CN114245004B

CN114245004B - Image compensation method, system, hard disk video recorder and readable storage medium

Info

Publication number: CN114245004B
Application number: CN202111433278.4A
Authority: CN
Inventors: 刘泳金; 冯亮
Original assignee: Zhejiang Dahua Technology Co Ltd
Current assignee: Zhejiang Dahua Technology Co Ltd
Priority date: 2021-11-29
Filing date: 2021-11-29
Publication date: 2023-06-23
Anticipated expiration: 2041-11-29
Also published as: CN114245004A

Abstract

The application discloses an image compensation method, an image compensation 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 image pickup equipment, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the image pickup 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; 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 an image to be compensated received from the image pickup device by using the new image balance table. By means of the method, the self-adaptive compensation of the image can be achieved.

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, an image compensation system, a hard disk video recorder, and a readable storage medium.

Background

After the camera is connected to a hard disk video recorder (Digital Video Recorder, DVR), in the process that the camera transmits collected image data to the DVR device through a Coaxial Cable (Coaxial Cable) or a Twisted Pair (TP), parameter information (including tone, saturation and brightness) of the image is attenuated to different degrees along with the length of the transmission Cable, so that distortion phenomena such as color fading or brightness darkening of the image occur; although the current DVR device can perform attenuation compensation on the image according to the image balancing table, the image balancing table is set according to the standard camera, so that only the image collected by the standard camera can be adjusted in the image adjusting process, and the situation that the image display is distorted/abnormal may occur when the images collected by the cameras other than the standard camera are adjusted, at this time, if the image is adjusted for multiple times or parameters in the image balancing table are adjusted, a great amount of manpower and material resources are required to be consumed for performing result verification, and the cost is high.

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 problems, 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 image pickup equipment, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the image pickup 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; 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 an image to be compensated received from the image pickup device by using the new image balance table.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: there is provided a hard disk recorder comprising a memory and a processor connected to each other, wherein the memory is adapted to store a computer program which, when executed by the processor, is adapted to carry out the image compensation method of the above-mentioned technical solution.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: an image compensation system is provided, the image compensation system comprises an image pickup device and a hard disk video recorder which are connected with each other, the hard disk video recorder is used for compensating the image output by the image pickup device, and the hard disk video recorder is the hard disk video recorder in the technical scheme.

In order to solve the technical problems, another technical scheme adopted by the application is as follows: there is provided a computer readable storage medium for storing a computer program for implementing the image compensation method of the above-mentioned technical solution when being executed by a processor.

Through above-mentioned scheme, the beneficial effect of this application is: firstly, acquiring a first reference image and a first historical image shot by image pickup equipment, wherein the first historical image is an image generated by the first reference image transmitted to a hard disk video recorder by the image pickup equipment through a transmission line, namely the first historical image is an image possibly having 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 value data between the unattenuated image and the attenuated image, and generating a first deviation value by using the pixel difference value data; then updating the image balancing table by using the first deviation value to obtain a new image balancing table, and compensating the image to be compensated transmitted by the camera equipment by using the new image balancing table; by matching the hard disk video recorder with the camera equipment, the image balancing table can be adaptively updated in real time, and the updated image balancing table is utilized to compensate the subsequently received image, so that the display distortion or abnormality of the image is improved, the quality of the image is improved, and the accuracy of subsequent operations (such as image detection, identification or tracking) is further improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. Wherein:

FIG. 1 is a schematic diagram of an embodiment of an image compensation system provided herein;

FIG. 2 is a schematic diagram of an embodiment of a hard disk recorder according to the present application;

FIG. 3 is a schematic diagram of the connection of the image capturing 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 herein;

FIG. 5 is a flowchart of another embodiment of an image compensation method provided herein;

FIG. 6 is a flow chart of calculating pixel difference data provided herein;

FIG. 7 is a schematic flow chart of obtaining a second deviation value provided in 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 is described in further detail below with reference to the drawings and examples. It is specifically noted that the following examples are only for illustration of the present application, but do not limit the scope of the present application. Likewise, the following embodiments are only some, but not all, of the embodiments of the present application, and all other embodiments obtained by one of ordinary skill in the art without making any inventive effort 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 may be included in at least one embodiment of the application. The appearances of such phrases 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. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

It should be noted that the terms "first," "second," and "third" are used herein for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying a number of technical features being indicated. Thus, a feature defining "a first", "a second", and "a third" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may 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, fig. 2 is a schematic structural diagram of an embodiment of a hard disk video recorder provided in the present application, and the image compensation system 1 includes an image capturing device 10 and a hard disk video recorder 20 connected to each other, where the hard disk video recorder 20 is used for compensating an image output by the image capturing device 10, the image capturing device 10 may be a camera, and the hard disk video recorder 20 is a DVR device.

