CN116109526A - Display picture enhancement method and system based on vehicle rearview mirror - Google Patents
Display picture enhancement method and system based on vehicle rearview mirror Download PDFInfo
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Abstract
The invention relates to the technical field of rearview mirror image enhancement, and discloses a display image enhancement method based on a vehicle rearview mirror, which comprises the following steps: detecting a rearview mirror image in a vehicle rearview mirror in real time, performing image digitization on the rearview mirror image to obtain a digitized image, performing image binarization on an encoded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image, extracting contour parameters of the contour to be fitted, performing filtering on a compensation image to obtain a filtering image, extracting a solid image in the filtering image, and performing linear transformation on the solid image to obtain a linear image; constructing a histogram of the linear image, and detecting the current environment of the rearview mirror of the vehicle in real time; and calculating the mirror surface ambiguity of the vehicle rearview mirror, and dispatching a mirror surface cleaning instruction of the vehicle rearview mirror to execute cleaning treatment on the vehicle rearview mirror so as to obtain the target rearview mirror. The invention aims to improve the display screen enhancement effect based on a vehicle rearview mirror.
Description
Technical Field
The invention relates to the technical field of rearview mirror image enhancement, in particular to a method and a system for enhancing a display image based on a vehicle rearview mirror.
Background
In recent years, automobile electronic technology as automobile core technology is rapidly developed, the proportion of automobile electronic products on automobiles is larger and larger, the visual angle of a driver can be improved by carrying out picture enhancement on rearview mirrors of the automobiles, the problem that the original optical rearview mirrors on the left side and the right side are small in visual field and basically cannot see the visual field behind the automobiles due to the influence of rain, fog and weather is solved, and the automobile electronic technology is greatly helpful for driving safety.
The current method for enhancing the rearview mirror image mainly achieves the purpose of enhancing the image by carrying out unilateral light supplementing treatment and enhanced color treatment on the rearview mirror image, but the method does not consider the weather environment of a vehicle, and cannot reduce the influence of the environment on the rearview mirror image when a rainy day and a foggy day occur, thereby leading to the enhancement effect of the rearview mirror image, so that a method capable of improving the enhancement effect of the display image based on the rearview mirror of the vehicle is needed.
Disclosure of Invention
The invention provides a display screen enhancement method and a display screen enhancement system based on a vehicle rearview mirror, and mainly aims to improve the display screen enhancement effect based on the vehicle rearview mirror.
In order to achieve the above object, the present invention provides a method for enhancing a display screen based on a vehicle rearview mirror, comprising:
Acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, performing image digitization processing on the rearview mirror image to obtain a digitized image, performing spectrum analysis on the rearview mirror image to obtain an image spectrum, extracting a spectrum peak value and a spectrum valley value in the image spectrum, obtaining an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and performing image coding processing on the digitized image according to the distortion degree to obtain a coded image;
performing image binarization processing on the coded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image according to the brightness value, extracting contour parameters of the contour to be fitted, setting compensation parameters of the binarized image according to the contour parameters, combining the compensation parameters, performing image compensation on the coded image to obtain a compensation image, performing filtering processing on the compensation image to obtain a filtered image, extracting an entity image in the filtered image, and performing linear transformation on the entity image to obtain a linear image;
Constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and carrying out equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
and calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and scheduling a mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is greater than a preset ambiguity so as to execute cleaning treatment on the vehicle rearview mirror to obtain a target rearview mirror.
Optionally, the calculating the distortion degree of the rearview mirror image according to the image frequency band includes:
collecting digital signals corresponding to the rearview mirror images, detecting signal energy values corresponding to the digital signals, and creating a signal diagram corresponding to the rearview mirror images according to the signal energy values;
constructing an image amplifier of the signal diagram according to the image frequency band, and performing scaling processing on the signal diagram by using the image amplifier to obtain a scaled image;
and calculating the image similarity of the scaled image and the signal diagram, and taking a scaling coefficient corresponding to the scaled image as the distortion degree of the rearview mirror image when the image similarity is smaller than a preset threshold value.
