A multi-pixel photometric measurement method, device and computer readable storage medium

Abstract

The application discloses a kind of multi-pixel photometric measurement method, equipment and computer readable storage medium, wherein the method comprises: obtaining the exposure parameter and original data of image;According to the distortion parameter of camera, vignetting parameter, flow parameter and the exposure parameter, linear calculation is carried out on the original data, and multi-channel luminance information is obtained;Multi-band color calibration is carried out through the multi-channel luminance information, and the color temperature correction parameter of measured object is calculated;According to the color temperature correction parameter, logarithmic conversion is carried out, and the surface brightness data of the measured object is obtained.The application realizes a kind of multi-pixel photometric measurement scheme based on camera, utilizes camera to complete standard photometric measurement to each pixel, and converts the reading of camera sensor into surface brightness with physical meaning.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of mobile communication, and in particular to a multi-pixel photometric measurement method, device and computer readable storage medium. BACKGROUND

[0002] In the prior art, with the development of the shooting function of intelligent terminals, terminals such as smart phones have been equipped with increasingly powerful sensors and different types of lenses. The combination of these sensors and lenses can achieve various shooting functions such as wide-angle, deep field, and long focus.

[0003] However, the current camera of the intelligent terminal lacks correction of field distortion and calibration of absolute photometry, so it cannot describe the real photometry of the photographed object and background, nor can it quantitatively compare the results obtained by different cameras. SUMMARY

[0004] In order to solve the above technical defects in the prior art, the present application proposes a multi-pixel photometric measurement method, which comprises:

[0005] obtaining the exposure parameters and the original data of the image;

[0006] linearly calculating the original data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters, to obtain multi-channel luminance information;

[0007] performing multi-band color calibration through the multi-channel luminance information, and calculating to obtain the color temperature correction parameters of the measured object;

[0008] performing logarithmic conversion according to the color temperature correction parameters to obtain the surface brightness data of the measured object.

[0009] Optionally, the obtaining of the exposure parameters and the original data of the image comprises:

[0010] obtaining the exposure parameters, wherein the exposure parameters include exposure time, aperture value, sensitivity value, black level value and white balance value;

[0011] obtaining the original data of the image through the LibRaw algorithm library.

[0012] Optionally, the linear calculation of the original data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters to obtain the multi-channel luminance information comprises:

[0013] forming the imaging of the plane perpendicular to the optical axis of the lens composed of equidistant grid points as a first image, and calculating the distortion curve of the lens and the off-axis angle of the optical axis of the lens relative to the lens center axis according to the first image;

[0014] The distortion parameter is determined according to the distortion curve and the off-axis angle.

[0015] Optionally, the linear calculation of the original data according to the distortion parameter, the vignetting parameter, the flux parameter and the exposure parameter of the camera to obtain the multi-channel luminance information further comprises:

[0016] The imaging of a plane with known surface brightness is taken as a second image.

[0017] The vignetting parameter is determined according to the glossiness of the second image and the wallpaper with known surface brightness.

[0018] Optionally, the linear calculation of the original data according to the distortion parameter, the vignetting parameter, the flux parameter and the exposure parameter of the camera to obtain the multi-channel luminance information further comprises:

[0019] The corresponding position of the sky region observed by the night sky quality meter on the focal plane of the lens is determined according to the distortion parameter, and the response difference of the corresponding position with the focal plane position is corrected according to the vignetting parameter.

[0020] The night sky surface brightness calculated by the lens in the simulation of the measurement mode of the night sky quality meter is obtained by integrating the incidence angle luminance curve of the night sky quality meter, and the surface brightness variation curve obtained by the night sky quality meter is compared with the surface brightness variation curve obtained by the lens, and the average value of the surface brightness difference is determined as the flux parameter.

[0021] Optionally, the linear calculation of the original data according to the distortion parameter, the vignetting parameter, the flux parameter and the exposure parameter of the camera to obtain the multi-channel luminance information comprises:

[0022] According to the color filter array, a multi-channel data matrix is extracted in the array of the original data.

[0023] The unit of the multi-channel data matrix is converted from electronic unit to dark sky unit.

[0024] The multi-channel data matrix in dark sky unit is calculated according to the white balance information to obtain the multi-channel surface brightness.

