CN114245004A - Image compensation method, system, hard disk video recorder and readable storage medium - Google Patents

Image compensation method, system, hard disk video recorder and readable storage medium Download PDF

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CN114245004A
CN114245004A CN202111433278.4A CN202111433278A CN114245004A CN 114245004 A CN114245004 A CN 114245004A CN 202111433278 A CN202111433278 A CN 202111433278A CN 114245004 A CN114245004 A CN 114245004A
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image
value
deviation
saturation
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CN114245004B (en
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刘泳金
冯亮
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Zhejiang Dahua Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/222—Studio circuitry; Studio devices; Studio equipment
    • H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/76—Television signal recording
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application discloses an image compensation method, a system, a hard disk video recorder and a readable storage medium, wherein the image compensation method comprises the following steps: acquiring a first reference image and a first historical image shot by the camera equipment, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the camera equipment through a transmission line; comparing the first reference image with the first historical image to obtain pixel difference data; generating a first deviation value based on the pixel difference data; and updating an image balance table in the hard disk video recorder based on the first deviation value to obtain a new image balance table, and compensating the image to be compensated received from the camera equipment by using the new image balance table. By the mode, the self-adaptive compensation of the image can be realized.

Description

Image compensation method, system, hard disk video recorder and readable storage medium
Technical Field
The present application relates to the field of image processing technologies, and in particular, to an image compensation method, system, hard disk video recorder, and readable storage medium.
Background
After a camera is connected to a Digital Video Recorder (DVR), in the process that the camera transmits acquired image data to DVR equipment through a Coaxial Cable (Coaxial Cable) or a Twisted Pair Cable (TP), parameter information (including hue, saturation and brightness) of an image is attenuated to different degrees along with the length of a transmission Cable, so that distortion phenomena such as color fading or brightness dimming of the image occur; although the current DVR device can perform attenuation compensation on an image according to the image equalization table, the image equalization table is set according to the standard camera, so that only the image acquired by the standard camera can be adjusted in the image adjustment process, and when the image acquired by the camera other than the standard camera is adjusted, the image display distortion/abnormality may occur.
Disclosure of Invention
The application provides an image compensation method, an image compensation system, a hard disk video recorder and a readable storage medium, which can realize self-adaptive compensation of images.
In order to solve the technical problem, the technical scheme adopted by the application is as follows: there is provided an image compensation method including: acquiring a first reference image and a first historical image shot by the camera equipment, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the camera equipment through a transmission line; comparing the first reference image with the first historical image to obtain pixel difference data; generating a first deviation value based on the pixel difference data; and updating an image balance table in the hard disk video recorder based on the first deviation value to obtain a new image balance table, and compensating the image to be compensated received from the camera equipment by using the new image balance table.
In order to solve the above technical problem, another technical solution adopted by the present application is: there is provided a hard disk video recorder comprising a memory and a processor connected to each other, wherein the memory is used for storing a computer program, and the computer program is used for implementing the image compensation method in the above technical solution when being executed by the processor.
In order to solve the above technical problem, another technical solution adopted by the present application is: the image compensation system comprises the camera device and the hard disk video recorder which are connected with each other, wherein the hard disk video recorder is used for compensating images output by the camera device, and the hard disk video recorder is the hard disk video recorder in the technical scheme.
In order to solve the above technical problem, another technical solution adopted by the present application is: there is provided a computer readable storage medium for storing a computer program for implementing the image compensation method in the above technical solution when the computer program is executed by a processor.
Through the scheme, the beneficial effects of the application are that: the method comprises the steps that a first reference image and a first historical image shot by a camera device are obtained, the first historical image is an image generated by the fact that the first reference image is transmitted to a hard disk video recorder through a transmission line by the camera device, namely the first historical image is an image which is possibly attenuated, and the first reference image is an unattenuated image; then comparing the first reference image with the first historical image to obtain pixel difference data between the unattenuated image and the attenuated image, and generating a first deviation value by using the pixel difference data; then, updating the image balance table by using the first deviation value to obtain a new image balance table, and compensating the image to be compensated transmitted by the camera equipment by using the new image balance table; through the cooperation of the hard disk video recorder and the camera equipment, the image balance table can be adaptively updated in real time, the updated image balance table is used for compensating the subsequently received images, the image display distortion or abnormity condition is improved, the image quality is improved, and the accuracy of subsequent operations (such as image detection, identification or tracking) is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:
FIG. 1 is a schematic diagram of an embodiment of an image compensation system provided in the present application;
FIG. 2 is a schematic structural diagram of an embodiment of a hard disk video recorder provided in the present application;
FIG. 3 is a schematic diagram of the connection between the image pickup apparatus and the hard disk video recorder provided in the present application;
FIG. 4 is a flowchart illustrating an embodiment of an image compensation method provided in the present application;
FIG. 5 is a schematic flowchart of another embodiment of an image compensation method provided in the present application;
FIG. 6 is a schematic flow chart of the calculation of pixel difference data provided herein;
FIG. 7 is a schematic flow chart illustrating a process for obtaining a second deviation value according to the present application;
FIG. 8 is a schematic diagram of a preset deviation table provided herein;
FIG. 9 is a schematic structural diagram of an embodiment of a computer-readable storage medium provided in the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be noted that the following examples are only illustrative of the present application, and do not limit the scope of the present application. Likewise, the following examples are only some examples and not all examples of the present application, and all other examples obtained by a person of ordinary skill in the art without any inventive work are within the scope of the present application.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
It should be noted that the terms "first", "second" and "third" in the present application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic structural diagram of an embodiment of an image compensation system provided in the present application, and fig. 2 is a schematic structural diagram of an embodiment of a hard disk recorder provided in the present application, where the image compensation system 1 includes an image capturing device 10 and a hard disk recorder 20 that are connected to each other, the hard disk recorder 20 is configured to compensate an image output by the image capturing device 10, the image capturing device 10 may be a camera, and the hard disk recorder 20 is a DVR device.
