮度是相同的。为了计算假体人脸额头上一点A的反射率曲线，进行如下操作：
1)利用成像光谱仪拍摄场景数据，得到各个波段下的光谱图像；
2)遮挡成像光谱仪镜头，拍摄暗场数据，得到各个波段下的暗场图像；
3)以图示700nm为例，读取700nm光谱图像中A点的灰度值，假设为112，读取700nm暗场图像中A点的灰度值，假设为12；
7)计算700nm光谱图像中漫反射板区域的平均灰度值，假设为210，计算700nm暗场图像中漫反射板区域的平均灰度值，假设为10；
5)已知漫反射板在700nm的反射率为98％，则A点在700nm的反射率为(112-12)/(210-10)*98％＝79％；
对各个波长的光谱图像重复上述步骤3-5，即得到A点在各个波长处的反射率数据。
上述过程可以用如下公式表示：
Figure PCTCN2022080525-appb-000001
ρ:反射率
0:待测目标
1:参考漫反射板
DN 0与DN 1为已扣除暗背景的灰度值
其中，间接测量法利用灰度值的比值计算反射率，其理论推导如下：
Figure PCTCN2022080525-appb-000002
E s:sensor表面pixel处的辐照度
L:物体辐亮度
M:物体辐射出射度
E:物体表面辐照度
通过上述公式可以看出，在间接测量法中，有一个重要假设：待测物体接收的辐照度E0与漫反射板接收的辐照度E1相等，这也是间接测量法中漫反射板尽可能靠近物体的原因。
但是，在实际测量中上述假设并不总是成立的，即待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大。
在大尺度观测场景下，如远距离测量场景或遥感场景中的卫星观测、无人机观测等，待测物体表面的结构变化被尺度略去，只表现出宏观的观测特性，待测物体表面可以被视为均匀平面。同时，又由于待测物体与光源(如太阳)的距离远，场景中的光照较为均匀。此时在待测物体附近放置漫反射板，则漫反射板与待测物体接收的辐照度可以认为是相同的。
但是，在近距离观测场景下，待测物体表面的结构变化不能被忽略，且待测物体不同部位与光源的距离变化也不能被忽略，此时待测物体不能被视为均一平面，因此无法用一块姿态与位置固定的漫反射板来获得待测物体不同部位所接收的辐照度。
也就是说，在实际测量中，待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大，漫反射板与物体表面处辐照度不同会导致在计算光谱反射率时出现误差。
为了解决这一问题，本实施例提出了一种光谱反射率的确定方法。请参见图2，图2是本申请第一实施例提供的一种光谱反射率的确定方法的示意流程图。本实施例中一种光谱反射率的确定方法的执行主体为具有光谱反射率的确定功能的设备。
在对光谱反射率的确定方法进行详细的说明前，先说明一下实施该方法所使用的硬件设备，包括：成像光谱设备、3D测量设备、照明设备。
其中，成像光谱设备可以是目前常见的成像光谱仪，如光栅式、旋转滤光片式、画幅式等；也可以是一些新型的成像光谱仪，如滤光片阵列式。其特点是可以输出各个波段/通道的光谱图像。
3D测量设备可以是结构光传感器、TOF传感器或双目传感器等。其特点是可以输出深度图像。
照明设备可以是点光源，几何尺寸较小，向空间各方向均匀发光，也可以是面光源或复杂形式的光源，甚至是各种复杂光源的组合。光源需要在测量期间保持稳定发光强度或光源组合不能有较大变动。在本实施例中，照明设备为点光源。
在实施本实施例的方法前，需要对硬件进行标定，利用相机标定方法标定3D测量设备的内参、成像光谱设备的内参以及二者之间的外参，精确测量点光源与成像光谱设备之间的距离信息，即光源到成像光谱设备测量坐标系的平移向量。标定完成后在整个光谱反射率的确定的期间保持三者之间的相对位姿不变。
如图2所示的光谱反射率的确定方法可以包括：
S101：获取配准深度图和目标光谱图像。
设备获取配准深度图和目标光谱图像。其中，配准深度图是成像光谱设备观测得到的深度图。目标光谱图像可以为扣除暗场数据后的光谱图像。
具体来说，在获取配准深度图时，设备获取由3D测量设备输出的初始深度图；根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将初始深度图转换为配准深度图。其中，目标外参数、成像光谱设备的第一内参数和3D测量设备的第二内参数，是在硬件标定时，标定得到的。目标外参数为点光源与成像光谱设备之间的距离信息，即光源到成像光谱设备测量坐标系的平移向量。设备将3D测量设备输出的初始深度图转换为成像光 谱设备观测得到的配准深度图，实际上就是实现了光谱数据与3D数据逐像素的配准。
在进行转换时，可以采用如下公式，对初始深度图中的每一个点对应的深度值进行转换，具体公式如下：