[0025] Optionally, the multi-band color calibration by the multi-channel luminance information and the calculation of the color temperature correction parameter of the measured object comprises:

[0026] The different color temperatures of the measured object are estimated by the multi-channel surface brightness information.

[0027] The color temperature correction parameter is calculated by simulating the multi-channel frequency response curve of the camera and the single-channel frequency response curve of the night sky quality meter at different color temperatures.

[0028] Optionally, the logarithmic conversion according to the color temperature correction parameter to obtain the surface brightness data of the measured object comprises:

[0029] converting the dark sky unit linearly related to the surface brightness into a sky brightness in units of star magnitude per square angular second related to the logarithm of the surface brightness;

[0030] determining the surface brightness data according to the sky brightness.

[0031] The present application further provides a multi-pixel photometric device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the multi-pixel photometric method according to any one of the above.

[0032] The present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a multi-pixel photometric program, and the multi-pixel photometric program, when executed by a processor, implements the steps of the multi-pixel photometric method according to any one of the above.

[0033] The multi-pixel photometric method, device and computer readable storage medium of the present application are implemented by acquiring exposure parameters and original data of an image; performing linear calculation on the original data according to distortion parameters, vignetting parameters, flow parameters of a camera and the exposure parameters to obtain multi-channel brightness information; performing multi-band color calibration through the multi-channel brightness information and calculating to obtain a color temperature correction parameter of a measured object; and performing logarithmic conversion according to the color temperature correction parameter to obtain surface brightness data of the measured object. The present application implements a camera-based multi-pixel photometric scheme, utilizes a camera to complete standard photometric measurement of each pixel, and converts readings of a camera sensor into surface brightness with physical meaning. BRIEF DESCRIPTION OF DRAWINGS

[0034] The present application will be further described below in conjunction with the accompanying drawings and embodiments, wherein:

[0035] Figure 1 is a hardware structure schematic diagram of a mobile terminal involved in the present application;

[0036] Figure 2 is a first flowchart of the multi-pixel photometric method of the present application;

[0037] Figure 3 is a second flowchart of the multi-pixel photometric method of the present application;

[0038] Figure 4 is a third flowchart of the multi-pixel photometric method of the present application;

[0039] Figure 5 is a fourth flowchart of the multi-pixel photometric measurement method of the present application;

[0040] Figure 6 is a fifth flowchart of the multi-pixel photometric measurement method of the present application;

[0041] Figure 7 is a sixth flowchart of the multi-pixel photometric measurement method of the present application;

[0042] Figure 8 is a seventh flowchart of the multi-pixel photometric measurement method of the present application;

[0043] Figure 9 is an eighth flowchart of the multi-pixel photometric measurement method of the present application;

[0044] Figure 10 is a flowchart of the actual measurement of the multi-pixel photometric measurement method of the present application. DETAILED DESCRIPTION

[0045] It should be understood that the specific embodiments described herein are merely illustrative of the present application and do not limit the present application.

[0046] In the following description, the suffixes used for elements, such as "module", "part", or "unit", are used only for convenience of explanation of the present application, and have no specific meaning by themselves. Thus, "module", "part", or "unit" can be mixedly used.

[0047] A terminal can be implemented in various forms. For example, the terminal described in the present application can include a mobile terminal such as a mobile phone, a tablet, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, etc., and a stationary terminal such as a digital TV, a desktop computer, etc.

[0048] In the following description, a mobile terminal will be exemplified, and those skilled in the art will understand that the configuration according to the embodiments of the present application can be applied to a stationary type terminal, except for elements particularly used for mobile purposes.

[0049] Referring to Figure 1Fig. 1 is a diagram illustrating a hardware structure of a mobile terminal according to an embodiment of the present application. The mobile terminal 100 can include a RF (Radio Frequency) unit 101, a WiFi module 102, an audio output unit 103, an A / V (audio / video) input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, a processor 110, and a power supply 111, etc. Those skilled in the art will understand that the mobile terminal structure illustrated in Fig. 1 is not intended to limit the scope of the present application, and the mobile terminal can include more or less components, or some components can be combined, or different components can be arranged. Figure 1 The mobile terminal structure illustrated in Fig. 1 is not intended to limit the scope of the present application, and the mobile terminal can include more or less components, or some components can be combined, or different components can be arranged.