The hard disk recorder 20 comprises a memory 21 and a processor 22 connected to each other, the memory 21 being used for storing a computer program, which when executed by the processor 22 is used for implementing the image compensation method provided by the present application, which will be described in detail below.
In a specific embodiment, referring to fig. 2 and fig. 3 in combination, the Image capturing apparatus 10 may be connected to the hard disk recorder 20 via a coaxial cable/twisted pair cable for data transmission, the Image capturing apparatus 10 may include an Image Sensor (Sensor)11 and an Image Signal Processing module (ISP) 12, the Image Sensor 11 is configured to capture an Image and transmit the Image to the Image Signal Processing module 12; the image signal processing module 12 processes the image output by the image sensor 11, converts the processed image into YUV data, performs digital-to-analog conversion on the YUV data, converts the YUV data into analog data, and transmits the analog data to the hard disk video recorder 20 through the coaxial cable/twisted pair cable.
The hard disk recorder 20 further includes an analog to Digital (AD) conversion chip 23, the processor 22 includes a main control chip 221, the AD conversion chip 23 is configured to receive analog data output by the image signal processing module 12, perform an AD conversion process on the analog data to convert the analog data into Digital data, and transmit the Digital data to the main control chip 221 by using a BT656 protocol; the main control chip 221 includes a video capture module 2211, a video pre-processing module 2212, and a video display module 2213, where the video capture module 2211 is configured to receive digital data and transmit the digital data to the video pre-processing module 2212, the video pre-processing module 2212 is configured to perform video pre-processing on the data, and then transmit the processed image data to the video display module 2213 for image display on a View Object (VO), and the video pre-processing may include operations such as image enlargement/reduction, sharpening, or filtering.
Further, the analog-to-digital conversion chip 23 may further include a storage device (not shown in the figure), such as: the FLASH memory (FLASH) can compensate the image through an image balance table stored in the FLASH, compensate the attenuation generated in the transmission process of the image and improve the distortion or abnormal condition of image display, the image balance table is a set of attenuation values and optimal image parameter values under different line lengths obtained by testing a standard camera, and the image parameters can comprise saturation, hue and brightness.
Specifically, when the image capturing apparatus 10 is connected to the hard disk recorder 20, the analog-to-digital conversion chip 23 may first identify the camera type (e.g., AHD720P/CVI1080P) and the cable type (coaxial cable/twisted pair cable) of the transmission cable, and then find out the corresponding camera format according to the camera type and the cable type in table 1 below, for example: the camera type of the accessed camera is CVI720P, and the cable type is coaxial cable, so that the corresponding camera system TCVI720P can be found.
TABLE 1 Camera systems and corresponding Cable types
Cable type Camera system Camera system Camera system Camera system
Coaxial cable TCVI720P TCVI1080P TAHD720P TAHD1080P
Twisted pair cable SCVI720P SCVI1080P SAHD720P SAHD1080P
The adc chip 23 may further identify and determine the attenuation values generated by the current day/night and the current image, and then look up the corresponding attenuation table, saturation table, hue table and brightness table in table 2 according to the obtained camera system and the current day/night, taking the above-mentioned camera system as TCVI720P as an example, if: in the daytime, the corresponding daytime attenuation table TDayDataC720 (as shown in table 3) can be found, the corresponding line length is found in table 3 according to the attenuation value generated by the identified current image, then the saturation value, the hue value and the brightness value corresponding to the line length are found in the saturation table, the hue table and the brightness table (as shown in table 4) according to the line length, and the saturation value, the hue value and the brightness value are stored in the FLASH of the analog-to-digital conversion chip 23, so that the adjustment of the saturation, the hue and the brightness of the image is realized, and the compensation processing of the image is completed.
TABLE 2 Camera System and corresponding attenuation Table
Figure BDA0003380932690000051
Figure BDA0003380932690000061
TABLE 3 line lengths and corresponding attenuation ranges
Figure BDA0003380932690000062
TABLE 4 line length and corresponding luminance, chrominance, and saturation values
Line length/m 1 25 50 75 100
TSatC720 0x50 0x60 0x70 0x80 0x90
THueC720 0x55 0x59 0x64 0x73 0x80
TBrigC720 0x71 0x72 0x73 0x75 0x77
It is understood that, for different types of image capturing apparatuses 10 that are connected, there may be differences in the images received by the analog-to-digital conversion chip 23, for example: the image color is too light, the hue is too high, the color is too bright, and the like, which cannot achieve the image effect expected by the user, and the image balance table stored in the analog-to-digital conversion chip 23 by default is relatively fixed, so that the saturation, hue, brightness and the like of the processed image can not be consistent with those of a standard camera when other camera devices are accessed; the image compensation method provided by the application can automatically adjust the existing default image balance table according to the accessed camera equipment, and generate the optimal image balance table suitable for the current camera equipment, so that the optimal image attenuation compensation processing is realized, the numerical requirements of different saturation, hue and brightness required by different camera equipment can be met, and the image compensation method is described in detail below.