Optionally, the filtering processing is performed on the compensation image to obtain a filtered image, including:
extracting image pixel points of the compensation image, and measuring the number of the image pixel points to obtain the number of the pixel points;
constructing a filter matrix of the compensation image according to the number of the pixel points, and carrying out matrix division on the pixel points of the image by utilizing the filter matrix to obtain a pixel point matrix;
calculating the pixel mean value of the pixel point matrix by the following formula:
and generating a filtered image of the compensation image according to the pixel mean value.
Optionally, the performing linear transformation on the entity image to obtain a linear image includes:
image framing is carried out on the entity image to obtain an entity framing image, and feature extraction is carried out on the entity framing image to obtain an entity feature image;
performing attribute analysis on the entity feature image to obtain entity feature attributes, and calculating the importance degree of each feature in the entity feature image according to the entity feature attributes;
According to the importance, performing linear transformation on pixels in the entity characteristic image through the following formula to obtain a characteristic pixel value;
and generating a characteristic linear image according to the characteristic pixel value, and carrying out image combination on the characteristic linear image to obtain a linear image.
Optionally, the calculating the importance degree of each feature in the entity feature image includes:
the importance of each feature in the physical feature image is calculated by the following formula:
Optionally, the performing equalization processing on the linear image according to the histogram and the environmental parameter to obtain an equalized image includes:
Marking a variable item with equalization processing in the histogram, and calculating an interference coefficient of the current environment on the vehicle rearview mirror according to the environment parameter;
and calculating the pixel density of each pixel of the linear image, and carrying out equalization processing on the pixel density according to the interference coefficient and the variable item to obtain an equalized image of the linear image.
Optionally, the performing equalization processing on the pixel density according to the interference coefficient and the variable term to obtain an equalized pixel value includes:
and carrying out equalization treatment on the pixel density by the following formula:
wherein S represents the pixel value after the pixel density is subjected to the equalization processing, mu represents the interference coefficient, i represents the initial pixel point of the pixel density, Q represents the pixel value corresponding to the pixel point in the pixel density, and R v Representation imageThe pixel number corresponding to the pixel value V, T represents the total number of pixels of the pixel density, and omega represents the mapping value corresponding to the variable item;
and generating an equilibrium image of the linear image according to the equilibrium pixel value.
In order to solve the above problems, the present invention also provides a display screen enhancement system based on a vehicle rearview mirror, the system comprising:
The image coding module is used for acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, carrying out image digitization processing on the rearview mirror image to obtain a digitized image, carrying out frequency spectrum analysis on the rearview mirror image to obtain an image frequency spectrum, extracting a frequency spectrum peak value and a frequency spectrum valley value in the image frequency spectrum, obtaining an image frequency band of the image frequency spectrum according to the frequency spectrum peak value and the frequency spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and carrying out image coding processing on the digitized image according to the distortion degree to obtain a coded image;
the linear conversion module is used for carrying out image binarization processing on the coded image to obtain a binarized image, detecting the brightness value of the binarized image, determining the contour to be fitted of the binarized image according to the brightness value, extracting the contour parameter of the contour to be fitted, setting the compensation parameter of the binarized image according to the contour parameter, carrying out image compensation on the coded image by combining the compensation parameter to obtain a compensation image, carrying out filtering processing on the compensation image to obtain a filtered image, extracting the entity image in the filtered image, and carrying out linear transformation on the entity image to obtain a linear image;
The image equalization module is used for constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and performing equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
and the rearview mirror cleaning module is used for calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and dispatching the mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is larger than the preset ambiguity so as to execute the cleaning treatment of the vehicle rearview mirror to obtain the target rearview mirror.
The invention can obtain corresponding image information in the vehicle rearview mirror by acquiring the vehicle rearview mirror to be processed and detecting the rearview mirror image in real time so as to process the rearview mirror image in the following, and can obtain a binarized image by carrying out image binarization processing on the coded image, and can determine parameters such as brightness and the like on the coded image so as to carry out compensation processing on the parameter image in the following; in addition, the mirror surface ambiguity of the vehicle rearview mirror is identified based on the balanced image, the ambiguity of the vehicle rearview mirror can be known through the mirror surface ambiguity, and a guarantee is provided for a follow-up dispatching mirror surface cleaning instruction of the vehicle rearview mirror so as to achieve the aim of enhancing a rearview mirror image. Therefore, the display screen enhancement method and the display screen enhancement system based on the vehicle rearview mirror can improve the display screen enhancement effect based on the vehicle rearview mirror.