Figure PCTCN2022080525-appb-000003
其中，K d为3D测量设备的第二内参数；K s为成像光谱设备的第一内参数，目标外参数包括3D测量设备到光谱测量设备的旋转矩阵与平移向量，分别记为R d2s与T d2s；d d为3D测量设备输出的初始深度图中一点[u d,v d]对应的深度值，可从初始深度图中读取；d s为转换后成像光谱设备配准深度图中对应点[u s,v s]的深度值。根据上式遍历初始深度图，可得到一张与成像光谱设备输出的目标光谱图像逐像素对应的配准深度图，从而实现深度图像数据与光谱图像数据的配准。
在获取目标光谱图像时，设备可以获取初始光谱图像和暗场图像；根据初始光谱图像和暗场图像得到目标光谱图像。具体来说，待光源发光稳定后，利用成像光谱仪采集场景的光谱图像；遮挡成像光谱仪镜头，拍摄暗场数据，得到暗场图像；将各个波段的初始光谱图像的图像数据减去相应波段的暗场图像的暗场数据，得到扣除暗场后的目标光谱图像。
S102：从所述配准深度图中获取目标点的深度信息以及漫反射板的深度信息。
设备从配准深度图中获取目标点的深度信息以及漫反射板的深度信息。具体来说，目标点的深度信息以及漫反射板的深度信息可以直接从配准深度图中读取到。举例来说，假设A点在目标光谱图像中的坐标为(m,n)，则直接读取配准深度图中坐标为(m,n)的点的深度值，即为A点的深度信息。
其中，目标点为某波段目标光谱图像中待测物体上的任一点。
S103：从所述目标光谱图像中获取所述目标点的第一灰度值和所述漫反射 板的第二灰度值。
设备从目标光谱图像中获取目标点的第一灰度值和漫反射板的第二灰度值，目标点的第一灰度值和漫反射板的第二灰度值可以从目标光谱图像中直接读取。
S104：根据所述目标点的深度信息和所述漫反射板的深度信息对所述第二灰度值进行修正，得到第三灰度值。
设备根据目标点的深度信息和漫反射板的深度信息对第二灰度值进行修正，得到第三灰度值。设备可以根据目标点的深度信息和漫反射板的深度信息，计算目标点的三维坐标和漫反射板的三维坐标，设备再获取目标点邻域内的点的三维坐标，通过上述这些点的三维坐标，对第二灰度值进行修正，得到修正后的第三灰度值。
其中，需要说明的是，利用三维坐标数据对漫反射板灰度值进行修正的原理为点光源辐照度的距离平方反比定律，说明如下：
若已知点光源向空间辐射的强度为I，则物体表面接收的辐照度与物体距点光源的距离成反比，与光照方向与法线夹角的余弦成正比。由此可知，由于点C与点A两点距光源的距离不同，两点的光照方向与法线夹角不同，因此C点处接收到的辐照度与A点接收的辐照度是不相同的，因此用对C点观测得到的灰度值进行反射率计算会存在误差。利用三维坐标数据，可以对C点的灰度值进行修正。
这个问题可以描述为：已知漫发射板在已知位置姿态下观测的灰度值，求漫反射板在指定位置姿态下(与目标A点的位姿相同)观测的灰度值。利用点光源辐照度的距离平方反比定律，可以得到改变位姿后漫反射板辐照度的修正系数，由于辐照度与灰度值的正比例关系，这个系数即为观测灰度值的修正系数。
具体来说，S104可以包括S1041～S1043，如图3所示，S1041～S1043具体如下：
S1041：根据所述目标点的深度信息计算点光源和所述目标点之间的第一线 段的第一距离，并且计算所述第一线段和所述目标点对应法线之间的第一夹角的第一角度。
设备根据目标点的深度信息计算点光源和目标点之间的第一线段的第一距离，并且计算第一线段和所述目标点对应法线之间的第一夹角的第一角度。具体来说，如图4所示，图4中，点A为目标点，点B为点光源，点C为漫反射板的中心点。线段AB为点光源和目标点之间的第一线段，标记第一线段AB的第一距离为d 0，第一线段AB和目标点A对应法线之间的第一夹角为θ 0。
具体来说，设备根据目标点的深度信息计算点光源和目标点之间的第一线段的第一距离。设备可以计算得到点光源和目标点的坐标，根据两者的坐标信息求得第一距离。设备根据目标点的深度信息、成像光谱设备的第一内参数和目标点在所述目标光谱图像中的第一坐标信息，计算得到目标点在成像光谱设备对应的坐标系下的第一三维坐标；具体可以采用如下公式：
Figure PCTCN2022080525-appb-000004
其中，(X,Y,Z)为目标点在成像光谱设备对应的坐标系下的第一三维坐标，(u s,v s)为目标光谱图像中该点的图像坐标，K s为成像光谱设备的第一内参数，d s为该点的深度值。
同理，设备从配准深度图中获取点光源的深度信息，并且根据点光源的深度信息、成像光谱设备的第一内参数和点光源在所述目标光谱图像中的第二坐标信息，计算得到点光源在所述成像光谱设备对应的坐标系下的第二三维坐标；第二三维坐标的计算方法可以参阅第一三维坐标的计算方法中的相关描述，此处不再赘述。