The hard disk recorder 20 comprises a memory 21 and a processor 22 interconnected, the memory 21 being adapted to store a computer program which, when executed by the processor 22, is adapted to carry out an image compensation method provided herein, which will be described in more detail below.

In a specific embodiment, referring to fig. 2 and 3 in combination, the image capturing apparatus 10 may be connected to the hard disk recorder 20 through a coaxial cable/twisted pair cable for data transmission, and the image capturing apparatus 10 may include an image Sensor (Sensor) 11 and an image signal processing module (Image Signal Processing, ISP) 12, the image Sensor 11 being configured to collect an image and transmit the image to the image signal processing module 12; the image signal processing module 12 processes the image output from the image sensor 11, converts the processed image into YUV data, digital-to-analog converts the YUV data into analog data, and transmits the analog data to the hard disk recorder 20 via the coaxial cable/twisted pair cable.

The hard disk video recorder 20 further comprises an analog-to-digital conversion chip (Analogue to Digital, AD) 23, the processor 22 comprises a main control chip 221, the analog-to-digital conversion chip 23 is used for receiving the analog data output by the image signal processing module 12, performing analog-to-digital conversion processing on the analog data to convert the analog data into digital data, and then transmitting the digital data to the main control chip 221 by adopting a BT656 protocol; the main control chip 221 includes a video capture module 2211, a video preprocessing 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 preprocessing module 2212, and the video preprocessing module 2212 is configured to perform video preprocessing on the data, and then transmit the processed image data to the video display module 2213 for image display at a View Object (VO), where the video preprocessing may include operations such as image zooming in/out, sharpening or filtering.

Further, the analog-to-digital conversion chip 23 may further include a storage device (not shown in the figure), for example: the FLASH memory (FLASH) can compensate the image through an image balancing table stored in the FLASH, compensate attenuation generated in the transmission process of the image, and improve the display distortion or abnormal situation of the image.

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/CVI 1080P) and the cable type (coaxial cable/twisted pair cable) of the transmission cable, and then find the corresponding camera system according to the camera type and cable type in the following table 1, for example: the camera type of the accessed camera is CVI720P, and the cable type is a coaxial cable, so that the corresponding camera system TCVI720P can be found.

Table 1 camera system and corresponding cable type

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 also identify and determine the attenuation values generated by the current image and the current day/night, and then find 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 camera system as TCVI720P as an example, if: at present, a corresponding daytime attenuation table TDayDataC720 (shown in table 3) can be found in daytime, then a corresponding line length is found in table 3 according to the attenuation value generated by the identified current image, then a saturation value, a tone value and a brightness value corresponding to the line length are found in a saturation table, a tone table and a brightness table (shown in table 4), and the saturation value, the tone value and the brightness value are stored in a FLASH of the analog-to-digital conversion chip 23, so that the saturation, the tone and the brightness of the image are adjusted, and the compensation processing of the image is completed.

Table 2 camera system and corresponding attenuation table

TABLE 3 line lengths and corresponding attenuation ranges

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 will be appreciated that there may be differences in the image received by the analog-to-digital conversion chip 23 for different types of image capturing apparatuses 10 that are accessed, for example: the image color is too pale, the color tone is too high or the color is too bright, etc., the image effect expected by the user is not achieved, and the image balance table stored by default in the analog-digital conversion chip 23 is relatively fixed, so that when other image pickup devices are accessed, the saturation, the color tone, the brightness, etc. of the processed image can be kept consistent with that of the standard camera; the image compensation method provided by the application can automatically adjust the existing default image balance table according to the accessed image pickup equipment to generate the optimal image balance table suitable for the current image pickup equipment, so that the optimal image attenuation compensation processing is realized, and the numerical requirements of different saturation, hue and brightness required by different image pickup equipment can be adapted, and the image compensation method is described in detail below.