Referring to fig. 4, fig. 4 is a schematic flowchart illustrating an embodiment of an image compensation method provided in the present application, the method including:
step 41: a first reference image and a first history image captured by an imaging apparatus are acquired.
Compensating the image to be adjusted so that the image generated after compensation can achieve the image effect presented by the first reference image, so that in order to ensure that the first reference image has reference, certain standards exist when the first reference image is selected, and firstly, the first reference image is consistent with the external environment where the image to be adjusted is located; secondly, the first reference image and the image to be adjusted are not subjected to image processing, such as filtering or sharpening; third, the first reference image is not signal attenuated.
In a specific embodiment, an AD chip may be used to acquire the first reference image from the image capturing device, the AD chip may be in communication connection with the image capturing device through an RS485 communication protocol in a High Definition Composite Video Interface (HDCVI) or other wireless communication methods, a transmission process of transmitting an image through the method is digital signal transmission, and a problem of signal attenuation does not occur, that is, the AD chip may directly acquire a frame of the first reference image without attenuation from the image capturing device.
Further, the first history image is an image generated by the first reference image being transmitted to the DVR device by the camera device through the transmission line, and transmission attenuation is generated when the acquired first reference image is transmitted through the transmission line, and the first history image acquired by the DVR device is the attenuated first reference image at this time; specifically, a main control chip in the DVR device is used to process data output by the AD chip to obtain a first historical image, please refer to fig. 3, the video pre-processing module 2212 may process the image, the processed image may generate a change in image style, and cannot be compared with a first reference image, so as to affect the accuracy of pixel difference data obtained by subsequent comparison, and therefore, the image acquired by the video acquisition module 2211 from the AD chip 23 is used as the first historical image, so as to avoid image differences generated by image processing.
Step 42: and comparing the first reference image with the first historical image to obtain pixel difference data.
An image has a plurality of pixels, and the number of pixels is related to the resolution of the image, for example: an image with a resolution of 250 x 360, having 250 x 360 pixels, each with respective parameter values, for example: saturation, hue or brightness, and the like, and corresponding comparison operation is performed on the parameter values corresponding to the pixels in the first reference image and the first history image, so that pixel difference data between the two images can be obtained.
Step 43: based on the pixel difference data, a first deviation value is generated.
After acquiring the pixel difference data, the following steps may be taken to generate a first deviation value:
1) and acquiring a second deviation value based on the pixel difference value data and a preset deviation table.
The preset deviation table comprises a pixel change range and an adjustment value corresponding to the pixel change range, and the adjustment value corresponding to the pixel change range currently obtained can be obtained through matching the pixel difference value data with the pixel change range in the preset deviation table, namely a second deviation value, wherein the second deviation value can represent a deviation value between a parameter in the image balance table to be updated currently and a target parameter to be adjusted. It is to be understood that the pixel difference data may include parameter difference data in terms of saturation, hue, or brightness, the preset deviation table may also include pixel variation ranges and adjustment values corresponding to the parameters of saturation, hue, or brightness, and the obtained second deviation values may also include a plurality of deviation values corresponding to the parameters of saturation, hue, or brightness.
Specifically, the data in the preset deviation table may be obtained according to an actual test, and in a specific embodiment, the actual measurement method may include: reading the values of the parameters such as saturation, chromaticity or brightness of the current image, sequentially adjusting the deviation values of the parameters such as saturation, chromaticity or brightness of the image, for example, adjusting the saturation deviation of the image by 0.5, reading the parameter values corresponding to the saturation of the image after deviation adjustment, calculating the saturation change range corresponding to the saturation deviation of 0.5 according to the parameter values corresponding to the saturation after adjustment and the parameter values corresponding to the saturation before adjustment, adjusting the magnitude of the deviation values in an increasing or decreasing manner, performing deviation adjustment on the saturation until the saturation parameter test is completed, and testing the rest of the parameters in the same manner.
2) And correcting the second deviation value based on the line length of the transmission line to obtain a first deviation value.
The larger the line length of the transmission line is, the larger the generated signal attenuation is, after the second deviation value is obtained according to the preset deviation table and the pixel difference value data, in order to further ensure the accuracy of the deviation value, the second deviation value is corrected according to the line length so as to obtain a more accurate first deviation value.
Step 44: and updating an image balance table in the hard disk video recorder based on the first deviation value to obtain a new image balance table, and compensating the image to be compensated received from the camera equipment by using the new image balance table.
After the current image balance table to be adjusted is updated by using the first deviation value to obtain a new image balance table suitable for the current camera equipment, the new image balance table can be written into the storage equipment so as to prevent data loss caused by accidents; specifically, the new image balance table may be stored in a FLASH of an AD chip in the DVR device, and when a subsequent AD chip receives a new image (i.e., an image to be compensated) from the image capturing device, the new image balance table may be used to compensate the image to be compensated.
