CN113658431B - Traffic image data processing system - Google Patents
Traffic image data processing system Download PDFInfo
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- CN113658431B CN113658431B CN202110927261.8A CN202110927261A CN113658431B CN 113658431 B CN113658431 B CN 113658431B CN 202110927261 A CN202110927261 A CN 202110927261A CN 113658431 B CN113658431 B CN 113658431B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/56—Provisioning of proxy services
- H04L67/565—Conversion or adaptation of application format or content
- H04L67/5651—Reducing the amount or size of exchanged application data
Abstract
The invention provides a traffic image data processing system, which is characterized by comprising the following components: the traffic image acquisition module is used for acquiring a traffic original image, the traffic image transmission module is used for transmitting the traffic original image to the traffic image processing module, the traffic image processing module is used for optimizing the traffic original image to obtain a traffic optimized image, the traffic image storage module is used for storing the traffic optimized image, and the traffic image acquisition module, the traffic image transmission module, the traffic image processing module and the traffic image storage module are connected in a wired or wireless mode. The invention realizes the rapid optimization of the traffic image, and reduces the occupied space of a single traffic image on the premise of ensuring the traffic image to be visually indistinguishable.
Description
Technical Field
The invention relates to the field of image processing, in particular to a traffic image data processing system.
Background
With the popularization of intelligent transportation and the improvement of the definition of traffic images, the required storage space is larger and larger, and the speed is also reduced when the high-definition traffic images are read, so that the subsequent processing including transmission and identification is influenced.
In the prior art, the image compression technology is used for reducing the occupied space of the image, but the image quality is reduced along with the increase of the compression ratio, so that the requirement of image compression at a low bit rate cannot be met. Based on the characteristics of a human eye vision system, the invention realizes the rapid optimization of the traffic image aiming at the field of the traffic image, and reduces the occupied space of a single traffic image on the premise of ensuring no difference in the traffic image vision.
Disclosure of Invention
In view of the above problems, the present invention is directed to a traffic image data processing system.
The purpose of the invention is realized by adopting the following technical scheme:
a traffic image data processing system, comprising: the traffic image acquisition module is used for acquiring a traffic original image, the traffic image transmission module is used for transmitting the traffic original image to the traffic image processing module, the traffic image processing module is used for optimizing the traffic original image to obtain a traffic optimized image, the traffic image storage module is used for storing the traffic optimized image, and the traffic image acquisition module, the traffic image transmission module, the traffic image processing module and the traffic image storage module are connected in a wired or wireless mode.
The invention has the beneficial effects that: the traffic image is quickly optimized, and the occupied space of a single traffic image is reduced on the premise of ensuring no difference in traffic image vision.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
FIG. 1 is a block diagram of the framework of the present invention;
fig. 2 is a frame structure diagram of a traffic image processing module according to the present invention.
Reference numerals:
a traffic image capturing module 1, a traffic image transmitting module 2, a traffic image processing module 3, a traffic image storing module 4, a stationary detection step 31, a pixel search step 32, and a band selection step 33.
Detailed Description
The invention is further described in connection with the following application scenarios.
Referring to fig. 1, the traffic image data processing system of the present embodiment is characterized by including: the traffic image acquisition module 1 is used for capturing a traffic original image, the traffic image transmission module 2 is used for transmitting the traffic original image to the traffic image processing module 3, the traffic image processing module 3 is used for optimizing the traffic original image to obtain a traffic optimized image, the traffic image storage module 4 is used for storing the traffic optimized image, and the traffic image acquisition module 1, the traffic image transmission module 2, the traffic image processing module 3 and the traffic image storage module 4 are connected in a wired or wireless mode.
The traffic image capturing module 1 captures a traffic original image by using a camera.
The traffic image storage module 2 adopts a computer readable storage medium mode for storage and/or cloud storage.
Referring to fig. 2, the traffic image processing module 3 rearranges and selects the band sequence of the original traffic image, the selection process includes a stationary detection step 31, a pixel search step 32 and a band selection step 33 to obtain the traffic rearranged image, the stationary detection step 31 detects the stationary performance of the traffic rearranged image, the stationary coefficient of each band of the traffic rearranged image is measured and calculated, and the stationary coefficient standard values are set for comparison, the pixel search step 32 performs algorithm search on the traffic rearranged image which has completed the stationary detection step 31 to find out similar pixels in a similar neighborhood, and the band selection step 33 performs selective highlighting on the similar pixels to obtain the traffic optimized image.
