Method for evaluating illumination environment space brightness by using HDR panoramic image

Abstract

The invention discloses a method for evaluating the brightness of a light environment space by using an HDR panoramic image, and the method comprises the following steps: 1, shooting and synthesizing a high dynamic range panoramic image in a to-be-evaluated light environment space; step 2, performing brightness calibration on the high dynamic range panoramic image synthesized in the step 1; 3, the main light source is shaded based on a brightness threshold value method, and a shaded high-dynamic-range panoramic image is obtained; and step 4, performing brightness calculation of the light environment space on the masked panoramic image with the high dynamic range to obtain average indirect visual brightness or average indirect panoramic illumination for quantitative evaluation of the brightness of the light environment space. The invention is beneficial to solving the problem of actual measurement of the space brightness.

Description

Technical Field

[0001] The present invention relates to a method for evaluating brightness, in particular to a method for evaluating the spatial brightness of an illumination environment using an HDR panoramic image. Background Art

[0002] The information provided in this section is only background information related to the present disclosure and is not necessarily prior art.

[0003] With the development of technology and the changes in living and working styles, the focus of indoor lighting has gradually shifted from the illuminance distribution on the working surface to the pursuit of overall high-quality lighting in the space.

[0004] First, the way of reading and writing on paper documents has been mostly replaced by self-luminous screens, and complex manual and visual tasks are often completed through automation technology. Therefore, the demand for high working surface illuminance in indoor lighting has gradually decreased. Second, the development of new and more efficient lighting technologies (such as LED lighting) has made lighting planning and control more flexible. Therefore, in addition to meeting the basic function of making the illuminated object visible, the creation of the comfort, aesthetics, and safety of the illuminated space has received increasing attention.

[0005] In the international lighting standard vocabulary CIE (International Commission on Illumination), "spatial brightness" is defined as the subjective perception of the degree to which a space is illuminated when an observer is in the space or the space occupies most of the observer's field of view. See 2021.E-ILV, 17-22-060 Spatial brightness, which is comprehensively affected by factors such as the luminous flux and intensity distribution of the light source, the reflectivity of the surfaces in the illuminated space, and the layout of the light sources.

[0006] Research shows that higher spatial brightness can improve the visual comfort of observers, thereby improving visual perception, visual communication, and visual experience. Good spatial brightness lighting design can not only provide higher visual comfort, but also improve the functionality and energy-saving effect of the space, which is crucial in architectural design and interior design.

[0007] The mean room surface exitance (MRSE) is a method for measuring spatial brightness proposed by Christopher (Kit) Cuttle, the winner of the Lifetime Achievement Award in Lighting, to evaluate the average exitant luminous flux of all surfaces in a room. That is, MRSE excludes the direct luminous flux from the light source and only considers the indirect luminous flux reflected from the room surfaces, because the human eye's perception of spatial brightness is mainly determined by the reflected luminous flux, and because direct light sources are likely to cause uncomfortable glare, and the human eye will consciously avoid them when the line of sight moves in the space.

[0008] Since the calculation of the average room surface exitance (MRSE) requires excluding the contribution of direct light sources, and it is difficult for general measurement equipment to distinguish the luminous flux of direct light sources and reflected light, it is difficult to actually measure the spatial brightness.

[0009] It should be noted that the information disclosed in the above background art section is only used to enhance the understanding of the background of the present disclosure, and thus may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0010] Object of the Invention: The technical problem to be solved by the present invention is to provide a method for evaluating the spatial brightness of an illumination environment using an HDR panoramic image in view of the deficiencies of the prior art.

[0011] To solve the above technical problem, the present invention discloses a method for evaluating the spatial brightness of an illumination environment using an HDR panoramic image, including the following steps:

[0012] Step 1, within the illumination environment space to be evaluated, capture and synthesize a high-dynamic-range panoramic image;

[0013] Step 2, perform brightness calibration on the high-dynamic-range panoramic image synthesized in Step 1;

[0014] Step 3, mask the main light sources using a brightness threshold method to obtain a masked high-dynamic-range panoramic image;

[0015] Step 4, perform brightness calculation on the masked high-dynamic-range panoramic image for the illumination environment space to obtain the average indirect visible brightness or average indirect panoramic illuminance, which is used to quantitatively evaluate the spatial brightness of the illumination environment space.