在计算得到第一三维坐标和第二三维坐标后，设备根据第一三维坐标和第二三维坐标计算点光源和目标点之间的第一线段的第一距离。举例来说，已知目标点A点的坐标(X,Y,Z)，点光源B的坐标也是已知的(X 1,Y 1,Z 1)，则第 一距离d 0＝|AB|＝[(X-X 1) 2+(Y-Y 1) 2+(Z-Z 1) 2] 1/2。
在计算第一线段和目标点对应法线之间的第一夹角的第一角度时，设备获取目标点的邻域点所形成的空间曲面，并根据空间曲面获取目标点对应法线向量；根据第一三维坐标和第二三维坐标计算点光源和目标点之间的目标向量；根据法线向量和目标向量确定第一线段和目标点对应法线之间的第一夹角的第一角度。
具体来说，设备需要先获取目标点的邻域点，目标点的邻域，不做具体限定，比如可以选择以目标点为中心，21*21像素窗口，或31*31像素，或71*71像素，作为目标点的邻域。其中，在确定邻域时，一般选宽度为奇数的窗口。
目标点的邻域点所形成的空间曲面即为这些邻域点的形成的表面轮廓，具体可以通过确定这些邻域点的三维坐标来确定，这里计算邻域点的三维坐标的方法可以参阅上文中第一三维坐标的计算方法，此处不再赘述。其中，邻域的深度值也是根据其像素坐标，从配准深度图中读取得到。假设在目标光谱图像中选择了以A点为中心，21*21的窗口作为A点的邻域，则对邻域中的每一邻域点遍历求解其三维坐标，最终求得的441个点的三维坐标即构成了A点邻域的点云数据，即为目标点的邻域点所形成的空间曲面。
然后，设备可以根据主成分分析算法对空间曲面进行分析计算，获取目标点对应法线向量。设备根据第一三维坐标和第二三维坐标计算点光源和目标点之间的目标向量，目标向量AB＝(X 1-X,Y 1-Y,Z 1-Z)。
设备根据法线向量和目标向量确定第一线段和目标点对应法线之间的第一夹角的第一角度，法线向量为n，目标向量为m，则第一夹角的第一角度θ 0＝arccos(m*n/|m||n|)。
S1042：根据所述漫反射板的深度信息计算所述点光源和所述漫反射板的中心点之间的第二线段的第二距离，并且计算所述第二线段和所述漫反射板对应法线之间的第二夹角的第二角度。
在S1042中，第二距离和第二角度的计算方法，具体细节可以参阅S1071 中的相关描述，此处不再赘述。
采用S1041中类似的方法，求得第二线段的，以及第二夹角的第二角度θ 1。
S1043：根据所述第一距离、所述第二距离、所述第一角度和所述第二角度对所述第二灰度值进行修正，得到所述第三灰度值。
设备根据第一距离、第二距离、第一角度和第二角度对第二灰度值进行修正，得到第三灰度值，具体可以根据如下公式进行修正：
Figure PCTCN2022080525-appb-000005
其中，DN 2为第三灰度值，DN 1为第二灰度值，θ 0为第一角度，θ 1为第二角度，d 0为第一距离，d 1为第二距离。
S105：获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第三灰度值计算所述目标点的反射率。
设备获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值DN 0和第三灰度值计算目标点的反射率。已知漫反射板的反射率为ρ r利用修正后的第二灰度值DN 2计算目标点反射率ρ A如下：
Figure PCTCN2022080525-appb-000006
设备可以对待测物体上的每一个目标点进行上述计算，得到所有目标点的反射率，对所有波段重复上述操作，然后，设备根据所有目标点的反射率，确定待测物体所有点的光谱反射率曲线。
本申请实施例中，获取配准深度图和目标光谱图像；从配准深度图中获取目标点的深度信息以及漫反射板的深度信息；从目标光谱图像中获取目标点的第一灰度值和漫反射板的第二灰度值；根据目标点的深度信息和漫反射板的深度信息对第二灰度值进行修正，得到第三灰度值；获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值和第三灰度值计算目标点的反射率。上述方法，当照明设备为点光源时，在进行光谱反射率的测量时，通过对一个确定位置与姿态的漫反射板的灰度值进行修正，得到一个与待测物体三维形貌完全相 同的“漫反射体”，放在与待测物体完全相同的位置，此时“漫反射体”的各个部位与待测物体的相同部位接收到的辐照度完全相同，再来计算光谱反射率。这样就避免了待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大，进一步避免了光谱反射率在计算时可能出现的误差，也可以为近距光谱应用提供更精确的数据源。