Further, after a new image balance table is obtained, a compensation file can be generated based on the new image balance table and stored in a preset directory; after the DVR equipment is powered off and restarted, judging whether a compensation file exists in a preset directory or not; if the compensation file exists in the preset directory, the compensation file can be analyzed to obtain a new image balance table; if the compensation file does not exist in the preset directory, a new image balance table can be read from the storage device, and then the compensation is carried out on the image to be compensated based on the new image balance table.
In other embodiments, after the DVR device is powered off and restarted, there may be a case where the image capturing device is replaced, and at this time, the default image equalization table before updating may be directly read, and then adaptive updating may be performed based on the default image equalization table, and the image may be adjusted by referring to the newly generated image equalization table. The method can be understood that after the default image equalization table is updated to generate a new image equalization table, the default image equalization table before updating is still reserved, so that the default image equalization table can be called to be updated after the camera equipment is subsequently replaced; specifically, the updated new image balance table and the default image balance table may be stored in different storage devices in the AD chip, respectively, so that when the image capturing apparatus is replaced, the AD chip may directly acquire a required image balance table from the corresponding storage device.
In this embodiment, a first reference image and a first history image captured by an image capturing device are obtained, where the first history image is an image generated by the first reference image being transmitted to a hard disk video recorder by the image capturing device through a transmission line, that is, the first history image is an image which may have attenuation, and the first reference image is an unattenuated image; then comparing the first reference image with the first historical image to obtain pixel difference data between the unattenuated image and the attenuated image, and generating a first deviation value by using the pixel difference data; then, updating the image balance table by using the first deviation value to obtain a new image balance table, and compensating the image to be compensated transmitted by the camera equipment by using the new image balance table; through the cooperation of the hard disk video recorder and the camera equipment, the image balance table can be adaptively updated in real time, the updated image balance table is used for compensating the subsequently received images, the image display distortion or abnormity condition is improved, the image quality is improved, and the accuracy of subsequent operations (such as image detection, identification or tracking) is improved; the line length of the transmission line is used as a factor influencing the image equalization table to adjust the numerical value in the image equalization table, so that the numerical value in the image equalization table is closer to the actual application scene, and the accuracy of compensating the subsequent image by using the updated image equalization table is further improved.
Referring to fig. 5, fig. 5 is a schematic flowchart illustrating an image compensation method according to another embodiment of the present application, the method including:
step 51: a first reference image and a first history image captured by an imaging apparatus are acquired.
This step is the same as step 41 in the above embodiment, and is not described again here.
The first reference image and the first history image are images in YUV format, and after the first reference image and the first history image are acquired, the first reference image and the first history image are respectively converted into a second reference image and a second history image, and the second reference image and the second history image are images in HSV format, as shown in step 52-step 53.
Step 52: and respectively carrying out format conversion processing on the first reference image and the first historical image to obtain a third reference image and a third historical image.
When receiving an image acquired by an image sensor, an ISP module of the image pickup device may convert the image into a YUV data format, where both a first reference image and a first history image acquired from the image pickup device are in the YUV data format, and perform format conversion processing on the first reference image and the first history image, respectively, and convert the YUV data format into an RGB data format, so as to obtain a third reference image and a third history image in the RGB data format.
Specifically, each pixel in the image in YUV data format corresponds to Y, U, V three component values, "Y" represents brightness, "U" and "V" represent chroma, which represents the color and saturation of the image through the data format; each pixel in the image in the RGB data format corresponds to R, G, B three component values, the color and brightness corresponding to the pixel are represented by the combination of R, G, B three component values, and the conversion between the YUV data format and the RGB data format can be realized by a corresponding format conversion formula, which is as follows:
R＝Y+1.4075*V (1)
G＝Y-0.3455*U-0.7169*V (2)
B＝Y+1.779*U (3)
the format conversion formula is used for substituting Y, U, V component values in each pixel in the first reference image and the first history image into the format conversion formula, each pixel in the first reference image and the first history image is converted into R, G, B component values, the format conversion formula can be used for converting the first reference image in the data format of Y11-Y1 n, U11-U1 n and V11-V1 n into the third reference image in the data format of R11-R1 n, G11-G1 n and B11-B1 n, and the format conversion formula is used for converting the first history image in the data format of Y21-Y2 n, U21-U2 n and V21-V2 n into the third history image in the data format of R21-R2 n, G21-G2 n and B21-B2 n.
Step 53: and respectively carrying out format conversion processing on the third reference image and the third history image to obtain a second reference image and a second history image.
After an image in an RGB data format is obtained, the RGB data format of the image is converted into an HSV data format, the image in the HSV data format can comprise H, S, V three component values, "H" represents the chroma of a pixel, "S" represents the saturation of the pixel, and "V" represents the brightness of the pixel, and R11-R1 n, G11-G1 n and B11-B1 n in a third reference image are converted into H11-H1 n, S11-S1 n and V11-V1 n; R21-R2 n, G21-G2 n and B21-B2 n in the third history image are converted into H21-H2 n, S21-S2 n and V21-V2 n.
Specifically, the format conversion formula for converting the RGB data format into the HSV data format is as follows:
R'＝R/255 (4)
G'＝G/255 (5)
B'＝B/255 (6)
Cmax＝max(R',G',B') (7)
Cmin＝min(R',G',B') (8)
Δ＝Cmax-Cmin (9)
calculating R ', G ', B ' and C corresponding to each pixel according to the formulamax、CminAnd after delta, the values are respectively substituted into the following formulas to obtain H, S, V values:
Figure BDA0003380932690000111
Figure BDA0003380932690000112
V＝Cmax (12)
wherein, CmaxIs the maximum value of three component values of R ', G ' and B ', CminIs the minimum value of three component values of R ', G ' and B '.