Drawings
Fig. 1 is a flowchart of a method for enhancing a display screen based on a vehicle rearview mirror according to an embodiment of the invention;
FIG. 2 is a functional block diagram of a display enhancement system based on a rearview mirror of a vehicle according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the method for enhancing a display screen based on a vehicle rearview mirror according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a display screen enhancement method based on a vehicle rearview mirror. In the embodiment of the present application, the execution body of the display screen enhancement method based on the vehicle rearview mirror includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided in the embodiment of the present application. In other words, the vehicle rearview mirror-based display screen enhancement method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a method for enhancing a display screen based on a vehicle rearview mirror according to an embodiment of the invention is shown. In this embodiment, the method for enhancing the display screen based on the vehicle rearview mirror includes steps S1 to S4:
s1, acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, performing image digitization processing on the rearview mirror image to obtain a digitized image, performing spectrum analysis on the rearview mirror image to obtain an image spectrum, extracting a spectrum peak value and a spectrum valley value in the image spectrum, obtaining an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and performing image coding processing on the digitized image according to the distortion degree to obtain a coded image.
According to the invention, the rearview mirror image in the vehicle rearview mirror is detected in real time by acquiring the vehicle rearview mirror to be processed, so that the corresponding image information in the vehicle rearview mirror can be obtained, and the rearview mirror image can be processed later.
The vehicle rearview mirror is a rearview mirror for observing vehicle information at the rear part in a vehicle, the visual field range of a driver is enlarged, the rearview mirror image is reflected image information in the vehicle rearview mirror, the digital image is a two-dimensional array image obtained by digital processing of the rearview mirror image, the image spectrum is a spatial frequency corresponding to the rearview mirror image, the spectrum peak value and the spectrum valley value respectively represent the maximum value and the minimum value in the image spectrum, the image frequency band is the frequency range of the image spectrum, and the distortion degree is a coefficient which has no obvious change after the rearview mirror image is amplified or reduced by a certain coefficient.
Further, the rearview mirror image in the vehicle rearview mirror can be detected by an image sensor, the image digitization processing of the rearview mirror image can be realized by a discrete cosine transform method, the spectrum analysis of the rearview mirror image can be analyzed by a spectrum analyzer, the spectrum peak value and the spectrum valley value in the image spectrum can be extracted by a left function, and the image coding processing of the digitized image can be obtained by a statistical coding method.
The invention obtains the coded image by carrying out image coding processing on the digitized image, and can compress the digitized image so as to reduce the memory of the image, thereby being convenient for improving the subsequent discharging efficiency of the image, wherein the coded image is the image obtained by compressing the digitized image.
Further, as an optional embodiment of the present invention, the calculating the distortion degree of the rearview mirror image according to the image frequency band includes: collecting digital signals corresponding to the rearview mirror image, detecting signal energy values corresponding to the digital signals, creating a signal diagram corresponding to the rearview mirror image according to the signal energy values, constructing an image amplifier of the signal diagram according to the image frequency band, performing scaling processing on the signal diagram by using the image amplifier to obtain a scaled image, calculating the image similarity of the scaled image and the signal diagram, and taking a scaling coefficient corresponding to the scaled image as the distortion degree of the rearview mirror image when the image similarity is smaller than a preset threshold.
The digital signal is a binary digital representation signal corresponding to the rearview mirror image, the signal energy value is an integral of an amplitude square of the digital signal, the signal image is a signal image representation form of the rearview mirror image, the image amplifier amplifies the signal image, the scaled image is an image obtained by scaling the signal image, the image similarity represents the similarity degree between the scaled image and the signal image, the preset threshold is a criterion of the image similarity, and the criterion can be 0.8 or can be set according to an actual service scene.
Further, as an optional embodiment of the present invention, the digital signal corresponding to the rearview mirror image may be acquired by a signal acquisition device, the signal energy value corresponding to the digital signal may be detected by an energy detector, the energy detector is compiled by a scripting language, the signal map corresponding to the rearview mirror image may be created by an illustrator tool, the image amplifier of the signal image may be constructed by a discrete design method, and the image similarity between the scaled image and the signal map may be calculated by a cosine similarity algorithm.