Preferably, the measuring and calculating of the stationary coefficient of each waveband of the traffic rearrangement image comprises measuring and calculating the correlation coefficient of the spectrum vector of the original traffic image and the spectrum vector of the traffic rearrangement image, and representing the stationary performance of the two spectrum vectors through the measuring and calculating result, wherein the customized measuring and calculating formula is as follows:
wherein, I (T) p ,T q ) The correlation coefficient, T, representing two spectral vectors p And T q Respectively representing the traffic rearrangement image spectral vector and the traffic original image spectral vector, t p (x) Representing the spectral vector, t, of the traffic rearrangement image of the xth band under test q (x) Representing the spectrum vector of the original traffic image of the x-th band to be measured, p representing the band serial number of the traffic rearranged image, q representing the band serial number of the original traffic image, x representing the band serial number to be measured,
and
respectively represent t p (x) And t q (x) W is the total number of spectral vectors, | represents the norm.
In the preferred embodiment, the correlation coefficient of the spectral vectors of the original traffic image and the rearranged traffic image is measured, so that the spectral vector misjudgment caused by the influence of an abnormal value is avoided, and meanwhile, compared with the prior art, the calculation complexity is simplified, and the algorithm speed is improved.
Preferably, the algorithm search is performed on the traffic rearrangement image which has completed the stationary detection step, and is implemented by calculating the local average value of the similar neighborhood of the pixel w +1, and different custom calculation formulas are adopted according to the difference of the pixel w:
when w is more than or equal to 1 and less than or equal to U:
when w > U:
wherein U represents the number of pixels in the similar domain, w represents the pixel,
the initialization is 0.
In the preferred embodiment, the algorithm searching precision is improved by utilizing the calculation of distinguishing the local average value of the similar neighborhood, so that the accuracy of wave band selection is improved, and the occupied space of the image is reduced under the condition of ensuring that the image is not distorted and the visual effect of human eyes is not changed.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (4)
1. A traffic image data processing system, comprising: the traffic image acquisition module is used for capturing a traffic original image, the traffic image transmission module is used for transmitting the traffic original image to the traffic image processing module, the traffic image processing module is used for optimizing the traffic original image to obtain a traffic optimized image, the traffic image storage module is used for storing the traffic optimized image, and the traffic image acquisition module, the traffic image transmission module, the traffic image processing module and the traffic image storage module are connected in a wired or wireless mode;
the traffic image processing module rearranges and selects the wave band sequence of the original traffic image, the selection processing comprises a stability detection step, a pixel search step and a wave band selection step to obtain a traffic rearranged image, the stability detection step detects the stability performance of the traffic rearranged image, the stability coefficient of each wave band of the traffic rearranged image is measured and calculated, and the stability coefficient standard value is set for comparison, the pixel search step carries out algorithm search on the traffic rearranged image which is subjected to the stability detection step, the same type of pixels are found out in the similar neighborhood, and the wave band selection step carries out selective highlighting on the same type of pixels to obtain a traffic optimized image;
the measurement and calculation of the stability coefficient of each wave band of the traffic rearrangement image comprises the steps of measuring and calculating the correlation coefficient of the spectrum vectors of the original traffic image and the traffic rearrangement image, and expressing the stability performance of the two spectrum vectors through the measurement and calculation result, wherein the self-defined measurement and calculation formula is as follows:
wherein, I (T) p ,T q ) Represents twoCorrelation coefficient of spectral vector, T p And T p Respectively representing the traffic rearrangement image spectral vector and the traffic original image spectral vector, t p (x) Representing the spectral vector, t, of the traffic rearrangement image of the xth band under test q (x) Representing the spectrum vector of the original traffic image of the x-th band to be measured, p representing the band serial number of the traffic rearranged image, q representing the band serial number of the original traffic image, x representing the band serial number to be measured,
and
respectively represent t p (x) And t q (x) Is the total number of spectral vectors, | represents the norm.
2. The traffic image data processing system according to claim 1, wherein the traffic image capturing module captures a traffic raw image using a camera.
3. The traffic image data processing system according to claim 1, wherein the traffic image storage module is stored in a computer-readable storage medium and/or in a cloud.
4. The traffic image data processing system according to claim 1, wherein the algorithm search for the traffic rearranged image that has completed the stationary detection step is performed by calculating a local average value of a similar neighborhood of the pixel w +1, and different custom calculation formulas are adopted according to the difference of the pixel w:
when w is more than or equal to 1 and less than or equal to U:
when w > U:
wherein the content of the first and second substances,
represents the local average of the similarity neighborhood of pixel w +1, U represents the number of pixels in the similarity neighborhood, w represents the pixel,
the initialization is 0.
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| CN106846815A (en) * | 2017-03-29 | 2017-06-13 | 深圳万智联合科技有限公司 | A kind of efficient intelligent traffic administration system big data analysis system |
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