Step 54: and comparing the second reference image with the second historical image, and calculating pixel difference data.
The pixel difference data includes a first chrominance difference value, a first saturation difference value and a first luminance difference value, and is calculated based on the second reference image with the data formats of H11-H1 n, S11-S1 n and V11-V1 n and the second history image with the data formats of H21-H2 n, S21-S2 n and V21-V2 n, as shown in fig. 6, the specific calculation steps are as follows:
step 541: and calculating the sum of the chromaticities of all pixels in the second reference image to obtain a first value, calculating the sum of the saturations of all pixels in the second reference image to obtain a second value, and calculating the sum of the luminances of all pixels in the second reference image to obtain a third value.
The chromaticity set of all pixels in the second reference image is H11-H1 n, the saturation set is S11-S1 n, the luminance set is V11-V1 n, the chromaticity of all pixels in the second reference image is added to obtain a first numerical value H1 ═ H11+ H12+ ·+ H1n, and the saturation of all pixels in the second reference image is added to obtain a second numerical value S1 ═ S11+ S12+ ·+ S1 n; the luminances of all pixels in the second reference image are added to obtain a third value V1 ═ V11+ V12+. + V1 n.
Step 542: and calculating the sum of the chromaticities of all pixels in the second historical image to obtain a fourth numerical value, calculating the sum of the saturations of all pixels in the second historical image to obtain a fifth numerical value, and calculating the sum of the luminances of all pixels in the second historical image to obtain a sixth numerical value.
The set of the chroma of all the pixels in the second history image is H21-H2 n, the set of the saturation is S21-S2 n, the set of the brightness is V21-V2 n, the chroma of all the pixels in the second history image is added to obtain a fourth numerical value H2, H2 is H21+ H22+ ·+ H2n, the saturation of all the pixels in the second history image is added to obtain a fifth numerical value S2, and S2 is S21+ S22+ ·+ S2 n; the luminances of all the pixels in the second history image are added to obtain a sixth value V2, V2 ═ V21+ V22+. + V2 n.
Step 543: and taking the difference value between the fourth numerical value and the first numerical value as a first chrominance difference value.
The fourth value H2 is subtracted from the first value H1 to obtain a first chrominance difference DcH, which is H2-H1, and it is understood that in the HSV data format, "H" represents the chrominance of the pixel, and the chrominance difference between the second history image and the second reference image can be obtained by calculating the difference between the fourth value H2 in the second history image and the first value H1 in the second reference image.
Step 544: and taking the difference between the fifth value and the second value as the first saturation difference.
Subtracting the fifth value S2 from the second value S1 yields a first saturation difference DcS, which is S2-S1, and it is understood that in HSV data format, "S" represents the saturation of a pixel and the saturation difference between the two images can be obtained by calculating the difference between the fifth value S2 in the second history image and the second value S1 in the second reference image.
Step 545: and taking the difference value between the sixth numerical value and the third numerical value as the first brightness difference value.
The sixth value V2 is subtracted from the third value V1 to obtain a first luminance difference DcV, which is V2-V1, and it is understood that in the HSV data format, "V" represents the luminance of a pixel and the luminance difference between the two images can be obtained by calculating the difference between the sixth value V2 in the second history image and the third value V1 in the second reference image.
Step 55: and acquiring a second deviation value based on the pixel difference value data and a preset deviation table.
The preset deviation table comprises a pixel change range and an adjustment value corresponding to the pixel change range, the pixel change range comprises a chrominance change range, a saturation change range and a brightness change range, and the adjustment value comprises a first adjustment value corresponding to the chrominance change range, a second adjustment value corresponding to the saturation change range and a third adjustment value corresponding to the brightness change range; specifically, the second deviation value includes a first sub-deviation, a second sub-deviation and a third sub-deviation, the above steps may obtain a first chrominance difference value, a first saturation difference value and a first luminance difference value, and the first chrominance difference value, the first saturation difference value and the first luminance difference value are respectively matched with a preset deviation table to obtain a first sub-deviation, a first sub-deviation and a third sub-deviation corresponding to the chrominance, the saturation and the luminance, as shown in fig. 7, the specific steps are as follows:
step 551: and matching the first chromaticity difference value with a preset deviation table to obtain a chromaticity variation range corresponding to the first chromaticity difference value, and further obtain a first sub-deviation.
The first sub-deviation is a first adjustment value corresponding to the chromaticity variation range, for example: the first chroma difference DcH is found to be 0.05, and based on the value, referring to the preset deviation table shown in fig. 8, it is found that the chroma difference 0.05 falls within the chroma variation range (0.03, 0.06), and the corresponding first adjustment value is 2, then the first sub-deviation is obtained to be 2, which means that the chroma parameter value in the default image balance table needs to be adjusted upwards by 2 units.
Step 552: and matching the first saturation difference value with a preset deviation table to obtain a chromaticity variation range corresponding to the first saturation difference value, and further obtain a second sub-deviation.
