CN113989394A - Image processing method and system for color temperature of automatic driving simulation environment - Google Patents

Image processing method and system for color temperature of automatic driving simulation environment Download PDF

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CN113989394A
CN113989394A CN202111235691.XA CN202111235691A CN113989394A CN 113989394 A CN113989394 A CN 113989394A CN 202111235691 A CN202111235691 A CN 202111235691A CN 113989394 A CN113989394 A CN 113989394A
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color temperature
image
algorithm
image processing
scene
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刘美江
邓伟文
丁娟
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Zhejiang Tianxingjian Intelligent Technology Co ltd
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Abstract

The invention discloses an image processing method and system for color temperature of an automatic driving simulation environment, and relates to the technical field of automatic driving. The image processing method for the color temperature of the automatic driving simulation environment comprises the following steps: acquiring an initial image and weather information corresponding to a current simulation scene of automatic driving; determining target parameters of an algorithm according to the weather information; and calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene. The invention can make the color temperature of the image provided by the simulation scene consistent with the color temperature of the actual driving scene.

Description

Image processing method and system for color temperature of automatic driving simulation environment
Technical Field
The invention relates to the technical field of automatic driving, in particular to an image processing method and system for color temperature of an automatic driving simulation environment.
Background
With the development of automatic driving technology, a vision-based driver assistance system (VADAS) also gets more and more attention of research and development personnel, the VADAS senses the surrounding environment of a vehicle using a vision sensor, the installation range and the angle of view of the vision sensor are flexible, and the VADAS can be conveniently combined with the vehicle and can obtain more comprehensive sensing information, such as: lane lines, traffic signal indicator lights, other vehicles, pedestrians and the like, and the cost of the visual sensor is low, so the VADAS can obtain richer perception information through low hardware cost, but the VADAS needs to acquire actual scenes around the vehicle in real time, and the sensitivity of the visual sensor cannot meet the requirement generally.
To solve this problem, research and development personnel develop a simulation camera to obtain information around the vehicle through an automatic driving algorithm. However, since the testing of the automatic driving algorithm under a severe environment is costly and the consequences of failure are severe, research and development personnel want to acquire enough data sets through a simulation scenario for training the automatic driving algorithm. In order to improve the reality of the simulation scene, the problem of consistency between the simulation camera and the real camera needs to be solved in the process of acquiring the data set through the simulation scene. Although the original picture provided by the simulated scene obtained through the automatic driving algorithm can be the same as the scene shot by the real camera arranged on the vehicle, the color temperature matched with the actual weather cannot be simulated, namely, the existing simulated scene is not consistent with the scene shot by the real camera arranged on the vehicle.
Therefore, how to make the color temperature of the image provided by the simulation scene consistent with the color temperature of the actual driving scene is a technical problem which needs to be solved urgently by the technicians in the field.
Disclosure of Invention
The invention provides an image processing method and system for color temperature of an automatic driving simulation environment, which can enable the color temperature of an image provided by a simulation scene to be consistent with the color temperature of an actual driving scene.
The invention provides the following scheme:
in a first aspect, the present invention provides an image processing method for color temperature of an automatic driving simulation environment, comprising:
acquiring an initial image and weather information corresponding to a current simulation scene of automatic driving;
determining target parameters of an algorithm according to the weather information;
and calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene.
Optionally, the calculating the initial image by using the algorithm for selecting the target parameter, and acquiring the simulated image corresponding to the current simulation scene includes:
acquiring all pixel points of the initial image and an initial RGB value corresponding to each pixel point;
calculating the initial RGB value corresponding to each pixel point by utilizing an algorithm for selecting the target parameters to obtain a target RGB value corresponding to each pixel point;
and generating the simulation image according to the target RGB values corresponding to all the pixel points.
Optionally, the algorithm includes a color temperature conversion polynomial, and the calculating the initial RGB value corresponding to each pixel point by using the algorithm for selecting the target parameter to obtain the target RGB value corresponding to each pixel point includes:
and inputting the initial RGB value into the color temperature conversion polynomial adopting the target parameter to calculate the target RGB value.