上述实施例中，提供了照明设备为点光源的方法，针对面光源或其他复杂光照条件，可以采用如下方式来确定目标点的反射率。请参见图5，图5是本申请第二实施例提供的另一种光谱反射率的确定方法的示意流程图。本实施例中一种光谱反射率的确定方法的执行主体为具有光谱反射率的确定功能的设备。
本实施例中，所使用的硬件设备以及硬件标定的方式与第一实施例中完全相同，此处不再赘述。
如图5所示的光谱反射率的确定方法可以包括：
S201：获取配准深度图和目标光谱图像。
设备获取配准深度图和目标光谱图像。其中，配准深度图是成像光谱设备观测得到的深度图。目标光谱图像可以为扣除暗场数据后的光谱图像。
具体来说，在获取配准深度图时，获取由3D测量设备输出的初始深度图；根据目标外参数、成像光谱设备的第一内参数和3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
在获取目标光谱图像时，设备获取初始光谱图像和暗场图像；根据初始光谱图像和暗场图像得到目标光谱图像。
其中，S201中获取配准深度图和目标光谱图像的方式与相关的细节，与第一实施例中的S101一致，可以参阅S101中的相关描述，此处不再赘述。
S202：从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值。
设备选取目标点，目标点为某波段目标光谱图像中待测物体上的任一点。设备从配准深度图中获取目标点的深度信息。具体来说，目标点的深度信息可 以直接从配准深度图中读取到。举例来说，假设A点在目标光谱图像中的坐标为(m,n)，则直接读取配准深度图中坐标为(m,n)的点的深度值，即为A点的深度信息。
设备从目标光谱图像中获取目标点的第一灰度值，目标点的第一灰度值可以从目标光谱图像中直接读取。
S203：根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息。
S203中，计算目标点在成像光谱设备对应的坐标系下的三维坐标信息与第一实施例中S1071中设备根据目标点的深度信息、成像光谱设备的第一内参数和目标点在所述目标光谱图像中的第一坐标信息，计算得到目标点在成像光谱设备对应的坐标系下的第一三维坐标的方法完全一致，可以参阅S1071中的相关描述，此处不再赘述。
S204：根据所述目标点的邻域点确定所述目标点对应的法线向量信息。
设备根据目标点的邻域点确定目标点对应的法线向量信息，设备先确定目标点的邻域点，目标点的邻域，不做具体限定，比如可以选择以目标点为中心，21*21像素窗口，或31*31像素，或71*71像素，作为目标点的邻域。其中，在确定邻域时，一般选宽度为奇数的窗口。
设备可以根据目标点的邻域点确定目标点对应的法线向量信息，可以利用预设的算法对邻域点的坐标进行计算，得到目标点对应的法线向量信息。
具体来说，设备根据目标点的邻域点确定邻域点所形成的空间曲面，并根据空间曲面获取目标点对应法线向量信息。目标点的邻域点所形成的空间曲面即为这些邻域点的形成的表面轮廓，具体可以通过确定这些邻域点的三维坐标来确定，这里计算邻域点的三维坐标的方法可以第一实施例中第一三维坐标的计算方法，此处不再赘述。设备可以根据主成分分析算法对空间曲面进行分析计算，获取目标点对应法线向量信息。
S205：将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值。
设备中存储预设漫反射板全光照模型，其中，预设漫反射板全光照模型的输入为三维坐标信息和法线向量信息，三维坐标信息和所述法线向量信息的输出为修正后的第二灰度值。预设漫反射板全光照模型可以是直接由设备预先训练好，也可以由其他设备预先完成训练后，移植到本端设备中。
设备将三维坐标信息和法线向量信息输入预设漫反射板全光照模型，得到第二灰度值。第二灰度值即为在当前复杂光照条件下，与目标点A点相同距离与姿态的漫反射板的观测灰度值。
一种实施方式中，设备可以预先进行建模，通过对获取到的数据进行拟合，得到预设漫反射板全光照模型。在建模阶段，首先固定某一波长，设为目标波长，获取某个位置姿态的数据。设备获取目标波长下各个预设的位置姿态的样本数据，对样本数据进行拟合处理，得到预设漫反射板全光照模型。
其中，样本数据包括样本点的样本灰度值、样本法线向量信息和样本三维坐标信息。以漫反射板中心点C点为例，提取漫反射板中心点C的样本灰度值DN，漫反射板中心点C点的样本三维坐标信息(X,Y,Z)，漫反射板的样本法线向量信息[m,n,k]，得到一组数据[DN,X,Y,Z,m,n,k]；提取该波长下各个预设的位置姿态的数据。利用所有的这些数据，拟合漫反射板样本灰度值DN与(X,Y,Z,m,n,k)的关系。拟合函数的具体形式不做限定，可以统一表示如下：
DN＝F(X,Y,Z,m,n,k)
即当光照条件固定时，给定漫反射板的任意距离与姿态，模型可以输出成像光谱仪对该位置姿态的漫反射板的观测灰度值。对成像光谱仪工作的所有波段进行上述操作，即可得到漫反射板全光照模型，即预设漫反射板全光照模型。