[0016] Further, the capturing and synthesizing of the high-dynamic-range panoramic image in Step 1 includes:

[0017] Step 1-1, within the illumination environment space to be evaluated, a fixed camera takes a set of low-dynamic-range images at different exposure durations at equal intervals in the same shooting direction, where the brightest point in the low-dynamic-range images is not overexposed at the lowest exposure duration, and the darkest point is not overexposed at the highest exposure duration;

[0018] Step 1-2, change the shooting direction and take another set of low-dynamic-range images according to the method of Step 1-1 until all images cover all azimuth angles in the illumination environment space to be evaluated;

[0019] Step 1-3, synthesize each set of captured low-dynamic-range images into a high-dynamic-range image;

[0020] Steps 1-4: Stitch all the synthesized high-dynamic range images to form a high-dynamic range panoramic image.

[0021] Furthermore, the brightness calibration described in Step 2 includes:

[0022] Step 2-1: At the camera position during shooting in Step 1, use a regular tetrahedron illuminometer to measure, record the illuminance values in four directions of the regular tetrahedron, and calculate the panoramic illuminance value E. 全景 ;

[0023] Step 2-2: For the high-dynamic range panoramic image synthesized in Step 1, calculate a single-channel high-dynamic range panoramic grayscale image through the Y value in the XYZ color space, and use the spherical harmonic function decomposition method to calculate the uncalibrated panoramic illuminance value E. 全景-未校准 ;

[0024] Step 2-3: Compare the panoramic illuminance value E described in Step 2-1 全景 and the uncalibrated panoramic illuminance value E described in Step 2-2 全景-未校准 , and calculate the brightness calibration coefficient k of the high-dynamic range panoramic image.

[0025] Step 2-4: Multiply the brightness calibration coefficient k by the single-channel high-dynamic range panoramic grayscale image without brightness calibration to obtain a panoramic image of the true brightness distribution.

[0026] Furthermore, the calculation of the uncalibrated panoramic illuminance value E using the spherical harmonic function decomposition method described in Step 2-2 全景-未校准 includes:

[0027]

[0028] where d(L 0 ) represents the optical flow density of the uncalibrated high-dynamic range brightness distribution panoramic image, which is calculated from the zero-order coefficient of the spherical harmonic function decomposition of the high-dynamic range brightness distribution panoramic image.

[0029] Furthermore, the calculation of the zero-order coefficient of the spherical harmonic function decomposition of the high-dynamic range brightness distribution panoramic image described in Step 2-2 is as follows:

[0030] Expand any spatial brightness distribution function using spherical harmonics as the basis, which is expressed as follows:

[0031]

[0032] where is the coefficient, is the spherical harmonic basis function, l represents the order of the spherical harmonic function, m represents the order of the spherical harmonic function, and θ represents the polar angle. Indicates the azimuth angle;

[0033] Luminance distribution function Expressed as a combination of coefficient vectors of all orders SH(f), which is expressed as follows:

[0034] SH(f) = {SH 0 (f), SH 1 (f), SH 2 (f), …}

[0035] Among them, the coefficient vector SH of the l-th order l (f) is expressed as follows:

[0036]

[0037] The intensity d(SH l ) of the l-th order is calculated as follows:

[0038]

[0039] Among them, the 0-th order is d(L 0 ).

[0040] Furthermore, in step 3, the main light source is masked using the luminance threshold method, that is, in the true luminance distribution panoramic image obtained in steps 2 - 4, the luminance and azimuth information of the direct light source and the reflecting surface are separated, that is, the direct light source is screened out by the luminance threshold method and masked.

[0041] Furthermore, screening out the direct light source by the luminance threshold method and masking it in step 3 includes:

[0042] Step 3 - 1, set the luminance threshold, and identify the area in the true luminance distribution panoramic image with a luminance value higher than this threshold as the direct light source area;

[0043] Step 3 - 2, use the histogram equalization method to highlight the direct light source area;

[0044] Step 3 - 3, generate a binary mask image according to the luminance threshold, set the area with a luminance higher than the luminance threshold to black, and keep other areas unchanged;

[0045] Step 3 - 4, perform a smooth transition process on the black area.