Optionally, the color temperature conversion polynomial comprises a third order conversion polynomial.
Optionally, the determining target parameters of the algorithm according to the weather information includes:
obtaining color temperature information corresponding to the current scene according to the weather information;
and the target parameter is obtained according to the color temperature information.
Optionally, the weather information includes: at least one of sunny, cloudy, foggy, snowy, and rainy.
Optionally, the current simulation scenario is provided by a scenario library generated based on a UNITY 3D engine.
In a second aspect, the present invention provides an image processing system for automatically driving a simulated ambient color temperature, comprising:
the acquisition module is used for acquiring an initial image and weather information corresponding to the current simulation scene of automatic driving;
the analysis module is connected with the acquisition module and used for determining target parameters of the algorithm according to the weather information;
and the execution module is connected with the analysis module and used for calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene.
In a third aspect, the present invention provides a computer device comprising a memory and a processor, the memory having stored thereon a computer program executable on the processor, the computer program, when executed by the processor, implementing the image processing method for color temperature of an autopilot simulation environment.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed, implements the image processing method for automatically driving a simulated ambient color temperature.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the image processing method for the color temperature of the automatic driving simulation environment determines the target parameters of the algorithm through the weather information provided by the current simulation scene, and then adjusts the color of the initial image according to the algorithm for selecting the target parameters, so that the color temperature of the image provided by the simulation scene is consistent with the color temperature of the actual driving scene.
Furthermore, when the color temperature of the initial image is adjusted, each pixel point and the corresponding initial RGB value of the pixel point transmitted by the current simulation scene are traversed, the initial RGB value is converted into a target RGB value according to an algorithm, and then all the pixel points are adjusted according to the target RGB value. Because the pixel points are the minimum units for forming the initial image, the finally obtained simulated image can be matched with the weather information to the maximum extent by adjusting the color of the pixel points, so that the simulated scene is closer to the actual scene.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a block flow diagram of an image processing method for automatically driving a simulated ambient color temperature according to an embodiment of the present invention;
FIG. 2 is a block flow diagram of an image processing method for automatically driving a simulated ambient color temperature according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of a lamp box calibrated by a color temperature conversion polynomial according to an embodiment of the present invention;
FIG. 4 is a graph of red fit results provided by one embodiment of the present invention;
FIG. 5 is a graph of green fitting results provided by one embodiment of the present invention;
FIG. 6 is a graph of blue fitting results provided by one embodiment of the present invention;
FIG. 7 is a block diagram of an image processing system for automatically driving a simulated ambient color temperature according to an embodiment of the present invention;
fig. 8 is an architecture diagram of a computer device, as provided by one embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
The following describes a specific implementation scheme provided by the embodiment of the present invention in detail.
The invention provides an image processing method and system for automatically driving a simulation environment color temperature, which adjust the color of an initial image provided by a simulation scene to be matched with the real-time weather color temperature according to a color temperature conversion polynomial, simulate the environment color temperature and enable the simulation scene to be adaptive to the current actual scene of automatic driving.
Example one
Fig. 1 is a block flow diagram of an image processing method for automatically driving a simulated ambient color temperature according to an embodiment of the present invention. As shown in fig. 1, the present embodiment provides an image processing method for color temperature of an automatic driving simulation environment, which generally includes the following steps:
s10: acquiring an initial image and weather information corresponding to a current simulation scene of automatic driving;
s20: determining target parameters of an algorithm according to the weather information;
s30: and calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene.
The initial image usually includes an image stream, the current simulation scene has a weather transformation function, and image signals of different weather can be output according to actual weather, that is, weather information is the same as the actual weather information.
In the embodiment, the target parameter of the algorithm is determined through the weather information provided by the current simulation scene, the target parameter is matched with the weather information, and then the color of the initial image is adjusted by adopting the algorithm for selecting the target parameter, so that the color temperature of the image provided by the simulation scene is consistent with the color temperature of the actual driving scene.