S2, performing image binarization processing on the coded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image according to the brightness value, extracting contour parameters of the contour to be fitted, setting compensation parameters of the binarized image according to the contour parameters, combining the compensation parameters, performing image compensation on the coded image to obtain a compensation image, performing filtering processing on the compensation image to obtain a filtered image, extracting an entity image in the filtered image, and performing linear transformation on the entity image to obtain a linear image.
According to the invention, the coded image is subjected to image binarization processing, so that the coded image is subjected to image binarization processing to obtain a binarized image, and the brightness value of the binarized image is detected, so that parameters such as brightness and the like of the coded image can be determined, and the subsequent compensation processing of the parameter image is facilitated.
The binary image is an image of the coded image represented by a single tone, the brightness value is the brightness degree corresponding to the binary image, the contour to be fitted is a contour with obvious change of the brightness degree in the binary image, the contour parameter is data information corresponding to the contour to be fitted, and the compensation parameter is a parameter required to meet the compensation of the contour to be fitted.
Further, the image binarization processing of the encoded image may be performed by a maximum inter-class variance method, the luminance value of the binarized image may be detected by a luminance detector, the contour parameter of the contour to be fitted may be extracted by a parameter extraction tool, the parameter extraction tool is compiled by Java, and the image compensation of the encoded image may be performed by an illumination compensation algorithm, where the illumination compensation algorithm includes a gray world color equalization algorithm.
The invention can carry out denoising treatment on the compensation image by carrying out filtering treatment on the compensation image so as to obtain an image without noise interference, wherein the filtering image is an image obtained by removing the noise interference in the compensation image.
As an embodiment of the present invention, the filtering the compensation image to obtain a filtered image includes: extracting image pixels of the compensation image, measuring the number of the image pixels to obtain the number of the pixels, constructing a filter matrix of the compensation image according to the number of the pixels, dividing the image pixels by using the filter matrix to obtain a pixel matrix, calculating the pixel mean value of the pixel matrix, and generating a filter image of the compensation image according to the pixel mean value.
The image pixel points are pixel points in the compensation image, the filter matrix is a matrix when the image is subjected to filter processing, the pixel point matrix is a square matrix with a certain size obtained by dividing the image pixel points through the filter matrix, and the pixel mean value is a pixel point mean value in the pixel point matrix.
Further, the image pixels of the compensation image may be extracted by a pixel extractor, the filter matrix of the compensation image may be constructed by a matrix function, and the filter image of the compensation image may be generated by a pixel-to-picture converter.
Further, in an optional embodiment of the present invention, the calculating a pixel mean value of the pixel point matrix includes:
calculating the pixel mean value of the pixel point matrix by the following formula:
further, the invention extracts the entity image in the filtering image, carries out linear transformation on the entity image, and can convert the brightness value of the entity image into a new brightness value through a function, thereby facilitating the subsequent equalization processing on the linear image, wherein the entity image is an image of the entity part in the filtering image, the linear image is an image obtained after the entity image is subjected to linear transformation, and further, the entity image in the filtering image can be extracted through an entity extraction algorithm, and the entity extraction algorithm comprises a Pipeline method.
As one embodiment of the present invention, the performing linear transformation on the physical image to obtain a linear image includes: performing image framing on the entity image to obtain an entity framing image, performing feature extraction on the entity framing image to obtain an entity feature image, performing attribute analysis on the entity feature image to obtain an entity feature attribute, calculating the importance of each feature in the entity feature image according to the entity feature attribute, performing linear transformation on the entity feature image according to the importance to obtain a feature linear image, and performing image merging on the feature linear image to obtain a linear image.
The physical frame image is an image obtained after the physical image is subjected to frame division, the physical feature image is a representative part in the physical frame image, the physical feature attribute is attribute information corresponding to the physical feature, the importance degree represents the importance degree of each feature in the physical feature image, and the feature linear image is an image obtained after the physical feature image is subjected to linear change.
Further, in an alternative embodiment of the present invention, the image framing of the entity image is implemented by a framing tool, such as a PR framing tool, the feature extraction of the entity framing image may be implemented by an lbp feature extraction algorithm, the attribute analysis of the entity feature image may be implemented by a preset attribute analysis method, and the preset attribute analysis method may be compiled by a python language.