[0046] Furthermore, in step 4, the calculation of the brightness of the illumination environment space is performed, that is, for the masked high - dynamic range panoramic image, the average indirect panoramic illuminance and the average indirect visible luminance of the measurement points in the illumination environment space are calculated through the spherical harmonic function decomposition method and the reciprocity method of luminance - illuminance related indicators.

[0047] Further, the spherical harmonic function decomposition method described in step 4 is the same as the spherical harmonic function decomposition method described in step 2-2, and is expressed as follows:

[0048]

[0049] where d(L ′ 0 ) represents the optical flow density of the masked high-dynamic range panoramic image.

[0050] Further, the reciprocity method of the luminance-illuminance related index described in step 4 includes:

[0051]

[0052] where L 平均间接可视亮度 represents the average indirect visible luminance, and E 平均间接全景照度 represents the average indirect panoramic illuminance.

[0053] Beneficial effects:

[0054] 1. The present invention extracts the luminance information contained in the high-dynamic range panoramic image and applies it to calculate the relevant indexes of the spatial brightness of the lighting environment. Using the reciprocity algorithm of the luminance-related index and the illuminance-related index proposed by the present invention, the complexity of the calculation and measurement process can be simplified, and the application of HDR panoramic images in the field of spatial brightness evaluation of the lighting environment can be explored.

[0055] 2. In the method proposed by the present invention, the high-dynamic range panoramic image after luminance calibration records the luminance values in all directions within the space, and the direct light source can be conveniently identified and filtered out. Then, the average indirect visible luminance and the average indirect panoramic illuminance around the measurement point can be calculated by using the spherical harmonic function decomposition method, which is used to quantify the brightness of the lighting space. The proposed method is beneficial to solving the actual measurement problem of spatial brightness. Description of the drawings

[0056] The following further specifically describes the present invention in conjunction with the drawings and specific embodiments, and the above and / or other advantages of the present invention will become clearer.

[0057] Figure 1 is the system block diagram of the present invention.

[0058] Figure 2 is the schematic diagram of the high-dynamic range panoramic images of 4 natural scenes and the effect of light source masking.

[0059] Figure 3 is the schematic diagram of the spherical harmonic function decomposition of the high-dynamic range panoramic image.

[0060] Figure 4It is a schematic diagram of projecting the brightness distribution map with the direct light source filtered out onto a unit sphere centered at the shooting point using the projection method. Detailed implementation manners

[0061] High-dynamic-range panoramic images use 32-bit floating-point numbers to store data. Compared with general picture formats, they can record more complete brightness range information in the scene. After brightness calibration, the threshold method can be used to quickly identify direct light sources, which can then be used for spatial brightness calculation and measurement.

[0062] After the high-dynamic-range panoramic images are brightness-calibrated and the direct light sources are filtered out, by applying the spherical harmonic (SH) function decomposition method and the reciprocity algorithm of the brightness-illuminance related indicators proposed in this paper, the average indirect visible brightness and the average indirect panoramic illuminance around the observation position can be quickly calculated, and then used to quantify the spatial brightness of the lighting environment.

[0063] The present invention extracts the contained brightness information from high-dynamic-range panoramic images and applies it to calculate the relevant indicators of the spatial brightness of the lighting environment. At the same time, by using the reciprocity algorithm of the brightness-related indicators and the illuminance-related indicators proposed in the present invention, the complexity of the calculation and measurement process can be simplified, and the application of HDR panoramic images in the field of spatial brightness evaluation of the lighting environment can be explored.

[0064] The present invention can be realized through the following technical solutions:

[0065] Step 1, adopt the high-dynamic-range panoramic image synthesis method to shoot and synthesize high-dynamic-range panoramic images, which is convenient for subsequent steps to perform brightness calibration on the high-dynamic-range panoramic images. This method includes:

[0066] Shooting of LDR panoramic images and synthesis of HDR panoramic images. Each high-dynamic-range image is synthesized from multiple low-dynamic-range images. A series of LDR perspective-limited images are taken at equal intervals with different exposure durations using a camera fixed by a tripod, ensuring that the brightest point in the scene is not overexposed at the lowest exposure duration and the darkest point is not overexposed at the highest exposure duration.