S206：获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
设备获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值DN 0和 第二灰度值DN 2计算目标点的反射率。已知漫反射板的反射率为ρ r利用修正后的第二灰度值DN 2计算目标点反射率ρ A如下：
Figure PCTCN2022080525-appb-000007
设备可以对待测物体上的每一个目标点进行上述计算，得到所有目标点的反射率，对所有波段重复上述操作，然后，设备根据所有目标点的反射率，确定待测物体所有点的光谱反射率曲线。
本申请实施例中，获取配准深度图和目标光谱图像；从配准深度图中获取目标点的深度信息，并获取目标点的第一灰度值；根据目标点的深度信息、成像光谱设备的第一内参数和目标点在所述目标光谱图像中的第一坐标信息，计算得到目标点的三维坐标信息；根据目标点的邻域点确定目标点对应的法线向量信息；将三维坐标信息和法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；获取漫反射板的反射率，根据漫反射板的反射率、第一灰度值和第二灰度值计算目标点的反射率。上述方法，针对面光源或其他复杂光照条件，在进行光谱反射率的测量时，通过对一个确定位置与姿态的漫反射板的灰度值进行修正，得到一个与待测物体三维形貌完全相同的“漫反射体”，放在与待测物体完全相同的位置，此时“漫反射体”的各个部位与待测物体的相同部位接收到的辐照度完全相同，再来计算光谱反射率。这样就避免了待测物体接收的辐照度与漫反射板接收的辐照度在某些场景下差异较大，进一步避免了光谱反射率在计算时可能出现的误差，也可以为近距光谱应用提供更精确的数据源。
应理解，上述实施例中各步骤的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
请参见图6，图6是本申请第三实施例提供的光谱反射率的确定设备的示意图。包括的各单元用于执行图5对应的实施例中的各步骤。具体请参阅图5对应的实施例中的相关描述。为了便于说明，仅示出了与本实施例相关的部分。参见图6，光谱反射率的确定设备6包括：
第一获取单元610，用于获取配准深度图和目标光谱图像；
第二获取单元620，用于从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
第一计算单元630，用于根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
确定单元640，用于根据所述目标点的邻域点确定所述目标点对应的法线向量信息；
第一处理单元650，用于将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
第二计算单元660，用于获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
进一步地，所述第一获取单元610，具体用于：
获取由3D测量设备输出的初始深度图；
根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
进一步地，光谱反射率的确定装置6，还包括：
第三获取单元，用于获取初始光谱图像和暗场图像；
第二处理单元，用于根据所述初始光谱图像和所述暗场图像得到目标光谱图像。
进一步地，光谱反射率的确定装置6，还包括：
第三获取单元，用于获取目标波长下各个预设的位置姿态的样本数据；所述样本数据包括样本点的样本灰度值、样本法线向量信息和样本三维坐标信息；
第三处理单元，用于对所述样本数据进行拟合处理，得到预设漫反射板全光照模型。
进一步地，光谱反射率的确定装置6，还包括：
第四处理单元，用于根据所述配准深度图中所有所述目标点的反射率，确定所述待测物体的光谱反射率曲线。
进一步地，所述确定单元640，具体用于：
根据所述目标点的邻域点确定所述邻域点所形成的空间曲面，并根据所述空间曲面获取所述目标点对应法线向量信息。
图7是本申请第四实施例提供的光谱反射率的确定设备的示意图。如图7所示，该实施例的光谱反射率的确定设备7包括：处理器70、存储器71以及存储在所述存储器71中并可在所述处理器70上运行的计算机程序72，例如光谱反射率的确定程序。所述处理器70执行所述计算机程序72时实现上述各个光谱反射率的确定方法实施例中的步骤，例如图5所示的步骤201至206。或者，所述处理器70执行所述计算机程序72时实现上述各装置实施例中各模块/单元的功能，例如图6所示模块610至660的功能。