Further, in an alternative embodiment of the present invention, the importance of each feature in the physical feature image is calculated by the following formula:
In an optional embodiment of the invention, the performing linear transformation on the entity characteristic image includes:
the physical feature image is linearly transformed by the following formula:
s3, constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and carrying out equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image.
The invention detects the current environment of the vehicle rearview mirror in real time by constructing the histogram of the linear image, extracts the environment parameters of the current environment, can learn the visual expression diagram of various parameters of the linear image through the histogram, can learn various data of the current environment through the environment parameters, and is convenient for carrying out equalization processing on the linear image, wherein the histogram is a quality distribution diagram of the linear image, the current environment is the environment where the vehicle rearview mirror is located, the environment parameters are various data information of the current environment, and further, the histogram of the linear image can be constructed through a Visio drawing tool, and the detection of the current environment of the vehicle rearview mirror can be realized through an environment detection instrument.
According to the invention, the linear image is subjected to equalization processing according to the histogram and the environmental parameter, and the overall quality of the linear image can be improved by the equalization processing of the linear image, so that a high-quality image can be conveniently obtained, wherein the equalization image is an image obtained by nonlinear stretching of the whole linear image, and is more balanced relative to the overall image parameter of the original image.
As one embodiment of the present invention, the performing an equalization process on the linear image according to the histogram and the environmental parameter to obtain an equalized image includes: marking a variable item with equalization processing in the histogram, calculating an interference coefficient of the current environment on the vehicle rearview mirror according to the environment parameter, calculating the pixel density of each pixel of the linear image, and carrying out equalization processing on the pixel density according to the interference coefficient and the variable item to obtain an equalization image of the linear image.
The variable item is a variable item with the lowest probability in the histogram, the interference coefficient represents the influence degree of the current environment on the vehicle rearview mirror, and the pixel density represents the pixel distribution probability in the linear image.
Furthermore, the variable item with equalization processing in the histogram can be obtained through marking by a marking tool, the marking tool comprises a color tool, the pixel density of each pixel of the linear image can be obtained through calculating a probability density function, and the interference coefficient of the current environment on the rearview mirror of the vehicle can be obtained through calculating an interference coefficient algorithm.
As an optional embodiment of the present invention, the performing the equalization processing on the pixel density to obtain an equalized image of the linear image includes:
and carrying out equalization treatment on the pixel density by the following formula:
wherein S represents the pixel value after the pixel density is subjected to the equalization processing, i represents the initial pixel point of the pixel density, Q represents the pixel value corresponding to the pixel point in the pixel density, and R v The number of pixels corresponding to the pixel value V is represented, and T represents the total number of pixels of the pixel density.
And S4, calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and scheduling a mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is larger than a preset ambiguity so as to execute cleaning treatment on the vehicle rearview mirror to obtain a target rearview mirror.
According to the invention, the mirror surface ambiguity of the vehicle rearview mirror is identified based on the balanced image, the ambiguity of the vehicle rearview mirror can be known through the mirror surface ambiguity, and a guarantee is provided for a mirror surface cleaning instruction of the vehicle rearview mirror to be scheduled subsequently so as to achieve the aim of enhancing a rearview mirror picture, wherein the ambiguity represents the ambiguity of the vehicle rearview mirror.
As one embodiment of the present invention, the identifying the mirror surface ambiguity of the vehicle rearview mirror based on the equalized image includes: and determining the fuzzy factor of the vehicle rearview mirror according to the balanced image, calculating the weight coefficient of each factor in the fuzzy factor, and calculating the mirror surface ambiguity of the vehicle rearview mirror according to the weight coefficient.
The fuzzy factors are factors, such as dust, fog, rainwater and the like, in the balanced image, which cause the blurring of the vehicle rearview mirror, the weight coefficients represent the importance degree of the fuzzy factors, further, the fuzzy factors of the vehicle rearview mirror can be obtained by analyzing the factors in the balanced image, and the weight coefficient of each factor in the fuzzy factors can be calculated by an AHP (advanced high Performance) analytic hierarchy process.