Referring to fig. 4, fig. 4 is a flowchart of an embodiment of an image compensation method provided in the present application, where the method includes:

Step 41: a first reference image and a first history image captured by an image capturing apparatus are acquired.

The method comprises the steps of carrying out compensation processing on an image to be adjusted so that an image generated after compensation can reach an image effect presented by a first reference image, so that in order to ensure that the first reference image has referential, certain standard exists when the first reference image is selected, and the first reference image is consistent with the external environment where the image to be adjusted is positioned; 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, the first reference image may be obtained from the image capturing apparatus by using an AD chip, where the AD chip may be communicatively connected to the image capturing apparatus by using an RS485 communication protocol in a high-definition composite video interface (High Definition Composite Video Interface, HDCVI) or other wireless communication methods, and the transmission process of transmitting the image by this method is digital signal transmission, so that the problem of signal attenuation does not occur, that is, the AD chip may directly obtain a frame of unattenuated first reference image from the image capturing apparatus.

Further, the first historical image is an image generated by transmitting the first reference image to the DVR device through a transmission line by the camera device, transmission attenuation is generated when the acquired first reference image is transmitted through the transmission line, and at the moment, the first historical image acquired by the DVR device is the attenuated first reference image; specifically, the main control chip in the DVR device is used to process the data output by the AD chip to obtain a first history image, referring to fig. 3, the video preprocessing module 2212 may process the image, the processed image may generate a change in image style, and the processed image may not be compared with the first reference image, so as to affect the accuracy of the pixel difference data obtained by the subsequent comparison, so that the image collected by the video collecting module 2211 from the AD chip 23 is used as the first history image to avoid the image difference generated by the image processing.

Step 42: and comparing the first reference image with the first historical image to obtain pixel difference data.

The image has a plurality of pixels, the number of which is related to the resolution to which the image corresponds, for example: an image with a resolution of 250 x 360 has 250 x 360 pixels, each with a respective parameter value, for example: and (3) carrying out corresponding comparison operation on the parameter values corresponding to the pixels in the first reference image and the first historical image by using the saturation, the tone or the brightness and the like, so as to obtain pixel difference value data between the two images.

Step 43: a first offset value is generated based on the pixel difference data.

After the pixel difference data is obtained, the following steps may be employed 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 which is currently corresponding to the pixel change range, namely a second deviation value, can be obtained by matching the pixel difference value data with the pixel change range in the preset deviation table, wherein the second deviation value can represent the deviation value between the parameter in the image balance table to be updated currently and the target parameter to be adjusted. It may be understood that the pixel difference data may include parameter difference data in terms of saturation, hue, brightness, etc., the preset deviation table may also include pixel variation ranges and adjustment values corresponding to parameters such as saturation, hue, brightness, etc., and the obtained second deviation value may also be a plurality of deviation values corresponding to parameters such as saturation, hue, brightness, etc.

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: the method comprises the steps of reading the values of parameters such as the saturation, the chromaticity or the brightness of a current image, sequentially adjusting the deviation values of the parameters such as the saturation, the chromaticity or the brightness of the image, for example, adjusting the saturation deviation of the image by 0.5, reading the parameter value corresponding to the saturation of the image after deviation adjustment, calculating to obtain the corresponding saturation change range when the saturation deviation is 0.5 according to the parameter value corresponding to the saturation after adjustment and the parameter value corresponding to the saturation before adjustment, adjusting the magnitude of the deviation value in a numerical increment or decrement mode, performing deviation adjustment on the saturation until the saturation parameter is tested, and testing the rest parameters in the same mode.

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, and after the second deviation value is obtained according to the preset deviation table and the pixel difference value data, the second deviation value is corrected by referring to the line length to obtain a more accurate first deviation value in order to further ensure the accuracy of the deviation value.

Step 44: 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 an image to be compensated received from the image pickup device by using the new image balance table.

After updating the current image balance table to be adjusted 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 unexpected situations; specifically, a new image equalization table may be stored in the FLASH of the 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 equalization table may be utilized 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 the compensation file is stored under a preset directory; after the DVR equipment is powered off and restarted, judging whether a compensation file exists in a preset directory; if the compensation file exists in the preset catalog, the compensation file can be analyzed to obtain a new image balance table; if the compensation file does not exist under the preset directory, a new image balancing table can be read from the storage device, and then the image to be compensated is compensated based on the new image balancing table.