[0050] The following detailed description will be made with reference to the accompanying drawings. Figure 1 The components of the mobile terminal will be described in detail.

[0051] The RF unit 101 can be used for receiving and transmitting signals in the process of receiving or transmitting information or a call. Specifically, the RF unit 101 receives downlink signals from a base station, and transmits uplink signals to the base station. The RF unit 101 can include, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the RF unit 101 can communicate with the network and other devices through wireless communication. The wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communication), GPRS (General Packet Radio Service), CDMA2000 (Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division Duplexing-Long Term Evolution), TDD-LTE (Time Division Duplexing-Long Term Evolution), etc.

[0052] The WiFi belongs to a short-range wireless transmission technology, and the mobile terminal can help the user to send and receive e-mails, browse web pages, and access streaming media, etc. through the WiFi module 102, which provides the user with wireless broadband Internet access. Although Figure 1 The WiFi module 102 is shown, but it is understood that it does not belong to the necessary components of the mobile terminal, and can be omitted as needed without changing the essence of the application.

[0053] The audio output unit 103 can convert audio data, which is received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109, into an audio signal and output it as sound when the mobile terminal 100 is in a call signal reception mode, a call mode, a recording mode, a voice recognition mode, a broadcast reception mode, and the like. Moreover, the audio output unit 103 can provide audio output related to a particular function (e.g., call signal reception sound, message reception sound, etc.) performed by the mobile terminal 100. The audio output unit 103 can include a speaker, a buzzer, and the like.

[0054] The A / V input unit 104 is used to receive audio or video signals. The A / V input unit 104 can include a graphics processor (GPU) 1041 and a microphone 1042, the graphics processor 1041 processes image data of a still picture or a video obtained by an image capture device (e.g., a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 106. The image frame processed by the graphics processor 1041 can be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 can receive sound (audio data) via the microphone 1042 in a telephone call mode, a recording mode, a voice recognition mode, and the like, and can process such sound into audio data. The processed audio (voice) data can be converted into a format transmittable to a mobile communication base station in a telephone call mode and outputted. The microphone 1042 can implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the process of receiving and transmitting audio signals.

[0055] The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 1061 according to the brightness of ambient light, and the proximity sensor can turn off the display panel 1061 and / or the backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and when at rest, can detect the magnitude and direction of gravity, and can be used for applications such as identifying the posture of the mobile phone (such as switching between horizontal and vertical screens, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometers, tapping), and the like. As for the fingerprint sensor, pressure sensor, iris sensor, molecular sensor, gyroscope, barometer, hygrometer, thermometer, infrared sensor and other sensors that can be configured on the mobile phone, they will not be described here.

[0056] The display unit 106 is configured to display information input by a user or information provided to the user. The display unit 106 can include a display panel 1061, which can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0057] The user input unit 107 can be configured to receive input digital or character information, and to generate key signal inputs related to user settings and function controls of the mobile terminal. Specifically, the user input unit 107 can include a touch panel 1071 and other input devices 1072. The touch panel 1071, also known as a touch screen, can collect a user's touch operation (such as the user's operation on or near the touch panel 1071 using a finger, a stylus, or any suitable object or accessory) and drive the corresponding connection device according to the pre-set program. The touch panel 1071 can include two parts, a touch detection device and a touch controller. The touch detection device detects the user's touch position and detects the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into touch coordinates, and sends it to the processor 110, and can also receive commands from the processor 110 and execute them. In addition, the touch panel 1071 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 can also include other input devices 1072. Specifically, the other input devices 1072 can include one or more of a physical keyboard, function keys (such as volume control buttons, on / off buttons, etc.), trackballs, mice, joysticks, and the like, without limitation.