As one embodiment of the present invention, the calculating the mirror surface ambiguity of the vehicle rearview mirror according to the weight coefficient includes:
calculating the mirror surface ambiguity of the vehicle rearview mirror by the following formula:
As an optional embodiment of the present invention, the calculating a weight coefficient of each factor of the blur factors includes:
calculating the weight coefficient of each factor in the fuzzy factors through the following formula:
wherein,,
weight coefficient representing each of the blurring factors, +.>
Representing the total number of blur factors>
Sequence numbers representing the blur factors, respectively,/->
Representing the weight score corresponding to the c-th fuzzy factor,>
representing the weight score corresponding to the d-th blurring factor,/>
representing the weight score corresponding to the nth blurring factor.
According to the invention, when the mirror surface ambiguity is larger than the preset ambiguity, a mirror surface cleaning instruction of the vehicle rearview mirror is dispatched to execute cleaning treatment of the vehicle rearview mirror to obtain a target rearview mirror, and it is understood that when the mirror surface ambiguity is larger than the preset ambiguity, the mirror surface cleaning instruction of the vehicle rearview mirror is dispatched to execute cleaning treatment of the vehicle rearview mirror, wherein the preset ambiguity is a standard value compared with the mirror surface ambiguity, the mirror surface cleaning instruction is an instruction for cleaning the vehicle rearview mirror, the target rearview mirror is obtained after the vehicle rearview mirror is cleaned, further, the mirror surface cleaning instruction of the vehicle rearview mirror can be dispatched through an algorithm, and the cleaning treatment of the vehicle rearview mirror can be realized through a cleaning device in a vehicle.
The invention can obtain corresponding image information in the vehicle rearview mirror by acquiring the vehicle rearview mirror to be processed and detecting the rearview mirror image in real time so as to process the rearview mirror image in the following, and can obtain a binarized image by carrying out image binarization processing on the coded image, and can determine parameters such as brightness and the like on the coded image so as to carry out compensation processing on the parameter image in the following; in addition, the mirror surface ambiguity of the vehicle rearview mirror is identified based on the balanced image, the ambiguity of the vehicle rearview mirror can be known through the mirror surface ambiguity, and a guarantee is provided for a follow-up dispatching mirror surface cleaning instruction of the vehicle rearview mirror so as to achieve the aim of enhancing a rearview mirror image. Therefore, the display picture enhancement method based on the vehicle rearview mirror provided by the embodiment of the invention can improve the display picture enhancement effect based on the vehicle rearview mirror.
Fig. 2 is a functional block diagram of a display screen enhancement system based on a vehicle rearview mirror according to an embodiment of the present invention.
The display enhancement system 100 based on the vehicle rearview mirror according to the present invention may be installed in an electronic device. Depending on the functions implemented, the vehicle rearview mirror based display screen enhancement system 100 may include an image encoding module 101, a linear conversion module 102, an image equalization module 103, and a rearview mirror cleaning module 104. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the image encoding module 101 is configured to obtain a vehicle rearview mirror to be processed, detect a rearview mirror image in the vehicle rearview mirror in real time, perform image digitization processing on the rearview mirror image to obtain a digitized image, perform spectrum analysis on the rearview mirror image to obtain an image spectrum, extract a spectrum peak value and a spectrum valley value in the image spectrum, obtain an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculate a distortion degree of the rearview mirror image according to the image frequency band, and perform image encoding processing on the digitized image according to the distortion degree to obtain an encoded image;
The linear conversion module 102 is configured to perform image binarization processing on the encoded image to obtain a binarized image, detect a brightness value of the binarized image, determine a contour to be fitted of the binarized image according to the brightness value, extract a contour parameter of the contour to be fitted, set a compensation parameter of the binarized image according to the contour parameter, perform image compensation on the encoded image in combination with the compensation parameter to obtain a compensated image, perform filtering processing on the compensated image to obtain a filtered image, extract an entity image in the filtered image, and perform linear transformation on the entity image to obtain a linear image;
the image balancing module 103 is configured to construct a histogram of the linear image, detect a current environment of the vehicle rearview mirror in real time, extract an environmental parameter of the current environment, and perform balancing processing on the linear image according to the histogram and the environmental parameter to obtain a balanced image;
the rearview mirror cleaning module 104 is configured to calculate a mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and schedule a mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is greater than a preset ambiguity, so as to perform cleaning processing on the vehicle rearview mirror, and obtain a target rearview mirror.
In detail, each module in the display screen enhancing device 100 based on a vehicle rearview mirror according to the embodiment of the present application adopts the same technical means as the display screen enhancing method based on a vehicle rearview mirror according to fig. 1, and can produce the same technical effects, which are not described herein.