In other embodiments, after the DVR device is powered off and restarted, there may be a case of replacing the image capturing device, at this time, the default image balance table before updating may be directly read, then the adaptive update is performed based on the default image balance table, and the image is adjusted by referring to the newly generated image balance table. It can be understood that after updating the default image balance table to generate a new image balance table, the default image balance table before updating is still reserved, so that the default image balance table can be invoked for updating after the camera equipment is replaced subsequently; specifically, the new image balance table and the default image balance table obtained after updating 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 the 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 acquired first, where the first history image is an image generated by transmitting the first reference image to a hard disk video recorder through a transmission line by the image capturing device, that is, the first history image is an image that 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 value data between the unattenuated image and the attenuated image, and generating a first deviation value by using the pixel difference value data; then updating the image balancing table by using the first deviation value to obtain a new image balancing table, and compensating the image to be compensated transmitted by the camera equipment by using the new image balancing table; the image balancing table can be adaptively updated in real time through the cooperation of the hard disk video recorder and the camera equipment, and the updated image balancing table is utilized to compensate the subsequently received image, so that the display distortion or abnormality of the image is improved, the quality of the image is improved, and the accuracy of subsequent operations (such as image detection, identification or tracking) is further improved; the line length of the transmission line is used as a factor affecting the image balance table to adjust the numerical value in the image balance table, so that the numerical value in the image balance table is closer to an actual application scene, and the accuracy of compensating the subsequent image by using the updated image balance table is further improved.

Referring to fig. 5, fig. 5 is a flowchart of another embodiment of an image compensation method provided in the present application, where the method includes:

step 51: a first reference image and a first history image captured by an image capturing apparatus are acquired.

This step is the same as step 41 in the above embodiment, and will not be described again.

The first reference image and the first history image are images in a YUV format, 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 an HSV format, which is shown in steps 52-53.

Step 52: and performing format conversion processing on the first reference image and the first historical image respectively to obtain a third reference image and a third historical image.

When the ISP module of the image pickup equipment receives an image acquired by the image sensor, the image can be converted into a YUV data format, and then the first reference image and the first historical image acquired from the image pickup equipment are in the YUV data format, format conversion processing is respectively carried out on the first reference image and the first historical image, the YUV data format is converted into an RGB data format, and a third reference image and a third historical image in the RGB data format are obtained.

Specifically, each pixel in the image in the YUV data format corresponds to Y, U, V three component values, respectively, "Y" represents luminance, "U" and "V" represent chromaticity, and the color and saturation of the image are represented by such 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 conversion between the YUV data format and the RGB data format can be achieved by a corresponding format conversion formula, where the format conversion formula 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 Y, U, V component value in each pixel in the first reference image and the first history image is substituted 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 first reference image in the data format of Y11-Y1 n, U11-U1 n and V11-V1 n can be converted into the third reference image in the data format of R11-R1 n, G11-G1 n and B11-B1 n by using the format conversion formula by taking n pixels in each of the first reference image and the first history image as an example, and the first history image in the data format of Y21-Y2 n, U21-U2 n and V21-V2 n can be converted 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 historical image to obtain a second reference image and a second historical image.

After the image in the RGB data format is obtained, converting the RGB data format of the image into an HSV data format, wherein the image in the HSV data format can comprise H, S, V three component values, wherein 'H' represents the chromaticity of a pixel, 'S' represents the saturation of the pixel, '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 to R2n, G21 to G2n, B21 to B2n in the third history image are converted into H21 to H2n, S21 to S2n, V21 to V2n.

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)

C _max ＝max(R',G',B') (7)

C _min ＝min(R',G',B') (8)

Δ＝C _max -C _min (9)

r ', G', B ', C' corresponding to each pixel are calculated according to the formula _max 、C _min And after delta, the H, S, V value is obtained by substituting the following formulas:

V＝C _max (12)

wherein C is _max Is the maximum value of three component values R ', G ', B ', C _min Is the minimum of the three component values of R ', G ', 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 saturation difference, and a first luminance difference, and is calculated based on the second reference images with the data formats of H11 to H1n, S11 to S1n, and V11 to V1n and the second history images with the data formats of H21 to H2n, S21 to S2n, and V21 to V2n, 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 numerical value, calculating the sum of the saturation of all pixels in the second reference image to obtain a second numerical value, and calculating the sum of the brightnesses of all pixels in the second reference image to obtain a third numerical value.