The second sub-deviation is a second adjustment value corresponding to the saturation change range, for example: the first saturation difference DcS is found to be 0.66, and based on the value, referring to the preset deviation table shown in fig. 8, it is found that the saturation difference 0.66 falls within the saturation variation range (0.5, 0.75), and the corresponding second adjustment value is 4, then the second sub-deviation is obtained to be 4, which means that the saturation parameter value in the default image equalization table needs to be adjusted upwards by 4 units.
Step 553: and matching the first brightness difference value with a preset deviation table to obtain a chromaticity variation range corresponding to the first brightness difference value, and further obtain a third sub-deviation.
The third sub-deviation is a third adjustment value corresponding to the luminance variation range, for example: the first brightness difference DcV is found to be-0.125, and based on the value, referring to the preset deviation table shown in fig. 8, it is found that the brightness difference-0.125 falls within the brightness variation range (-0.15, -0.1), and the corresponding third adjustment value is-6, then the third sub-deviation is obtained to be-6, which means that the brightness parameter value in the default image equalization table needs to be adjusted downward by 6 units.
It should be understood that, in this embodiment, only fig. 8 is taken as an example to describe the preset deviation table, and the preset deviation table may be obtained by testing according to an actual situation or set according to experience, and is not limited herein.
Step 56: and carrying out weighted summation on the second deviation value and the line length to obtain a first deviation value.
Correcting the second deviation value based on the line length of the transmission line, and performing weighted summation on the second deviation value and the line length to obtain a first deviation value; specifically, the first deviation value includes a fourth sub-deviation, a fifth sub-deviation and a sixth sub-deviation, and the first sub-deviation and the line length are weighted and summed respectively to obtain a fourth sub-deviation; carrying out weighted summation on the second sub-deviation and the line length to obtain a fifth sub-deviation; and carrying out weighted summation on the third sub-deviation and the line length to obtain a sixth sub-deviation.
In a specific embodiment, the matching gain multiple may be obtained by using a table of line length and preset gain multiple, then calculating a ratio of a product of the line length and the matching gain multiple to a preset value, and then adding the ratio to the second deviation value to obtain a first deviation value, as shown in the following formula:
DH＝Ht+X4*b (13)
DS＝St+X4*b (14)
DV＝Vt+X4*b (15)
wherein the line length is represented by X, the matching gain multiple is represented by b, the first and fourth sub-deviations are represented by Ht and DH, respectively, the second and fifth sub-deviations are represented by St and DS, respectively, and the third and sixth sub-deviations are represented by Vt and DV, respectively.
Further, the preset gain multiple table includes a plurality of line lengths and gain multiples corresponding to the line lengths, the gain multiples are in direct proportion to the line lengths of the transmission lines, the longer the line lengths are, the larger the gain multiples are, the specific gain multiple values can be obtained by querying the preset gain multiple table in a matching manner, the preset gain multiple table can be obtained according to a test, and no limitation is made here.
And 57: and adding the fourth sub-deviation, the fifth sub-deviation and the sixth sub-deviation to the chromaticity, the saturation and the brightness respectively to obtain new chromaticity, new saturation and new brightness.
The image balance table includes chroma, saturation and luminance, and after calculating the final first deviation value, the fourth sub-deviation, the fifth sub-deviation and the sixth sub-deviation are respectively added to the chroma, saturation and luminance in the image balance table to obtain new chroma, new saturation and new luminance, for example: if the saturation in the image equalization table is 80 and the fifth sub-deviation calculated is 2, then the two can be added to obtain a new saturation 82.
Step 58: and updating the image balance table by using the new chroma, the new saturation and the new brightness to obtain a new image balance table.
And updating the image balance table by using the new chromaticity, the new saturation and the new brightness, correspondingly replacing the numerical values of the chromaticity, the saturation and the brightness in the image balance table with the new chromaticity, the new saturation and the new brightness, and then storing the new image balance table into a FLASH of the AD chip so as to compensate the image to be compensated received from the camera equipment by using the new image balance table.
It is understood that the solutions provided in the present application are not limited to the embodiments shown in the above embodiments, and may be modified according to the specific application, for example: after the image in the RGB format or the YUV format is obtained, format conversion is not performed on the image, but a reference image in the same format (including the RGB format or the YUV format) is directly compared with a historical image to obtain pixel difference value data, format conversion processing is performed on the pixel difference value data to obtain pixel difference value data in the HSV format, and the pixel difference value data is matched with a preset deviation table, wherein subsequent processing steps are similar to those in the embodiment and are not repeated herein; or, the format of the numerical value in the preset deviation table is RGB, after the image in RGB format is obtained (if the obtained image is not in RGB format, it is converted into RGB format), the reference image is compared with the historical image to obtain pixel difference data, then the pixel difference data in RGB format is matched with the preset deviation table to obtain a corresponding deviation value, and then the deviation value is converted into a deviation value in HSV format, the subsequent processing steps are similar to those in the above embodiment, and are not repeated here; or, the format of the numerical value in the preset deviation table is YUV, after the image in the YUV format is acquired (if the acquired image is not in the YUV format, the image is converted into the YUV format), the reference image is compared with the historical image to acquire pixel difference data, then the pixel difference data in the YUV format is matched with the preset deviation table to acquire a corresponding deviation value, and then the deviation value is converted into a deviation value in the HSV format, and the subsequent processing steps are similar to those in the above embodiment and are not repeated here.