[0067] The sequence of the captured low-dynamic-range perspective-limited images is synthesized into high-dynamic-range perspective-limited images by high-dynamic-range image synthesis software.

[0068] The synthesized group of high-dynamic-range perspective-limited images is synthesized into high-dynamic-range panoramic images by panoramic stitching software.

[0069] Step 2: Use a brightness calibration algorithm to calibrate the brightness of the high-dynamic-range panoramic image synthesized in Step 1. Due to the synthesis error of the dynamic range and the significant difference between the response of the camera sensor to light and the human visual system, it is necessary to calibrate the brightness of the high-dynamic-range panoramic image synthesized in the previous step to facilitate recording the brightness values in all directions and identifying direct light sources in subsequent steps.

[0070] Measure at the high-dynamic-range panoramic image shooting position using a regular tetrahedron illuminometer, and record the illuminance values E in four directions of the regular tetrahedron 1 , E 2 , E 3 , E 4 and calculate the panoramic illuminance value E 全景 =(E 1 +E 2 +E 3 +E 4 ) / 4

[0071] Extract a single-channel high-dynamic-range panoramic grayscale image from the synthesized high-dynamic-range panoramic image according to Y = 179*(0.2126*R + 0.7152*G + 0.0722*B), and calculate the panoramic illuminance value E using the spherical harmonic function decomposition method 全景-未校准 ;

[0072] Compare the panoramic illuminance value E 全景 obtained by the illuminometer and the panoramic illuminance value E 全景-未校准 obtained by spherical harmonic decomposition, and calculate the brightness calibration coefficient k of the HDR panoramic image.

[0073] Multiply the brightness calibration coefficient k calculated in the above steps by the single-channel high-dynamic-range panoramic grayscale image without brightness calibration to obtain the true brightness values of each pixel in the panoramic image, that is, the panoramic image of the true brightness distribution;

[0074] Step 3: Mask the main light source using the brightness threshold method. Use the brightness and position information of both the direct light source and the reflecting surface in the true brightness distribution panoramic image generated in the previous step, and screen out the direct light source through the brightness threshold method for light source masking. The method of masking the main light source based on the brightness threshold method includes:

[0075] Set a brightness threshold (such as 1500 cd / m2), automatically screen out the areas where the brightness exceeds this threshold, and these areas are the direct light sources. Use the histogram equalization algorithm for image enhancement to highlight the direct light source area.

[0076] Once the light source area is identified, the next step is to create a mask to cover the direct light source part. According to the brightness value threshold, a binary mask image is generated, where the areas with brightness higher than the threshold are black (blocking the direct light source), and other areas remain unchanged. Then, the area around the light source is smoothed to ensure a natural transition of the mask area and avoid abrupt boundaries.

[0077] Step 4: Calculate the spatial brightness of the lighting environment. After using the brightness threshold method to mask the direct light source, the contribution of the direct luminous flux from the direct light source to the illuminance is filtered out, which facilitates the calculation of the average indirect panoramic illuminance and the average indirect visible brightness.

[0078] Based on the spherical harmonic function decomposition of the panoramic brightness map after filtering the light source, the zero-order coefficient intensity d(L ′ 0 ) is obtained. According to the reciprocity algorithm of the brightness-illuminance related indicators, that is the average indirect panoramic illuminance E of the measurement points in the lighting space can be calculated 平均间接全景照度 and the average indirect visible brightness L 平均间接可视亮度 , and then the spatial brightness degree of the lighting environment is quantified.

[0079] Embodiment:

[0080] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0081] As Figure 1 shown, the present invention is a method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image. This calculation method includes a total of 5 steps: scene selection, image acquisition, brightness calibration, light source masking, and spatial brightness calculation.

[0082] The scene selection includes four scenes: an empty room, a classroom, a meeting room, and an office, which are used as scene examples of the present invention.

[0083] The image acquisition steps are carried out in the selected scenario. The devices involved are the Insta360 pro panoramic camera and the tripod. In the experimental scenario, the panoramic camera is mounted on the tripod and placed in the center of the experimental scenario, connected to the computer by a data cable, and the computer controls the image shooting. The first group (a total of six) of low-dynamic-range images (LDR) is taken with an exposure duration of 1 / 8000s, the second group of images is taken with 1 / 4000s (i.e., twice the exposure duration of the first group of images), and so on until the captured images are all white. When taking the 16th - 18th images, the images appear all white, and the entire shooting process takes about 3 - 5 minutes.