The method comprises the steps that a set of chromaticities of all pixels in a second reference image is H11-H1 n, a set of saturation is S11-S1 n, a set of brightness is V11-V1 n, the chromaticities of all pixels in the second reference image are added to obtain a first numerical value H1=H11+H2+ & gt H1n, and the saturation of all pixels in the second reference image is added to obtain a second numerical value S1=S11+S12+ & gt S1n; the brightness of all pixels in the second reference image is added to obtain a third value v1=v11+v12+ & gt V1n.

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 saturation of all pixels in the second historical image to obtain a fifth numerical value, and calculating the sum of the brightnesses of all pixels in the second historical image to obtain a sixth numerical value.

The set of the chromaticities of all pixels in the second historical image is H21-H2 n, the set of the saturation is S21-S2 n, the set of the brightness is V21-V2 n, the chromaticities of all pixels in the second historical image are added to obtain a fourth numerical value H2, H2=H2+H2+ & gt, and the saturation of all pixels in the second historical image is added to obtain a fifth numerical value S2, S2=S21+S22+ & gt S2n; the brightness of all pixels in the second history image is added to obtain a sixth value V2, v2=v21+v22+ + V2n.

Step 543: and taking the difference value between the fourth numerical value and the first numerical value as a first color difference value.

The fourth value H2 is subtracted from the first value H1 to obtain a first chrominance difference DcH =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 two images 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 a first saturation difference.

The fifth value S2 is subtracted from the second value S1 to obtain a first saturation difference DcS =s2-S1, and it is understood that, in the HSV data format, "S" represents the saturation of the 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 between the sixth value and the third value as a first brightness difference.

The sixth value V2 is subtracted from the third value V1 to obtain a first luminance difference DcV =v2-V1, and it can be understood that, in the HSV data format, "V" represents the luminance of the 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, wherein the pixel change range comprises a chromaticity change range, a saturation change range and a brightness change range, and the adjustment value comprises a first adjustment value corresponding to the chromaticity 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, and the first color difference value, the first saturation difference value and the first luminance difference value can be obtained by the above steps, and the first color 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 color, the saturation and the luminance, respectively, 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 obtaining a first sub-deviation.

The first sub-deviation is a first adjustment value corresponding to a chromaticity variation range, for example: the first chrominance difference DcH is obtained to be 0.05, the preset deviation table shown in fig. 8 is referred to based on the value, if the chrominance difference 0.05 is found to be within the chrominance variation range (0.03,0.06) and the corresponding first adjustment value is 2, the first sub-deviation is obtained to be 2, which means that the chrominance parameter value in the default image balancing 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 obtaining a second sub-deviation.

The second sub-deviation is a second adjustment value corresponding to the saturation variation range, for example: the first saturation difference DcS is obtained to be 0.66, and based on the value, the preset deviation table shown in fig. 8 is referred to, and if the saturation difference 0.66 is found to be within the saturation change range (0.5, 0.75), and the corresponding second adjustment value is 4, the second sub-deviation is obtained to be 4, which means that the saturation parameter value in the default image balance 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 obtaining a third sub-deviation.

The third sub-deviation is a third adjustment value corresponding to the brightness variation range, for example: the first luminance difference DcV is found to be-0.125, and based on the value, the preset deviation table shown in fig. 8 is referred to, and when the luminance difference-0.125 is found to be within the luminance change range (-0.15, -0.1), the corresponding third adjustment value is-6, the third sub-deviation is obtained to be-6, which means that the luminance parameter value in the default image balance table needs to be adjusted downward by 6 units.