In the embodiment, a first reference image and a first historical image acquired from a camera device are subjected to format conversion to generate a second reference image and a second historical image in an HSV format, and HSV component values of the two images are compared and calculated to obtain a preliminary deviation value corresponding to chromaticity, saturation and brightness; then correcting the preliminary deviation value through the line length to obtain deviation values corresponding to the chromaticity, the saturation and the brightness in a default image balance table; finally, the deviation values are respectively added with the chromaticity, the saturation and the brightness in the default image balance table to complete the updating of the image balance table, and then the subsequent images are compensated according to the new image balance table, when the camera equipment is replaced, the current image balance table can be directly updated according to the reference images and the historical images acquired from the camera equipment, the self-adaptive adjustment of the image balance table can be realized, a large amount of manpower and material resources spent on the adjustment and verification of the image balance table are greatly saved, the cost is saved, and meanwhile, the universality is higher.
Referring to fig. 9, fig. 9 is a schematic structural diagram of an embodiment of a computer-readable storage medium 90 provided in the present application, where the computer-readable storage medium 90 is used for storing a computer program 91, and the computer program 91 is used for implementing the image compensation method in the foregoing embodiment when being executed by a processor.
The computer readable storage medium 90 may be a server, a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various media capable of storing program codes.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules or units is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and 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 units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are intended to be included within the scope of the present application.

Claims (13)

1. An image compensation method is applied to a hard disk video recorder, and the method comprises the following steps:
acquiring a first reference image and a first historical image shot by a camera device, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the camera device through a transmission line;
comparing the first reference image with the first historical image to obtain pixel difference data;
generating a first deviation value based on the pixel difference data;
and updating an image balance table in the hard disk video recorder based on the first deviation value to obtain a new image balance table, and compensating the image to be compensated received from the camera equipment by using the new image balance table.
2. The image compensation method of claim 1, wherein the step of generating a first deviation value based on the pixel difference data comprises:
acquiring a second deviation value based on the pixel difference value data and a preset deviation table, wherein the preset deviation table comprises a pixel change range and an adjusting value corresponding to the pixel change range;
and correcting the second deviation value based on the line length of the transmission line to obtain the first deviation value.
3. The image compensation method of claim 2, wherein the step of comparing the first reference image with the first history image to obtain pixel difference data comprises:
converting the first reference image and the first historical image into a second reference image and a second historical image respectively;
and comparing the second reference image with the second historical image, and calculating the pixel difference data.
4. The image compensation method of claim 3, wherein the pixel difference data comprises a first chrominance difference value, a first saturation difference value and a first luminance difference value, the pixel value of each pixel in the second reference image comprises chrominance, saturation and luminance, and the step of comparing the second reference image with the second history image to calculate the pixel difference data comprises:
calculating the sum of the chromaticities of all pixels in the second reference image to obtain a first numerical value, calculating the sum of the saturations of all pixels in the second reference image to obtain a second numerical value, and calculating the sum of the luminances of all pixels in the second reference image to obtain a third numerical value;
calculating the sum of the chromaticities of all pixels in the second historical image to obtain a fourth numerical value, calculating the sum of the saturations of all pixels in the second historical image to obtain a fifth numerical value, and calculating the sum of the luminances of all pixels in the second historical image to obtain a sixth numerical value;
taking a difference between the fourth numerical value and the first numerical value as the first chrominance difference value;
taking a difference between the fifth value and the second value as the first saturation difference;
and taking the difference value between the sixth numerical value and the third numerical value as the first brightness difference value.
5. The image compensation method according to claim 4, wherein the pixel variation range includes a chromaticity variation range, a saturation variation range, and a luminance variation range, the adjustment values include a first adjustment value corresponding to the chromaticity variation range, a second adjustment value corresponding to the saturation variation range, and a third adjustment value corresponding to the luminance variation range, the second bias value includes a first sub-bias, a second sub-bias, and a third sub-bias, and the step of obtaining the second bias value based on the pixel difference data and a preset bias table includes:
matching the first chromaticity difference value with the preset deviation table to obtain a chromaticity variation range corresponding to the first chromaticity difference value, and further obtaining a first sub-deviation, wherein the first sub-deviation is a first adjustment value corresponding to the chromaticity variation range;
matching the first saturation difference value with the preset deviation table to obtain a chromaticity variation range corresponding to the first saturation difference value, and further obtaining a second sub-deviation, wherein the second sub-deviation is a second adjustment value corresponding to the saturation variation range;
and matching the first brightness difference value with the preset deviation table to obtain a chromaticity variation range corresponding to the first brightness difference value, and further obtain a third sub-deviation, wherein the third sub-deviation is a third adjustment value corresponding to the brightness variation range.
6. The image compensation method of claim 2, wherein the step of correcting the second deviation value based on the line length of the transmission line to obtain a first deviation value comprises:
and carrying out weighted summation on the second deviation value and the line length to obtain the first deviation value.
7. The image compensation method of claim 6, wherein the step of weighted summing the second deviation value and the line length to obtain the first deviation value comprises:
obtaining a matching gain multiple by using the line length and a preset gain multiple table, wherein the preset gain multiple table comprises a plurality of line lengths and gain multiples corresponding to the line lengths;
calculating the ratio of the product of the line length and the matching gain multiple to a preset value;
and adding the ratio and the second deviation value to obtain the first deviation value.