Fig. 3 is a schematic structural diagram of an electronic device 1 according to an embodiment of the present invention for implementing a display screen enhancement method based on a vehicle rearview mirror.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a display enhancement method program based on a vehicle rear view mirror.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing Unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 10 is a Control Unit (Control Unit) of the electronic device 1, connects respective parts of the entire electronic device using various interfaces and lines, executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory 11 (for example, executing a display screen enhancing method program based on a vehicle rear view mirror, etc.), and calls data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used not only for storing application software installed in an electronic device and various types of data, such as codes of a display screen enhancement method program based on a vehicle rear view mirror, but also for temporarily storing data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device 1 and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The display screen enhancement method program based on the vehicle rearview mirror stored in the memory 11 in the electronic device 1 is a combination of a plurality of instructions, which when executed in the processor 10, can realize:
acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, performing image digitization processing on the rearview mirror image to obtain a digitized image, performing spectrum analysis on the rearview mirror image to obtain an image spectrum, extracting a spectrum peak value and a spectrum valley value in the image spectrum, obtaining an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and performing image coding processing on the digitized image according to the distortion degree to obtain a coded image;
Performing image binarization processing on the coded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image according to the brightness value, extracting contour parameters of the contour to be fitted, setting compensation parameters of the binarized image according to the contour parameters, combining the compensation parameters, performing image compensation on the coded image to obtain a compensation image, performing filtering processing on the compensation image to obtain a filtered image, extracting an entity image in the filtered image, and performing linear transformation on the entity image to obtain a linear image;
constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and carrying out equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
and calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and scheduling a mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is greater than a preset ambiguity so as to execute cleaning treatment on the vehicle rearview mirror to obtain a target rearview mirror.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, performing image digitization processing on the rearview mirror image to obtain a digitized image, performing spectrum analysis on the rearview mirror image to obtain an image spectrum, extracting a spectrum peak value and a spectrum valley value in the image spectrum, obtaining an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and performing image coding processing on the digitized image according to the distortion degree to obtain a coded image;
Performing image binarization processing on the coded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image according to the brightness value, extracting contour parameters of the contour to be fitted, setting compensation parameters of the binarized image according to the contour parameters, combining the compensation parameters, performing image compensation on the coded image to obtain a compensation image, performing filtering processing on the compensation image to obtain a filtered image, extracting an entity image in the filtered image, and performing linear transformation on the entity image to obtain a linear image;
constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and carrying out equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
and calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and scheduling a mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is greater than a preset ambiguity so as to execute cleaning treatment on the vehicle rearview mirror to obtain a target rearview mirror.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, system and method may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. A method for enhancing a display screen based on a vehicle rearview mirror, the method comprising:
acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, performing image digitization processing on the rearview mirror image to obtain a digitized image, performing spectrum analysis on the rearview mirror image to obtain an image spectrum, extracting a spectrum peak value and a spectrum valley value in the image spectrum, obtaining an image frequency band of the image spectrum according to the spectrum peak value and the spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and performing image coding processing on the digitized image according to the distortion degree to obtain a coded image;
performing image binarization processing on the coded image to obtain a binarized image, detecting a brightness value of the binarized image, determining a contour to be fitted of the binarized image according to the brightness value, extracting contour parameters of the contour to be fitted, setting compensation parameters of the binarized image according to the contour parameters, combining the compensation parameters, performing image compensation on the coded image to obtain a compensation image, performing filtering processing on the compensation image to obtain a filtered image, extracting an entity image in the filtered image, and performing linear transformation on the entity image to obtain a linear image;
Constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and carrying out equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
based on the equalized image, a mirror surface ambiguity of the vehicle rearview mirror is calculated by the following formula:
and when the mirror surface ambiguity is greater than a preset ambiguity, dispatching a mirror surface cleaning instruction of the vehicle rearview mirror so as to execute cleaning treatment on the vehicle rearview mirror and obtain a target rearview mirror.
2. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 1, wherein said calculating a distortion degree of said rearview mirror image from said image band comprises:
collecting digital signals corresponding to the rearview mirror images, detecting signal energy values corresponding to the digital signals, and creating a signal diagram corresponding to the rearview mirror images according to the signal energy values;
Constructing an image amplifier of the signal diagram according to the image frequency band, and performing scaling processing on the signal diagram by using the image amplifier to obtain a scaled image;
and calculating the image similarity of the scaled image and the signal diagram, and taking a scaling coefficient corresponding to the scaled image as the distortion degree of the rearview mirror image when the image similarity is smaller than a preset threshold value.
3. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 1, wherein said filtering the compensation image to obtain a filtered image comprises:
extracting image pixel points of the compensation image, and measuring the number of the image pixel points to obtain the number of the pixel points;
constructing a filter matrix of the compensation image according to the number of the pixel points, and carrying out matrix division on the pixel points of the image by utilizing the filter matrix to obtain a pixel point matrix;
calculating the pixel mean value of the pixel point matrix by the following formula:
and generating a filtered image of the compensation image according to the pixel mean value.
4. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 1, wherein said linearly transforming the physical image to obtain a linear image comprises:
image framing is carried out on the entity image to obtain an entity framing image, and feature extraction is carried out on the entity framing image to obtain an entity feature image;
performing attribute analysis on the entity feature image to obtain entity feature attributes, and calculating the importance degree of each feature in the entity feature image according to the entity feature attributes;
according to the importance, performing linear transformation on pixels in the entity characteristic image through the following formula to obtain a characteristic pixel value;
and generating a characteristic linear image according to the characteristic pixel value, and carrying out image combination on the characteristic linear image to obtain a linear image.
5. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 4, wherein said calculating the importance of each feature in said physical feature image comprises:
The importance of each feature in the physical feature image is calculated by the following formula:
6. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 1, wherein said performing an equalization process on said linear image based on said histogram and said environmental parameter to obtain an equalized image comprises:
marking a variable item with equalization processing in the histogram, and calculating an interference coefficient of the current environment on the vehicle rearview mirror according to the environment parameter;
and calculating the pixel density of each pixel of the linear image, and carrying out equalization processing on the pixel density according to the interference coefficient and the variable item to obtain an equalized image of the linear image.
7. The method for enhancing a display screen based on a vehicle rearview mirror according to claim 6, wherein said equalizing the pixel density according to the interference coefficient and the variable term to obtain an equalized pixel value comprises:
And carrying out equalization treatment on the pixel density by the following formula:
and generating an equilibrium image of the linear image according to the equilibrium pixel value.
8. A vehicle rearview mirror based display enhancement system, the system comprising:
the image coding module is used for acquiring a vehicle rearview mirror to be processed, detecting a rearview mirror image in the vehicle rearview mirror in real time, carrying out image digitization processing on the rearview mirror image to obtain a digitized image, carrying out frequency spectrum analysis on the rearview mirror image to obtain an image frequency spectrum, extracting a frequency spectrum peak value and a frequency spectrum valley value in the image frequency spectrum, obtaining an image frequency band of the image frequency spectrum according to the frequency spectrum peak value and the frequency spectrum valley value, calculating the distortion degree of the rearview mirror image according to the image frequency band, and carrying out image coding processing on the digitized image according to the distortion degree to obtain a coded image;
The linear conversion module is used for carrying out image binarization processing on the coded image to obtain a binarized image, detecting the brightness value of the binarized image, determining the contour to be fitted of the binarized image according to the brightness value, extracting the contour parameter of the contour to be fitted, setting the compensation parameter of the binarized image according to the contour parameter, carrying out image compensation on the coded image by combining the compensation parameter to obtain a compensation image, carrying out filtering processing on the compensation image to obtain a filtered image, extracting the entity image in the filtered image, and carrying out linear transformation on the entity image to obtain a linear image;
the image equalization module is used for constructing a histogram of the linear image, detecting the current environment of the vehicle rearview mirror in real time, extracting the environment parameters of the current environment, and performing equalization processing on the linear image according to the histogram and the environment parameters to obtain an equalized image;
and the rearview mirror cleaning module is used for calculating the mirror surface ambiguity of the vehicle rearview mirror based on the balanced image, and dispatching the mirror surface cleaning instruction of the vehicle rearview mirror when the mirror surface ambiguity is larger than the preset ambiguity so as to execute the cleaning treatment of the vehicle rearview mirror to obtain the target rearview mirror.
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