It should be understood that, in this embodiment, the preset deviation table is only illustrated in fig. 8, and the preset deviation table may be obtained by testing according to actual situations or may be empirically set, which 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 carrying out weighted summation on the second deviation value and the line length to obtain a first deviation value; specifically, the first deviation value comprises a fourth sub-deviation, a fifth sub-deviation and a sixth sub-deviation, and the first sub-deviation and the line length are respectively weighted and summed to obtain the 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 line length and the preset gain multiple table may be used to obtain a matching gain multiple, then the ratio of the product of the line length and the matching gain multiple to the preset value is calculated, and then the ratio is added to the second deviation value to obtain the first deviation value, as shown in the following formula:

DH＝Ht+X4*b (13)

DS＝St+X4*b (14)

DV＝Vt+X4*b (15)

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 searching the preset gain multiple table, the preset gain multiple table can be obtained according to the test, and the preset gain multiple table is not limited herein.

Step 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 a new chromaticity, a new saturation and a new brightness.

The image balancing table includes chromaticity, saturation and brightness, and after the final first deviation value is obtained by calculation, the fourth sub-deviation, the fifth sub-deviation and the sixth sub-deviation are added to the chromaticity, the saturation and the brightness in the image balancing table respectively to obtain a new chromaticity, a new saturation and a new brightness, for example: the saturation in the image equalization table is 80 and the calculated fifth sub-deviation is 2, then the two can be added to get the new saturation 82.

Step 58: and updating the image balancing table by using the new chromaticity, the new saturation and the new brightness to obtain a new image balancing table.

Updating the image balancing 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 balancing table with the new chromaticity, the new saturation and the new brightness, and then storing the new image balancing table into the FLASH of the AD chip so as to compensate the image to be compensated received from the image pickup device by using the new image balancing table.

It will be appreciated that the solution provided in the present application is not limited to the embodiments described above, but may be modified according to the needs of a specific application, for example: after the image in the RGB format or the YUV format is obtained, the image is not subjected to format conversion, but the reference image in the same format (including the RGB format or the YUV format) is directly compared with the history image to obtain pixel difference data, then the pixel difference data is subjected to format conversion processing to obtain the pixel difference data in the HSV format, and then the pixel difference data is matched with a preset deviation table, and the subsequent processing steps are similar to those in the above embodiment and are not repeated herein; or, the format of the numerical value in the preset deviation table is RGB, after the image in the RGB format is obtained (if the obtained image is not in the RGB format, the obtained image is converted into the RGB format), the reference image is compared with the history image to obtain pixel difference data, then the pixel difference data in the RGB format is matched with the preset deviation table to obtain a corresponding deviation value, the deviation value is converted into the deviation value in the HSV format, and the subsequent processing steps are similar to those in the above embodiment and are not repeated herein; or, the numerical value format in the preset deviation table is YUV, after the image in YUV format is obtained (if the obtained image is not in YUV format, the obtained image is converted into YUV format), the reference image is compared with the history image to obtain pixel difference data, then the pixel difference data in YUV format is matched with the preset deviation table to obtain a corresponding deviation value, the deviation value is converted into the deviation value in HSV format, and the subsequent processing steps are similar to those in the above embodiment and are not repeated herein.

In the embodiment, format conversion is performed on a first reference image and a first historical image obtained from image pickup equipment, a second reference image and a second historical image in an HSV format are generated, HSV component values of the two images are compared and calculated, and preliminary deviation values corresponding to chromaticity, saturation and brightness are obtained; correcting the preliminary deviation value through the line length to obtain a deviation value corresponding to chromaticity, saturation and brightness in a default image balance table; and finally, the deviation value is respectively added with the chromaticity, the saturation and the brightness in the default image balancing table to finish updating the image balancing table, so that the subsequent image is compensated according to the new image balancing table, the current image balancing table can be directly updated according to the reference image and the historical image acquired from the image capturing equipment when the image capturing equipment is replaced, the self-adaptive adjustment of the image balancing table can be realized, a large amount of manpower and material resources spent on adjusting and verifying the image balancing table are greatly saved, the cost is saved, and the image balancing table has higher universality.

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 to store a computer program 91, and the computer program 91, when executed by a processor, is used to implement the image compensation method in the above embodiment.

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 (Random Access Memory, RAM), a magnetic disk, or an optical disk, etc. various media capable of storing program codes.

In the several embodiments provided in the present application, it should be understood that the disclosed methods and apparatuses may be implemented in other manners. For example, the above-described device embodiments are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist alone physically, or two or more units may be integrated into one unit. The integrated units may be implemented in hardware or in software functional units.

The foregoing description is only exemplary embodiments of the present application and is not intended to limit the scope of the present application, and all equivalent structures or equivalent processes using the descriptions and the drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the present application.