Fig. 2 is a block flow diagram of an image processing method for automatically driving a simulated ambient color temperature according to another embodiment of the present invention. As shown in fig. 2, S30 includes:
s31: acquiring all pixel points of the initial image and an initial RGB value corresponding to each pixel point;
s32: calculating the initial RGB value corresponding to each pixel point by utilizing an algorithm for selecting the target parameters to obtain a target RGB value corresponding to each pixel point;
s33: and generating the simulation image according to the target RGB values corresponding to all the pixel points.
Wherein the color temperature information includes a color temperature value. Preferably, the weather information can be converted into the color temperature value according to general experience.
In this embodiment, when the color temperature of the initial image is adjusted, each pixel point and the corresponding initial RGB value thereof introduced into the current simulation scene are traversed, the initial RGB value is converted into the target RGB value according to the algorithm, and then all the pixel points are adjusted according to the target RGB value. Because the pixel points are the minimum units for forming the initial image, the finally obtained simulated image can be matched with the weather information to the maximum extent by adjusting the color of the pixel points, so that the simulated scene is closer to the actual scene.
Specifically, the algorithm includes a color temperature conversion polynomial, and the calculating the initial RGB values corresponding to each pixel point by using the algorithm for selecting the target parameter to obtain the target RGB values corresponding to each pixel point includes:
and inputting the initial RGB value into the color temperature conversion polynomial adopting the target parameter to calculate the target RGB value.
Specifically, S20 includes:
obtaining color temperature information corresponding to the current scene according to the weather information;
and determining the target parameters of the algorithm according to the color temperature information.
Because the color temperatures of images presented in different weathers are different, the actual weather information can be simulated by selecting the target parameters based on the color temperature information and utilizing an algorithm for selecting the target parameters to adjust the initial images to obtain the simulated images.
Specifically, the color temperature conversion polynomial is obtained by calibrating a simulation camera.
More specifically, the color temperature conversion polynomial includes a third order polynomial, which can secure a simulation rate and avoid overfitting. Fig. 3 is a schematic structural diagram of a lamp box calibrated by a color temperature conversion polynomial according to an embodiment of the present invention. The calibration process of the color temperature conversion polynomial comprises the following steps:
1. putting the color card 300 into the color temperature adjustable lamp box 100, wherein the color card is a ColorSpace standard 24 color card, the color temperature adjustable lamp box 100 selects ColorSpace CS-LE006, and the color light lamp 110 is arranged in the lamp box 100;
2. adjusting the color temperature in the lamp box according to the color temperature value corresponding to the weather, wherein the adjustment range of the color temperature is 2800K-10000K;
3. after the adjustment, shooting a color card by using a simulation camera 200 to obtain a color card image, wherein the simulation camera 200 is a BASLER industrial camera;
4. sampling each area of the color card image in a square frame, counting the RGB value with the highest frequency of occurrence of each area in the color card image as the characteristic RGB value of the area, and obtaining 24 groups of RGB values for each picture to obtain the following data:
Figure BDA0003317424280000071
wherein [ R ]n，Gn，Bn]Representing the characteristic RGB values of the nth region.
5. Obtaining initial RGB values of each region of the color card image, extracting three groups of data pairs by channels, obtaining the corresponding relation of the RGB values of each channel, and fitting to obtain:
R＝i0+ilR0+i2R0 2+i3R0 3+…
G＝j0+j1G0+j2G0 2+j3G0 3+…
B＝k0+k1B0+k2B0 2+k3B0 3+…
wherein [ R ]0，G0，B0]An initial RGB value representing a certain area, [ R,G，B]and representing the target RGB value of a certain region at the current color temperature, wherein i, j and k are coefficients of each order of the polynomial respectively.
Fig. 4 is a graph of red fitting results provided by one embodiment of the present invention. FIG. 5 is a graph of green fitting results provided by one embodiment of the present invention. FIG. 6 is a graph of blue fitting results provided by one embodiment of the present invention. In one embodiment, taking a snow scene as an example, the color temperature value is assumed to be 8000K, and the results obtained by fitting the color temperature conversion polynomial are shown in fig. 4-6.
After the calibration, the target parameters i, j and k at various color temperatures can be obtained.