[0058] Further, the touch panel 1071 can cover the display panel 1061, and when the touch panel 1071 detects a touch operation thereon or thereabout, transmit the same to the processor 110 to determine the type of the touch event, and then the processor 110 provides a corresponding visual output on the display panel 1061 according to the type of the touch event. Although in the above description, the touch panel 1071 and the display panel 1061 are implemented as two independent components to realize the input and output functions of the mobile terminal, in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated to realize the input and output functions of the mobile terminal, which is not limited herein. Figure 1

[0059] The interface unit 108 serves as an interface through which at least one external device can be connected with the mobile terminal 100. For example, the external device can include a wired or wireless headset port, an external power (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input / output (I / O) port, a video I / O port, an earphone port, and / or the like. The interface unit 108 can be used as a path for the input of external input data (e.g., data received by the identification module) to at least one element of the mobile terminal 100 and for the delivery of user command requests made by the user to at least one element of the mobile terminal 100. The interface unit 108 can further be used as a path through which data is delivered to or through the mobile terminal 100.

[0060] The memory 109 is generally used to store software programs and various data. The memory 109 can include a program region and a data region, wherein the program region can store an operating system, at least one application program (e.g., a sound play function, a picture play function, and / or the like) required for at least one function, and / or the like, and the data region can store data (e.g., audio data, a phonebook, and / or the like) created based on the use of the mobile terminal. In addition, the memory 109 can include a high-speed random access memory, and can further include a non-volatile memory such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid state storage device.

[0061] The processor 110 is a control center of the mobile terminal, which connects each part of the mobile terminal with various interfaces and lines, and performs various functions and processes data of the mobile terminal by running or executing software programs and / or modules stored in the memory 109 and by calling data stored in the memory 109, thereby monitoring the overall mobile terminal. The processor 110 can include one or more processing units; preferably, the processor 110 can integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and an application program, and the modem processor mainly processes wireless communication. It can be understood that the above-described modem processor can also not be integrated into the processor 110.

[0062] ​The mobile terminal 100 can further include a power supply 111 (such as a battery) for powering the various components of the mobile terminal 100. In addition, the power supply 111 can be preferably logically connected to the processor 110 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption management, etc.

[0063] Although Figure 1 The mobile terminal 100 can further include a Bluetooth module, etc., which are not shown here.

[0064] Based on the above mobile terminal hardware structure, various embodiments of the method of the present application are proposed.

[0065] Figure 2 is the first flowchart of the multi-pixel photometric measurement method of the present application. The embodiment proposes a multi-pixel photometric measurement method, which includes:

[0066] S1, obtaining the exposure parameters and the original data of the image;

[0067] S2, performing linear calculation on the original data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera, and the exposure parameters, to obtain multi-channel luminance information;

[0068] S3, performing multi-band color calibration through the multi-channel luminance information, and calculating to obtain the color temperature correction parameters of the measured object;

[0069] S4, performing logarithmic conversion according to the color temperature correction parameters to obtain the surface luminance data of the measured object.

[0070] In the embodiment, please refer to Figure 10 the actual measurement flowchart shown. First, the image processing unit obtains the exposure parameters and the original data of the input image; then, the linear calculation unit performs linear calculation on the original data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera, and the exposure parameters, to obtain multi-channel luminance information; then, the multi-band calibration unit performs multi-band color calibration through the multi-channel luminance information, and calculates to obtain the color temperature correction parameters of the measured object; finally, the color temperature correction parameters are used for logarithmic conversion to obtain the surface luminance data of the measured object.

[0071] Optionally, in the embodiment, the camera sensor readings are converted into dark sky units according to the distortion parameters, the vignetting parameters, and the flow parameters of the camera.

[0072] Optionally, in the embodiment, the dark sky units are converted into sky brightness related to the logarithm of surface luminance, in units of magnitude per square arcsecond.

[0073] In the embodiment, the lens camera calibration scheme can be arranged in any electronic device and can be used for parameter calibration of camera systems of various lens cameras.

[0074] The embodiment has the beneficial effect that the exposure parameters and the original data of an image are acquired, the original data are linearly calculated according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters, multi-channel luminance information is obtained, multi-band color calibration is performed through the multi-channel luminance information, the color temperature correction parameters of the measured object are calculated, the color temperature correction parameters are logarithmically converted, and the surface luminance data of the measured object are obtained. The embodiment realizes a multi-pixel photometric measurement scheme based on a camera, standard photometric measurement of each pixel is completed by using the camera, and readings of the camera sensor are converted into surface luminance with physical meaning.