Claims

1. An image compensation method, applied to a hard disk video recorder, comprising:

acquiring a first reference image and a first historical image shot by image pickup equipment, wherein the first historical image is an image generated by the first reference image transmitted to the hard disk video recorder by the image pickup 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;

updating an image balancing table in the hard disk video recorder based on the first deviation value to obtain a new image balancing table, and compensating an image to be compensated received from the image pickup device by utilizing the new image balancing table;

the image balancing table before updating comprises image parameters, wherein the image parameters comprise saturation, tone and brightness;

Before the acquiring the first reference image and the first history image captured by the image capturing apparatus, the method further includes:

judging whether the current time is in the daytime or the night;

based on the judging result and the camera system of the current camera connected to the hard disk video recorder, determining a corresponding attenuation table, a saturation table, a tone table and a brightness table from all pre-stored tables;

determining the line length of a current transmission line based on the attenuation value of the current image shot by the current camera and the attenuation table;

determining the saturation, the hue, and the brightness based on the line length of the current transmission line, the saturation table, the hue table, and the brightness table;

the pixel difference data comprises a first color difference value, a first saturation difference value and a first brightness difference value; the generating a first deviation value based on the pixel difference data includes:

respectively matching the first chroma difference value, the first saturation difference value and the first brightness difference value with a preset deviation table to obtain a first sub-deviation, a second sub-deviation and a third sub-deviation which respectively correspond to the chroma, the saturation and the brightness;

carrying out weighted summation on the first sub-deviation and the line length 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; carrying out weighted summation on the third sub-deviation and the line length to obtain a sixth sub-deviation;

The image equalization table includes the chromaticity, the saturation, and the luminance; the updating of the image balancing table in the hard disk video recorder based on the first deviation value to obtain a new image balancing table comprises the following steps:

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 balancing table by using the new chromaticity, the new saturation and the new brightness to obtain the new image balancing table.

2. The image compensation method of claim 1, wherein the step of generating a first offset 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 adjustment 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 historical image to obtain pixel difference data comprises:

Converting the first reference image and the first history image into a second reference image and a second history image respectively;

comparing the second reference image with the second historical image, and calculating the pixel difference value data.

4. The image compensation method of claim 3 wherein the pixel difference data comprises a first color 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 a chromaticity, a saturation, and a luminance, the step of comparing the second reference image with the second historical image, and calculating 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 saturation of all pixels in the second reference image to obtain a second numerical value, and calculating the sum of the brightness 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 saturation of all pixels in the second historical image to obtain a fifth numerical value, and calculating the sum of the brightness of all pixels in the second historical image to obtain a sixth numerical value;

Taking the difference between the fourth value and the first value as the first color difference;

taking the 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 deviation value includes a first sub-deviation, a second sub-deviation, and a third sub-deviation, and the step of acquiring a second deviation value based on the pixel difference data and a preset deviation 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 obtaining 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 according to 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 includes:

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 weighting and summing the second bias value and the line length to obtain the first bias value comprises:

obtaining a matched 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 to the second deviation value to obtain the first deviation value.

8. The image compensation method of claim 1, wherein the hard disk recorder comprises an analog-to-digital conversion chip, the analog-to-digital conversion chip comprising a memory device, the method further comprising:

writing the new image balance table into the storage device;

generating a compensation file based on the new balance table, and storing the compensation file under a preset directory;

after restarting after power failure, judging whether the compensation file exists under the preset directory;

if yes, analyzing the compensation file to obtain the new image balancing table;

if not, the new image balancing table is read from the storage device.

9. The image compensation method according to claim 8, 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 shot by the image pickup apparatus comprises:

acquiring the first reference image from the image pickup device 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.

10. A hard disk recorder comprising a memory and a processor connected to each other, wherein the memory is adapted to store a computer program for implementing the image compensation method according to any of claims 1-9 when executed by the processor.

11. An image compensation system comprising an image pickup apparatus and a hard disk recorder connected to each other, the hard disk recorder being for compensating an image output from the image pickup apparatus, the hard disk recorder being the hard disk recorder according to claim 10.

12. A computer readable storage medium storing a computer program, characterized in that the computer program, when being executed by a processor, is adapted to implement the image compensation method of any one of claims 1-9.