示例性的，所述计算机程序72可以被分割成一个或多个模块/单元，所述一个或者多个模块/单元被存储在所述存储器71中，并由所述处理器70执行，以完成本申请。所述一个或多个模块/单元可以是能够完成特定功能的一系列计算机程序指令段，该指令段用于描述所述计算机程序72在所述光谱反射率的确定设备7中的执行过程。例如，所述计算机程序72可以被分割成第一获取单元、第二获取单元、第一计算单元、确定单元、第一处理单元、第二计算单元，各单元具体功能如下：
第一获取单元，用于获取配准深度图和目标光谱图像；
第二获取单元，用于从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
第一计算单元，用于根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
确定单元，用于根据所述目标点的邻域点确定所述目标点对应的法线向量 信息；
第一处理单元，用于将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
第二计算单元，用于获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
所述光谱反射率的确定设备可包括，但不仅限于，处理器70、存储器71。本领域技术人员可以理解，图7仅仅是光谱反射率的确定设备7的示例，并不构成对光谱反射率的确定设备7的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件，例如所述光谱反射率的确定设备还可以包括输入输出设备、网络接入设备、总线等。
所称处理器70可以是中央处理单元(Central Processing Unit，CPU)，还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
所述存储器71可以是所述光谱反射率的确定设备7的内部存储单元，例如光谱反射率的确定设备7的硬盘或内存。所述存储器71也可以是所述光谱反射率的确定设备7的外部存储设备，例如所述光谱反射率的确定设备7上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等。进一步地，所述光谱反射率的确定设备7还可以既包括所述光谱反射率的确定设备7的内部存储单元也包括外部存储设备。所述存储器71用于存储所述计算机程序以及所述光谱反射率的确定设备所需的其他程序和数据。所述存储器71还可以用于暂时地存储已经输出或者将要输出的数据。
需要说明的是，上述装置/单元之间的信息交互、执行过程等内容，由于与 本申请方法实施例基于同一构思，其具体功能及带来的技术效果，具体可参见方法实施例部分，此处不再赘述。
本申请实施例还提供了一种网络设备，该网络设备包括：至少一个处理器、存储器以及存储在所述存储器中并可在所述至少一个处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述任意各个方法实施例中的步骤。
本申请实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现可实现上述各个方法实施例中的步骤。
本申请实施例提供了一种计算机程序产品，当计算机程序产品在移动终端上运行时，使得移动终端执行时实现可实现上述各个方法实施例中的步骤。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实现上述实施例方法中的全部或部分流程，可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一计算机可读存储介质中，该计算机程序在被处理器执行时，可实现上述各个方法实施例的步骤。其中，所述计算机程序包括计算机程序代码，所述计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。所述计算机可读介质至少可以包括：能够将计算机程序代码携带到拍照装置/终端设备的任何实体或装置、记录介质、计算机存储器、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、电载波信号、电信信号以及软件分发介质。例如U盘、移动硬盘、磁碟或者光盘等。在某些司法管辖区，根据立法和专利实践，计算机可读介质不可以是电载波信号和电信信号。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述或记载的部分，可以参见其它实施例的相关描述。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来 实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的实施例中，应该理解到，所揭露的装置/网络设备和方法，可以通过其它的方式实现。例如，以上所描述的装置/网络设备实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通讯连接可以是通过一些接口，装置或单元的间接耦合或通讯连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