[0075] Figure 3 The second flowchart of the multi-pixel photometric measurement method is based on the above embodiment, and the exposure parameters and the original data of an image are acquired, including:

[0076] S11, the exposure parameters are acquired, wherein the exposure parameters include an exposure time, an aperture value, a sensitivity value, a black level value and a white balance value;

[0077] S12, the original data of the image are acquired through a LibRaw algorithm library.

[0078] Figure 4 The third flowchart of the multi-pixel photometric measurement method is based on the above embodiment, and the original data are linearly calculated according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters, and multi-channel luminance information is obtained, and the previous process includes:

[0079] S01, imaging of a plane perpendicular to a lens optical axis and composed of equal-interval grid points is taken as a first image, and a distortion curve of a lens and an off-axis angle of the lens optical axis relative to a lens central axis are calculated according to the first image;

[0080] S02, the distortion parameters are determined according to the distortion curve and the off-axis angle.

[0081] Optionally, in this embodiment, firstly, the first image input by the distortion processing unit is a plane perpendicular to the optical axis composed of equidistant grid points; then, the position of the grid plane in three-dimensional space is determined according to the reference plane of the camera; then, the relationship between the position of the grid point on the image plane and the incident angle is calculated, and the fitting of the third-order polynomial of the result is taken as the distortion curve of the lens; at the same time, the deviation of the optical axis of the lens from the lens central axis is obtained by using the above steps; finally, it is specifically manifested that the optical center is not located at the center position of the focal plane, and the above distortion curve and the axis deviation angle jointly constitute the distortion parameters of this step.

[0082] Figure 5 is a fourth flowchart of the multi-pixel photometric measurement method of the present application, based on the above embodiment, the linear calculation of the original data according to the distortion parameters, vignetting parameters, flow parameters and exposure parameters of the camera to obtain multi-channel luminance information, further includes:

[0083] S03, imaging the plane with known surface brightness as a second image;

[0084] S04, determining the vignetting parameters according to the surface brightness of the second image and the known surface brightness of the wallpaper.

[0085] Optionally, in this embodiment, the second image input by the vignetting processing unit is a plane with known surface brightness. Taking the night sky as an example, the same piece of sky is photographed at the same time using the camera C1 to be calibrated and the camera C2 whose vignetting has been calibrated; the surface brightness ratio (C1 / C2) measured by the two is the vignetting effect diagram of the camera to be calibrated. Optionally, in actual operation, the method of continuous multiple shooting can be used to improve the sampling of different positions, thereby improving the smoothness of the obtained vignetting parameters.

[0086] Figure 6 is a fifth flowchart of the multi-pixel photometric measurement method of the present application, based on the above embodiment, the linear calculation of the original data according to the distortion parameters, vignetting parameters, flow parameters and exposure parameters of the camera to obtain multi-channel luminance information, further includes:

[0087] S05, determining the corresponding position of the sky area observed by the night sky quality instrument on the lens focal plane according to the distortion parameters, and correcting the different responses of the corresponding position to the focal plane position according to the vignetting parameters;

[0088] S06, obtaining the night sky surface brightness calculated by the lens in the simulation of the measurement mode of the night sky quality instrument through the integral of the incidence angle luminosity curve of the night sky quality instrument, and comparing the surface brightness variation curve obtained by the night sky quality instrument with the surface brightness variation curve obtained by the lens, to determine the average value of the surface brightness difference as the flow parameter.

[0089] Optionally, in the embodiment, the third image input by the flux calibration unit is a plane light source with a known surface brightness.

[0090] Taking the night sky as an example, the night sky quality meter is used to continuously detect the surface brightness of the sky area within 10 degrees of the zenith. For example, the same piece of the zenith area is photographed by the camera to be calibrated in the same time period. In the embodiment, the distortion parameters obtained by the above steps determine the corresponding position of the sky area observed by the night sky quality meter on the focal plane of the camera to be calibrated. Further, the vignetting parameters obtained by the above steps are used to correct the different responses of the above-mentioned area with the focal plane position. Based on this, the night sky surface brightness calculated by the camera to be calibrated in the simulation mode of the measurement of the night sky quality meter is obtained through the integral of the incident angle luminance curve of the night sky quality meter. Finally, the surface brightness variation curve obtained by the above night sky quality meter and the surface brightness variation curve obtained by the camera to be calibrated are compared, and the average value of the difference between the two surface brightnesses is the flux parameter of the camera to be calibrated.