[0084] Use stitching software (such as PTgui) to stitch the six images taken with the fisheye lens at the same exposure at the same moment into 1 low-dynamic-range panoramic image.

[0085] The synthesis of high-dynamic-range images (HDR) is completed by synthesis software (such as Photomatix pro6.1.1). Import the synthesized group of low-dynamic-range image pictures into the synthesis software (such as Photomatix pro) and directly synthesize them into 1 HDR image.

[0086] Measure at the high-dynamic-range panoramic image shooting position using a regular tetrahedron illuminometer, and record the illuminance values E in the normal directions of the four faces of the regular tetrahedron 1 , E 2 , E 3 , E 4 and calculate the panoramic illuminance value E 全景 =(E 1 +E 2 +E 3 +E 4 ) / 4.

[0087] Generate a channel high-dynamic-range panoramic grayscale image from the synthesized high-dynamic-range panorama according to Y = 179*(0.2126*R + 0.7152*G + 0.0722*B). Any spatial luminance distribution function can be expanded using spherical harmonic functions as the basis, expressed as formula (1):

[0088]

[0089] Here, is the coefficient, is the spherical harmonic basis function, and l represents the order of the spherical harmonic function. Figure 3 The real-valued spherical harmonic basis functions up to the second order are given. Each order contains 2l + 1 basis functions. Any order can be represented as a vector of the corresponding coefficients , and the representation of the entire function is SH(f) = {SH 0 (f), SH 1(f),SH 2 (f),…}. The strength of each order can be calculated using formula (2):

[0090]

[0091] d(L 0 ) represents the optical flow density, which can be calculated by the zero-order coefficient of the spherical harmonic decomposition of the high dynamic range brightness distribution panorama.

[0092] Moreover, the average indirect panoramic illumination around the shooting point is related to d(L 0 ) has the following numerical relationship Then find E 全景-未校准 . ;

[0093] Using the measured E 全景 With E 全景-未校准 By comparison, the brightness calibration coefficient k of the high dynamic range panoramic image is calculated.

[0094] The brightness calibration coefficient k calculated in the above step is multiplied by the single-channel high dynamic range panoramic grayscale image that has not been brightness calibrated to obtain the true brightness value of each pixel in the panoramic image, that is, the true brightness distribution panoramic image;

[0095] Set a brightness threshold to automatically filter out areas where the brightness exceeds the threshold. These areas are where the direct light source is located (the threshold is set to 1500cd / m2 in this measurement practice, and the threshold can be adjusted according to actual conditions until the direct light source is identified). Use the histogram equalization algorithm to enhance the image and highlight the direct light source area.

[0096] like Figure 2 As shown in the figure, once the light source area is identified, the next step is to create a mask to cover the direct light source part. According to the brightness value threshold, a binary mask image is generated. The area with brightness higher than the threshold is black (blocking the direct light source), and the other areas remain unchanged. Then the area around the direct light source is smoothed to ensure a natural transition in the mask area and avoid abrupt boundaries. The direct light source is masked to form a new brightness distribution.

[0097] like Figure 3 As shown in Figure 1, the high dynamic range panoramic image records the distribution of brightness in space. Any spatial brightness distribution function can be expanded using spherical harmonics as the basis, as shown in formula (1):

[0098]

[0099] here, is the coefficient, is a spherical harmonic basis function, where l represents the order of the spherical harmonic function. Figure 3 gives real-valued spherical harmonic basis functions up to the second order, with 2l + 1 basis functions for each order. Any order can be represented as a vector of corresponding coefficients and the representation of the entire function is the combination of all orders SH(f) = {SH 0 (f), SH 1 (f), SH 2 (f),...}. The intensity of each order can be calculated using Equation (2):

[0100]

[0101] d(L′ 0 ) represents the indirect optical flow density after the direct light source is masked, which can be calculated from the zero-order coefficient of the spherical harmonic function decomposition of the high-dynamic-range luminance distribution panorama after the direct light source is masked.