8. The image compensation method of claim 1, wherein the first bias value comprises a fourth sub-bias, a fifth sub-bias, and a sixth sub-bias, and the image equalization table comprises chroma, saturation, and luminance;
adding the fourth sub-deviation, the fifth sub-deviation and the sixth sub-deviation to the chromaticity, the saturation and the brightness respectively to obtain a new chromaticity, a new saturation and a new brightness;
and updating the image equalization table by using the new chroma, the new saturation and the new brightness to obtain the new image equalization table.
9. The method of claim 1, wherein the hard disk recorder comprises an analog-to-digital conversion chip, the analog-to-digital conversion chip comprising a storage device, the method further comprising:
writing the new image equalization table into the storage device;
generating a compensation file based on the new balance table, and storing the compensation file in a preset directory;
after the power failure restart, judging whether the compensation file exists in the preset directory or not;
if so, analyzing the compensation file to obtain the new image balance table;
and if not, reading the new image balance table from the storage equipment.
10. The image compensation method of claim 9, wherein the hard disk video recorder further comprises a main control chip, and the step of acquiring the first reference image and the first history image captured by the image capturing device comprises:
acquiring the first reference image from the camera equipment by adopting the analog-to-digital conversion chip;
and processing the data output by the analog-to-digital conversion chip by adopting the main control chip to obtain the first historical image.
11. A hard disk video recorder comprising a memory and a processor connected to each other, wherein the memory is used for storing a computer program, which when executed by the processor is used for implementing the image compensation method of any one of claims 1 to 10.
12. An image compensation system, comprising an image capturing device and a hard disk video recorder connected to each other, wherein the hard disk video recorder is used for compensating an image output by the image capturing device, and the hard disk video recorder is the hard disk video recorder of claim 11.
13. A computer-readable storage medium for storing a computer program, the computer program, when being executed by a processor, is adapted to carry out the image compensation method of any one of claims 1 to 10.
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Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS62272749A (en) * 1986-05-21 1987-11-26 Canon Inc Still picture transmission equipment
JPH06217333A (en) * 1993-01-20 1994-08-05 Hitachi Denshi Ltd Color television camera system
CN1479529A (en) * 2002-07-26 2004-03-03 ���ǵ�����ʽ���� Device and method of colour compensation
CN101635694A (en) * 2008-07-21 2010-01-27 中兴通讯股份有限公司 Adaptive equalizer and method for adaptive equalization
CN101729846A (en) * 2008-11-03 2010-06-09 英特赛尔美国股份有限公司 Cable equalization system and method
CN102497528A (en) * 2011-11-30 2012-06-13 中国船舶重工集团公司第七○九研究所 Double twisted pairs-based monitoring system and method for transmitting and allocating RGBHV
CN102821265A (en) * 2012-08-09 2012-12-12 厦门狄耐克电子科技有限公司 Video transmission method and building video doorphone system
CN103167262A (en) * 2012-11-12 2013-06-19 浙江大华技术股份有限公司 Video signal attenuation equalization circuit and video signal process equipment and control device and method
CN104754292A (en) * 2013-12-31 2015-07-01 浙江大华技术股份有限公司 Method and device for determining parameters for compensation treatment of video signal
CN109461409A (en) * 2018-10-31 2019-03-12 北京小米移动软件有限公司 Screen display method and device
CN109917217A (en) * 2019-04-24 2019-06-21 中国科学院长春光学精密机械与物理研究所 Parameter compensation method, system and associated component for electromagnetic compatibility standard test
CN112995645A (en) * 2021-02-04 2021-06-18 维沃移动通信有限公司 Image processing method and device and electronic equipment

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS62272749A (en) * 1986-05-21 1987-11-26 Canon Inc Still picture transmission equipment
JPH06217333A (en) * 1993-01-20 1994-08-05 Hitachi Denshi Ltd Color television camera system
CN1479529A (en) * 2002-07-26 2004-03-03 ���ǵ�����ʽ���� Device and method of colour compensation
CN101635694A (en) * 2008-07-21 2010-01-27 中兴通讯股份有限公司 Adaptive equalizer and method for adaptive equalization
CN101729846A (en) * 2008-11-03 2010-06-09 英特赛尔美国股份有限公司 Cable equalization system and method
CN102497528A (en) * 2011-11-30 2012-06-13 中国船舶重工集团公司第七○九研究所 Double twisted pairs-based monitoring system and method for transmitting and allocating RGBHV
CN102821265A (en) * 2012-08-09 2012-12-12 厦门狄耐克电子科技有限公司 Video transmission method and building video doorphone system
CN103167262A (en) * 2012-11-12 2013-06-19 浙江大华技术股份有限公司 Video signal attenuation equalization circuit and video signal process equipment and control device and method
CN104754292A (en) * 2013-12-31 2015-07-01 浙江大华技术股份有限公司 Method and device for determining parameters for compensation treatment of video signal
CN109461409A (en) * 2018-10-31 2019-03-12 北京小米移动软件有限公司 Screen display method and device
CN109917217A (en) * 2019-04-24 2019-06-21 中国科学院长春光学精密机械与物理研究所 Parameter compensation method, system and associated component for electromagnetic compatibility standard test
CN112995645A (en) * 2021-02-04 2021-06-18 维沃移动通信有限公司 Image processing method and device and electronic equipment

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