[0091] Figure 7 The sixth flow chart of the multi-pixel photometric measurement method is based on the above-mentioned embodiment, and the linear calculation of the original data according to the distortion parameters, the vignetting parameters, the flux parameters and the exposure parameters of the camera to obtain multi-channel luminance information, including:

[0092] S21, according to the color filter array, extracting a multi-channel data matrix in the array of the original data;

[0093] S22, converting the unit of the multi-channel data matrix from electronic units to dark sky units;

[0094] S23, calculating the multi-channel data matrix in the dark sky unit according to the white balance information to obtain the multi-channel surface brightness.

[0095] Optionally, in the embodiment, the multi-channel data matrix is extracted in the array of the original data by using the color filter array. Optionally, the Bayer array is used to measure the amount of light of different wave bands by adding different color filters in front of adjacent pixels. Optionally, for the same color mosaic color filter array (usually G green), the average value is used as the data matrix of the channel.

[0096] Optionally, in the embodiment, the unit of the multi-channel data matrix is converted from electronic units to dark sky units. The specific conversion formula is as follows:

[0097]

[0098] DN(k,j) is the electronic reading of the (k,j) pixel, DN black , DNsatu are the electronic readings of the dark level and the white level respectively, vign(k,j) is the vignetting parameter of the (k,j) pixel calculated by the above steps, dsu x is the flow parameter of the x waveband calculated by the above steps. Alternatively, in this embodiment, only the green channel is flow calibrated due to the response and quantum efficiency of different channels.

[0099] Figure 8 is the seventh flow chart of the multi-pixel photometric measurement method of the present application, based on the above embodiment, the multi-waveband color calibration by the multi-channel luminance information and the calculation of the color temperature correction parameter of the measured object, comprising:

[0100] S31, estimating the different color temperatures of the measured object by the multi-channel surface luminance information;

[0101] S32, calculating the color temperature correction parameter by simulating the camera multi-channel frequency response curve and the night sky quality instrument single-channel frequency response curve at different color temperatures.

[0102] Alternatively, in this embodiment, considering that different measured objects have different spectra, their energy spectrum distribution may be different from that of the night sky, which may cause the final obtained luminance measurement value to have a zero point deviation. Based on this, in this embodiment, by using the multi-channel luminance information, the approximate color temperature of the measured object is estimated, and by simulating the camera multi-channel frequency response curve and the night sky quality instrument single-channel frequency response curve at different color temperatures, the corresponding color temperature correction parameter is calculated, wherein the color temperature correction parameter for the night sky is zero.

[0103] Figure 9 is the eighth flow chart of the multi-pixel photometric measurement method of the present application, based on the above embodiment, the logarithmic conversion according to the color temperature correction parameter to obtain the surface luminance data of the measured object, comprising:

[0104] S41, converting the dark sky unit linearly related to the surface luminance into the sky brightness in units of star magnitude per square angular second related to the logarithm of the surface luminance;

[0105] S42, determining the surface luminance data according to the sky brightness.

[0106] In the embodiment, the dark sky unit linearly related to the surface brightness is converted into the sky brightness in units of star magnitude per square angular second related to the logarithm of the surface brightness, and a calibration and correction scheme for any sensor and lens is constructed by combining the above implementation steps. Further, in the embodiment, a multi-pixel brightness measurement scheme is proposed based on a smart phone, and each pixel of the sensor can be converted into a surface brightness measurement device calibrated by a scientific institution by using the scheme, so that the measurement of the two-dimensional surface brightness of any object can be realized.

[0107] Based on the above embodiment, the application further proposes a multi-pixel photometric measurement device, which comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program realizes the steps of the multi-pixel photometric measurement method according to any one of the above embodiments when executed by the processor.

[0108] It should be noted that the above device embodiment and the method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, and the technical features in the method embodiment are all applicable to the device embodiment, which will not be repeated here.

[0109] Based on the above embodiment, the application further proposes a computer readable storage medium, which stores a multi-pixel photometric measurement program, and the multi-pixel photometric measurement program realizes the steps of the multi-pixel photometric measurement method according to any one of the above embodiments when executed by a processor.

[0110] It should be noted that the above medium embodiment and the method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, and the technical features in the method embodiment are all applicable to the medium embodiment, which will not be repeated here.