Since the initial RGB values are known and the target parameters i, j, and k in the color temperature conversion polynomial may be determined according to color temperature information, inputting the initial RGB values into the color temperature conversion polynomial may result in the target RGB values.
Furthermore, the color temperature conversion polynomial corresponding to the color temperature information is determined after the color temperature conversion polynomial is calibrated in advance, and target parameters i, j and k are known, so that the corresponding color temperature conversion polynomial can be immediately determined through the color temperature information, the operation speed is high, the target RGB value can be quickly obtained, and a simulation scene similar to an actual scene can be simulated.
Preferably, the weather information includes: at least one of sunny, cloudy, foggy, snowy, and rainy. Empirically, in some embodiments, the color temperature value is 5500K for a sunny day, 6500K for a cloudy day, 8500K for a foggy day, and 8000K for snow and rain. Of course, it can be understood by those skilled in the art that the above color temperature values are only exemplary, and in actual operation, the color temperature values can be calibrated according to actual weather.
Specifically, the current simulation scenario is provided by a scenario library generated based on a UNITY 3D engine.
Example two
Fig. 7 is a block diagram of an image processing system for automatically driving a simulated ambient color temperature according to an embodiment of the present invention. As shown in fig. 7, the second embodiment provides an image processing system for color temperature of an automatic driving simulation environment, which generally includes an acquisition module 10, an analysis module 20 and an execution module 30. The acquisition module 10 is used for acquiring an initial image and weather information corresponding to a current simulation scene of automatic driving. The analysis module 20 is connected to the collection module 10, and is configured to determine target parameters of an algorithm according to the weather information. The execution module 30 is connected to the analysis module 20, and is configured to calculate the initial image by using an algorithm for selecting the target parameter, and obtain a simulated image corresponding to the current simulation scene.
Because the color temperatures of images presented in different weathers are different, the actual weather information can be simulated by adjusting the color temperature of the images. Therefore, in the embodiment, the target parameter corresponding to the algorithm of the weather information is selected according to the weather information provided by the current simulation scene, and the color of the initial image is adjusted by using the algorithm for selecting the target parameter, so that the color temperature of the image provided by the simulation scene is consistent with the color temperature of the actual driving scene.
A second embodiment is not detailed, and reference may be made to the first embodiment.
EXAMPLE III
Corresponding to the method, the invention also provides computer equipment, which comprises:
the image processing method for the color temperature of the automatic driving simulation environment provided by the embodiment is implemented by the processor and the memory, wherein the memory is stored with a computer program which can run on the processor, and the computer program is executed by the processor.
Fig. 8 illustrates, among other things, a computer device that may include, among other things, a processor 1510, a video display adapter 1511, a disk drive 1512, an input/output interface 1513, a network interface 1514, and a memory 1520. The processor 1510, video display adapter 1511, disk drive 1512, input/output interface 1513, network interface 1514, and memory 1520 may be communicatively coupled via a communication bus 1530.
The processor 1510 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solution provided by the present invention.
The Memory 1520 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, or the like. The memory 1520 may store an operating system 1521 for controlling the operation of the electronic device, a Basic Input Output System (BIOS) for controlling low-level operations of the electronic device. In addition, a web browser 1523, a data storage management system 1524, a device identification information processing system 1525, and the like can also be stored. The device identification information processing system 1525 may be an application program that implements the operations of the foregoing steps in the embodiment of the present invention. In summary, when the technical solution provided by the present invention is implemented by software or firmware, the relevant program codes are stored in the memory 1520 and called for execution by the processor 1510.
The input/output interface 1513 is used for connecting an input/output module to realize information input and output. The i/o module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.
The network interface 1514 is used to connect a communication module (not shown) to enable the device to communicatively interact with other devices. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, Bluetooth and the like).
The bus includes a path that transfers information between the various components of the device, such as the processor 1510, the video display adapter 1511, the disk drive 1512, the input/output interface 1513, the network interface 1514, and the memory 1520.
In addition, the electronic device may further obtain information of specific pickup conditions from the virtual resource object pickup condition information database for performing condition judgment, and the like.