[0102] If the resolution of the HDR panorama is X * Y pixels (i.e., X = 2Y), assuming it is projected onto a sphere centered at the shooting position with a radius of R = X / (2π). Then, for the observer, the average visible luminance on the inner surface of this panoramic projection sphere is L average = L all / (4π·R 2 ), where L all is the sum of all luminances on this sphere. Therefore, there is the following relationship between d(L 0 ) and L average :

[0103]

[0104] In addition, there is the following numerical relationship between the panoramic illuminance E 全景 around the shooting point and d(L 0 )

[0105] From this, Equation (4) can be obtained:

[0106]

[0107] After filtering out the direct light source on the luminance distribution panorama to form a new luminance distribution Similarly, the intensity of the zero-order component of the spherical harmonic function decomposition can be calculated according to the above method to obtain the average indirect visible luminance L 平均间接可视亮度 and the average indirect panoramic illuminance E 平均间接全景照度 around the measured point. That is, a reciprocal algorithm for obtaining luminance-illuminance related indicators, such as Equation (5):

[0108]

[0109] Both the average indirect visual brightness and the average indirect panoramic illuminance can be used to quantify the brightness of an illuminated space.

[0110] In four natural example scenarios, the present invention uses the projection method to verify the algorithm for quantifying the spatial brightness based on the spherical harmonic function decomposition method.

[0111] Using the projection method, the brightness distribution map with direct light sources filtered out is projected onto a unit sphere centered at the shooting point, as Figure 4 shown, and then the average indirect visual brightness L 平均间接可视亮度 ,

[0112] Furthermore, according to the inverse square law of brightness and illuminance, the illuminance values received at each azimuth around the shooting point under the illumination of this brightness distribution map are calculated and averaged to obtain the average indirect panoramic illuminance E 平均间接全景照度 around the measured point. The comparison results of the spatial brightness quantization index obtained based on the projection method and the index obtained based on the spherical harmonic function decomposition method are shown in Table 1.

[0113] Table 1 Comparison results table for four natural scenarios

[0114]

[0115] In specific implementation, the present application provides a computer storage medium and a corresponding data processing unit. Among them, the computer storage medium can store a computer program, and when the computer program is executed by the data processing unit, it can run the inventive content of a method for evaluating the spatial brightness of an illumination environment using an HDR panoramic image provided by the present invention and some or all of the steps in each embodiment. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0116] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the present invention can be implemented by means of a computer program and its corresponding general hardware platform. Based on such an understanding, the technical solutions in the embodiments of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a computer program, that is, a software product. This computer program software product can be stored in the storage medium and includes several instructions to enable a device (which can be a personal computer, a server, a single-chip microcomputer, an MCU, or a network device, etc.) including a data processing unit to execute the methods described in each embodiment or some parts of the embodiments of the present invention.

[0117] The present invention provides an idea and method for evaluating the brightness of the lighting environment space using HDR panoramic images. There are many methods and ways to specifically implement this technical solution. The above description is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention. Each component not clearly defined in this embodiment can be implemented using existing technologies.

Claims

1. A method for evaluating the spatial brightness of an illumination environment using an HDR panoramic image, characterized in that: The following steps are involved: Step 1, capturing and synthesizing a high dynamic range panoramic image in the lighting environment space to be evaluated; Step 2, performing brightness calibration on the high dynamic range panoramic image synthesized in step 1; Step 3, masking the main light source using a brightness threshold method to obtain a masked high dynamic range panoramic image; Step 4, calculating the brightness of the lighting environment space for the masked high dynamic range panoramic image to obtain the average indirect visible brightness or the average indirect panoramic illumination, which is used to quantitatively evaluate the brightness of the lighting environment space.

2. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 1, characterized in that: The process of capturing and synthesizing a high dynamic range panoramic image as described in step 1 includes: Step 1-1, in the lighting environment space to be evaluated, a fixed camera is used to shoot a group of low dynamic range images at equal intervals with different exposure times in the same shooting direction, wherein the brightest point in the low dynamic range image is not overexposed at the shortest exposure time, and the darkest point is not overexposed at the longest exposure time; Step 1-2, changing the shooting direction, and shooting another set of low dynamic range images according to the method of step 1-1, until all images cover all azimuth angles in the illumination environment space to be evaluated; Step 1-3, synthesizing each set of low dynamic range images taken into a high dynamic range image; Steps 1-4, all synthesized high dynamic range images are panorama stitched to synthesize a high dynamic range panoramic image.

3. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 2, characterized in that: Perform brightness calibration as described in step 2, including: Step 2-1: The camera position when shooting in step 1 is measured using a tetrahedron illuminance meter, and the illuminance values ​​in the four directions of the tetrahedron are recorded and the panoramic illuminance value E is calculated. 全景 ; Step 2-2: The high dynamic range panoramic image synthesized in step 1 is used to calculate the Y value of the XYZ color space to obtain a single-channel high dynamic range panoramic grayscale image, and the uncalibrated panoramic illumination value E is calculated using the spherical harmonic decomposition method. 全景-未校准 ; Step 2-3, compare the panoramic illumination value E described in step 2-1 全景 and the uncalibrated panoramic illumination value E described in step 2-2 全景-未校准 , calculate the brightness calibration coefficient k of the high dynamic range panoramic image; Step 2-4, multiplying the brightness calibration coefficient k by the single-channel high dynamic range panoramic grayscale image that has not been brightness calibrated to obtain a true brightness distribution panoramic image.

4. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 3, characterized in that: The uncalibrated panoramic illumination value E is calculated using the spherical harmonic decomposition method described in step 2-2. 全景-未校准 ,include: Wherein, d(L0) represents the optical flow density of the uncalibrated high dynamic range brightness distribution panoramic image, which is calculated by the zero-order coefficient of the spherical harmonic function decomposition of the high dynamic range brightness distribution panoramic image.

5. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 4, characterized in that: The calculation of the zero-order coefficients of the spherical harmonic decomposition of the high dynamic range brightness distribution panoramic image described in step 2-2 is as follows: The arbitrary spatial brightness distribution function Using spherical harmonics as the basis expansion, it is expressed as follows: in, is the coefficient, is the spherical harmonic basis function, l represents the order of the spherical harmonic function, m represents the order of the spherical harmonic function, θ represents the polar angle, Indicates azimuth; Brightness distribution function It is represented as a combination of all order coefficient vectors SH(f), expressed as follows: SH(f)={SH0(f),SH1(f),SH2(f),…} Among them, the l-th order coefficient vector SH l (f) is expressed as follows: The strength of the first order d(SH l ) is calculated as follows: Among them, the 0th order is d(L0).

6. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 5, characterized in that: The method described in step 3 of masking the main light source based on the brightness threshold is to separate the brightness and orientation information of the direct light source and the reflective surface contained in the real brightness distribution panorama obtained in steps 2-4, that is, to filter out the direct light source through the brightness threshold method and mask it.

7. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 6, characterized in that: The method described in step 3 of filtering out direct light sources by using the brightness threshold method and masking them includes: Step 3-1, setting a brightness threshold, identifying areas in the real brightness distribution panorama with brightness values ​​higher than the threshold as direct light source areas; Step 3-2, using the histogram equalization method to highlight the direct light source area; Step 3-3, generate a binary mask image according to the brightness threshold, set the area with brightness higher than the brightness threshold to black, and keep other areas unchanged; Step 3-4, perform smooth transition processing on the black area.

8. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 7, characterized in that: The brightness calculation of the lighting environment space described in step 4 is to calculate the average indirect panoramic illumination and the average indirect visible brightness of the measurement points in the lighting environment space for the masked high dynamic range panoramic image through the spherical harmonic function decomposition method and the reciprocity method of brightness and illumination related indicators.

9. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 8, characterized in that: The spherical harmonic decomposition method described in step 4 is the same as the spherical harmonic decomposition method described in step 2-2, and is expressed as follows: Among them, d(L ′ 0) represents the optical flow density of the high dynamic range panoramic image after masking.

10. The method for evaluating the spatial brightness of a lighting environment using an HDR panoramic image according to claim 9, characterized in that: The reciprocity method of brightness and illumination related indicators described in step 4 includes: Among them, L 平均间接可视亮度 represents the average indirect visible brightness, E 平均间接全景照度 Represents the average indirect panoramic illumination.

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