[0111] It should be noted that in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0112] The above embodiment numbers of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0113] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, also can be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application essentially or say the part which contributes to the prior art can be embodied in the form of software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a plurality of instructions to make a terminal (may be a mobile phone, computer, server, air conditioner, or network equipment, etc.) execute the method described in various embodiments of the present application.

[0114] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative, not limiting, and those skilled in the art can make many forms under the inspiration of the present application without departing from the scope of the present application and the scope protected by the claims.

Claims

1. A multi-pixel photometric measurement method, characterized by, The method comprises: obtaining exposure parameters and raw data of an image; performing linear calculation on the raw data according to distortion parameters, vignetting parameters, flow parameters of a camera and the exposure parameters to obtain multi-channel luminance information; performing multi-band color calibration through the multi-channel luminance information and calculating to obtain color temperature correction parameters of a measured object; performing logarithmic conversion according to the color temperature correction parameters to obtain surface luminance data of the measured object. The linear calculation on the raw data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters to obtain the multi-channel luminance information comprises: extracting a multi-channel data matrix in an array of the raw data according to a color filter array; converting units of the multi-channel data matrix from electronic units to dark sky units; calculating the multi-channel data matrix in the dark sky units according to white balance information to obtain multi-channel surface luminance; The multi-band color calibration through the multi-channel luminance information and the calculation to obtain the color temperature correction parameters of the measured object comprises: estimating different color temperatures of the measured object through the multi-channel surface luminance information; calculating the color temperature correction parameters through simulation of a camera multi-channel frequency response curve and a night sky quality meter single-channel frequency response curve under the different color temperatures; The logarithmic conversion according to the color temperature correction parameters to obtain the surface luminance data of the measured object comprises: converting the dark sky units linearly related to surface luminance into sky brightness in units of star magnitude per square arc second related to logarithm of surface luminance; determining the surface luminance data according to the sky brightness.

2. The method of multi-element photometric measurement according to claim 1, characterized in that, The obtaining of the exposure parameters and the raw data of the image comprises: obtaining the exposure parameters, wherein the exposure parameters comprise exposure time, aperture value, sensitivity value, black level value and white balance value; obtaining the raw data of the image through a LibRaw algorithm library.

3. The method of multi-element photometric measurement according to claim 1, wherein, The linear calculation on the raw data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters to obtain the multi-channel luminance information further comprises: taking imaging of a plane perpendicular to a lens optical axis composed of equally spaced grid points as a first image and calculating a distortion curve of the lens and an off-axis angle of the lens optical axis relative to a lens central axis according to the first image; determining the distortion parameters according to the distortion curve and the off-axis angle.

4. The method of multi-element photometric measurement according to claim 3, characterized in that, The linear calculation on the raw data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters to obtain the multi-channel luminance information further comprises: taking imaging of a plane with known surface luminance as a second image; determining the vignetting parameters according to a bright surface degree of the second image and a wallpaper of the known surface luminance.

5. The method of multi-element photometric measurement according to claim 4, characterized in that, The linear calculation on the raw data according to the distortion parameters, the vignetting parameters, the flow parameters of the camera and the exposure parameters to obtain the multi-channel luminance information further comprises: determining a corresponding position of a sky region observed by a night sky quality meter on a focal plane of the lens according to the distortion parameters and correcting different responses of the corresponding position to the focal plane position according to the vignetting parameters. The night sky brightness calculated by the lens in simulation of the measurement mode of the night sky quality meter is obtained by integration of the incidence angle luminosity curve of the night sky quality meter, and the average value of the difference in surface brightness is determined as the flow parameter by comparing the surface brightness change curve obtained by the night sky quality meter with the surface brightness change curve obtained by the lens.

6. A multi-element photometric measuring device, characterized by The device comprises a memory, a processor and a computer program stored on the memory and executable on the processor, and the computer program, when executed by the processor, implements the steps of the multi-pixel photometry method according to any one of claims 1 to 5.

7. A computer readable storage medium characterized by The computer readable storage medium stores a multi-pixel photometry program, and the multi-pixel photometry program, when executed by a processor, implements the steps of the multi-pixel photometry method according to any one of claims 1 to 5.

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