It should be noted that although the above devices only show the processor 1510, the video display adapter 1511, the disk drive 1512, the input/output interface 1513, the network interface 1514, the memory 1520, the bus, etc., in the specific implementation, the devices may also include other components necessary for normal operation. Furthermore, it will be understood by those skilled in the art that the apparatus described above may also include only the components necessary to implement the inventive arrangements, and need not include all of the components shown in the figures.
Example four
The invention also provides a computer readable storage medium, in which a computer program is stored, and when the computer program is executed, the image processing method for automatically driving the simulated environmental color temperature provided by the above embodiment is realized.
From the above description of the embodiments, it is clear to those skilled in the art that the present invention can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The technical solutions provided by the present invention are described in detail above, and the principles and embodiments of the present invention are explained herein by using specific examples, which are merely used to help understanding the method and the core ideas of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. An image processing method for automatically driving a simulated ambient color temperature, comprising:
acquiring an initial image and weather information corresponding to a current simulation scene of automatic driving;
determining target parameters of an algorithm according to the weather information;
and calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene.
2. The image processing method according to claim 1, wherein the calculating the initial image by using the algorithm for selecting the target parameter to obtain the simulated image corresponding to the current simulation scene comprises:
acquiring all pixel points of the initial image and an initial RGB value corresponding to each pixel point;
calculating the initial RGB value corresponding to each pixel point by utilizing an algorithm for selecting the target parameters to obtain a target RGB value corresponding to each pixel point;
and generating the simulation image according to the target RGB values corresponding to all the pixel points.
3. The method of claim 2, wherein the algorithm comprises a color temperature conversion polynomial, and the calculating the initial RGB value corresponding to each pixel point by the algorithm selecting the target parameter to obtain the target RGB value corresponding to each pixel point comprises:
and inputting the initial RGB value into the color temperature conversion polynomial adopting the target parameter to calculate the target RGB value.
4. The image processing method of claim 3, wherein the color temperature conversion polynomial comprises a third order conversion polynomial.
5. The image processing method of claim 1, wherein the determining target parameters of an algorithm from the weather information comprises:
obtaining color temperature information corresponding to the current scene according to the weather information;
and determining the target parameter according to the color temperature information.
6. The image processing method according to claim 1, wherein the weather information includes: at least one of sunny, cloudy, foggy, snowy, and rainy.
7. The method of image processing according to claim 1, wherein the current simulated scene is provided by a scene library generated based on a UNITY 3D engine.
8. An image processing system for automatically driving a simulated ambient color temperature, comprising:
the acquisition module is used for acquiring an initial image and weather information corresponding to the current simulation scene of automatic driving;
the analysis module is connected with the acquisition module and used for determining target parameters of the algorithm according to the weather information;
and the execution module is connected with the analysis module and used for calculating the initial image by adopting an algorithm for selecting the target parameters to obtain a simulated image corresponding to the current simulation scene.
9. A computer arrangement comprising a memory and a processor, the memory having stored thereon a computer program operable on the processor, the computer program, when executed by the processor, implementing the image processing method for automated driving simulation of ambient color temperature of any of claims 1-7.
10. A computer-readable storage medium, in which a computer program is stored, which, when executed, implements the image processing method for automated driving simulation of ambient color temperature according to any one of claims 1 to 7.
CN202111235691.XA 2021-10-22 2021-10-22 Image processing method and system for color temperature of automatic driving simulation environment Pending CN113989394A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115460391A (en) * 2022-09-13 2022-12-09 浙江大华技术股份有限公司 Image simulation method, image simulation device, storage medium and electronic device
WO2023207137A1 (en) * 2022-04-28 2023-11-02 华为技术有限公司 Image processing method and device

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023207137A1 (en) * 2022-04-28 2023-11-02 华为技术有限公司 Image processing method and device
CN115460391A (en) * 2022-09-13 2022-12-09 浙江大华技术股份有限公司 Image simulation method, image simulation device, storage medium and electronic device
CN115460391B (en) * 2022-09-13 2024-04-16 浙江大华技术股份有限公司 Image simulation method and device, storage medium and electronic device

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