以上所述实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围之内。

Claims (10)

  1. 一种光谱反射率的确定方法，其特征在于，包括：
    获取配准深度图和目标光谱图像；
    从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
    根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
    根据所述目标点的邻域点确定所述目标点对应的法线向量信息；
    将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
    获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
  2. 如权利要求1所述的光谱反射率的确定方法，其特征在于，所述获取配准深度图，包括：
    获取由3D测量设备输出的初始深度图；
    根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
  3. 如权利要求1所述的光谱反射率的确定方法，其特征在于，在所述获取配准深度图和目标光谱图像之前，还包括：
    获取初始光谱图像和暗场图像；
    根据所述初始光谱图像和所述暗场图像得到所述目标光谱图像。
  4. 如权利要求1所述的光谱反射率的确定方法，其特征在于，在所述将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值之前，还包括：
    获取目标波长下各个预设的位置姿态的样本数据；所述样本数据包括样本 点的样本灰度值、样本法线向量信息和样本三维坐标信息；
    对所述样本数据进行拟合处理，得到预设漫反射板全光照模型。
  5. 如权利要求1所述的光谱反射率的确定方法，其特征在于，在所述获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率之后，还包括：
    根据所述配准深度图中所有所述目标点的反射率，确定所述待测物体的光谱反射率曲线。
  6. 如权利要求1所述的光谱反射率的确定方法，其特征在于，所述根据所述目标点的邻域点确定所述目标点对应的法线向量信息，包括：
    根据所述目标点的邻域点确定所述邻域点所形成的空间曲面，并根据所述空间曲面获取所述目标点对应法线向量信息。
  7. 一种光谱反射率的确定装置，其特征在于，包括：
    第一获取单元，用于获取配准深度图和目标光谱图像；
    第二获取单元，用于从所述配准深度图中获取目标点的深度信息，并从所述目标光谱图像中获取所述目标点的第一灰度值；
    第一计算单元，用于根据所述目标点的深度信息、成像光谱设备的第一内参数和所述目标点在所述目标光谱图像中的第一坐标信息，计算得到所述目标点在所述成像光谱设备对应的坐标系下的三维坐标信息；
    确定单元，用于根据所述目标点的邻域点确定所述目标点对应的法线向量信息；
    第一处理单元，用于将所述三维坐标信息和所述法线向量信息输入预设漫反射板全光照模型，得到第二灰度值；
    第二计算单元，用于获取所述漫反射板的反射率，根据所述漫反射板的反射率、所述第一灰度值和所述第二灰度值计算所述目标点的反射率。
  8. 如权利要求7所述的光谱反射率的确定装置，其特征在于，所述第一获取单元，具体用于：
    获取由3D测量设备输出的初始深度图；
    根据目标外参数、成像光谱设备的第一内参数和所述3D测量设备的第二内参数，将所述初始深度图转换为配准深度图。
  9. 一种光谱反射率的确定设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1至6任一项所述的方法。
  10. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至6任一项所述的方法。
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