CN117455762B - Method and system for improving resolution of recorded picture based on panoramic automobile data recorder - Google Patents
Method and system for improving resolution of recorded picture based on panoramic automobile data recorder Download PDFInfo
- Publication number
- CN117455762B CN117455762B CN202311788192.2A CN202311788192A CN117455762B CN 117455762 B CN117455762 B CN 117455762B CN 202311788192 A CN202311788192 A CN 202311788192A CN 117455762 B CN117455762 B CN 117455762B
- Authority
- CN
- China
- Prior art keywords
- illumination
- image
- panoramic
- resolution
- scene
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000005286 illumination Methods 0.000 claims abstract description 218
- 238000013507 mapping Methods 0.000 claims abstract description 23
- 238000009432 framing Methods 0.000 claims abstract description 5
- 238000012545 processing Methods 0.000 claims abstract description 5
- 230000006872 improvement Effects 0.000 claims description 5
- 230000009467 reduction Effects 0.000 claims description 5
- 238000012549 training Methods 0.000 claims description 5
- 238000005516 engineering process Methods 0.000 claims description 3
- 238000009499 grossing Methods 0.000 claims description 2
- 238000003384 imaging method Methods 0.000 claims description 2
- 238000013139 quantization Methods 0.000 claims 2
- 230000000694 effects Effects 0.000 abstract description 4
- 238000005457 optimization Methods 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 238000013136 deep learning model Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4053—Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution
- G06T3/4076—Scaling of whole images or parts thereof, e.g. expanding or contracting based on super-resolution, i.e. the output image resolution being higher than the sensor resolution using the original low-resolution images to iteratively correct the high-resolution images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/28—Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/34—Smoothing or thinning of the pattern; Morphological operations; Skeletonisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
- G07C5/0866—Registering performance data using electronic data carriers the electronic data carrier being a digital video recorder in combination with video camera
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Multimedia (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- Artificial Intelligence (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Image Processing (AREA)
Abstract
The invention relates to the field of video processing, and discloses a method and a system for improving resolution of a recorded picture based on a panoramic automobile data recorder, wherein the method comprises the following steps: identifying illumination characteristics of a driving record scene, and analyzing illumination states of the driving record scene; identifying an illumination influence coefficient of the illumination state on the panoramic vehicle recorder, and constructing an equilibrium illumination network of the panoramic vehicle recorder; performing driving recording by using a panoramic driving recorder to obtain driving recording video, and framing the driving recording video to obtain driving recording frame images; identifying a low-resolution image of a driving record frame image, extracting image features of the low-resolution image, mapping the image features to obtain a mapping relation, and carrying out high-resolution reconstruction on the low-resolution image to obtain a high-resolution image; and constructing a high-resolution driving record video of the driving record video. The method and the device can improve the optimization effect on the resolution of the recorded picture of the panoramic automobile data recorder.
Description
Technical Field
The invention relates to the field of video processing, in particular to a method and a system for improving resolution of a recorded picture based on a panoramic automobile data recorder.
Background
Recording picture resolution generally refers to the sharpness and level of detail of a scene captured by a video or image sensor. This resolution determines the image quality, i.e., the number of pixels contained in a unit length (typically inches). The higher the resolution, the more pixels contained in a unit length, and the finer the image quality.
The improvement of the resolution of the recorded picture is mainly realized by selecting a high-resolution sensor and replacing a large aperture lens, the method is mainly used for optimizing hardware equipment, and details are lost when the recorded picture is exposed or is too dark, so that the picture with low resolution appears in the video recorded by the automobile data recorder, and the improvement effect of the resolution of the recorded picture is poor.
Disclosure of Invention
The invention provides a method and a system for improving the resolution of a recorded picture based on a panoramic automobile data recorder, and mainly aims to improve the optimization effect on the resolution of the recorded picture of the panoramic automobile data recorder.
In order to achieve the above object, the present invention provides a method for improving resolution of a recording picture based on a panoramic vehicle recorder, comprising:
acquiring a driving record scene of a panoramic driving recorder, identifying illumination characteristics of the driving record scene, and analyzing illumination states of the driving record scene based on the illumination characteristics;
identifying an illumination influence coefficient of the illumination state on the panoramic vehicle recorder, and constructing an equilibrium illumination network of the panoramic vehicle recorder based on the illumination influence coefficient;
based on the balanced illumination network, using the panoramic automobile data recorder to record an automobile to obtain an automobile data record video, and framing the automobile data record video to obtain an automobile data record frame image;
identifying a low-resolution image of the driving record frame image, extracting image features of the low-resolution image, mapping the image features to obtain a mapping relation, and carrying out high-resolution reconstruction on the low-resolution image based on the mapping relation to obtain a high-resolution image;
and constructing the high-resolution driving recording video of the driving recording video based on the high-resolution image.
Optionally, the identifying the illumination feature of the driving record scene includes:
acquiring a scene image of the driving recording scene;
calculating the third-order moment of the image brightness of the scene image;
analyzing the illumination distribution of the driving recording scene based on the third-order moment of the image brightness;
and extracting the illumination characteristics of the driving record scene based on the illumination distribution.
Optionally, the calculating the third order moment of the image brightness of the scene image includes:
marking image pixels of the scene image;
based on the image pixel points, calculating the third-order moment of the image brightness of the scene image by using the following formula:
；
wherein m30 represents an image luminance third moment of the scene image in the x-axis direction, a represents an abscissa of the image pixel point, c represents an ordinate of the image pixel point, f (a, c) represents a pixel value of the image pixel point, m03 represents an image luminance third moment of the scene image in the y-axis direction, m12 represents a second order mixed moment of the scene image in the x-axis and y-axis directions,
optionally, the analyzing the illumination state of the driving record scene based on the illumination feature includes:
training an illumination recognition model of the driving recording scene based on the illumination characteristics and the corresponding scene image of the driving recording scene;
calculating the model recall rate of the illumination recognition model;
and when the model recall rate meets the requirement, the illumination state of the driving record scene is identified by utilizing the illumination identification model.
Optionally, the identifying the illumination influence coefficient of the illumination state on the panoramic automobile data recorder includes:
identifying an illumination influence factor of the panoramic automobile data recorder;
analyzing the illumination influence relation of the illumination influence factors on the panoramic automobile data recorder;
based on the illumination state, quantifying the illumination influence factor to obtain a quantified illumination influence factor;
and calculating the illumination influence coefficient of the panoramic automobile data recorder based on the illumination influence relation and the quantized illumination influence factor.
Optionally, the calculating the illumination influence coefficient of the panoramic automobile data recorder based on the illumination influence relationship and the quantized illumination influence factor includes:
determining the influence factor weight of the corresponding illumination influence factor of the panoramic automobile data recorder based on the illumination influence relation;
based on the influence factor weight and the quantized illumination influence factor, calculating an illumination influence coefficient of the panoramic automobile data recorder by using the following formula:
；
wherein,representing illumination influence coefficients of the panoramic automobile data recorder, m represents the quantity of illumination influence factors corresponding to the panoramic automobile data recorder, and E i Representing quantized illumination influence factor corresponding to ith illumination influence factor of panoramic automobile data recorder, and Q i Influence factor weight indicating that panoramic automobile data recorder corresponds to ith illumination influence factor, and +.>Indicating that the ith illumination influence factor corresponding to the scenic driving recorder is opposite to other illumination influence factorsThe factors affect the coefficients.
Optionally, the extracting the image features of the low resolution image includes:
converting the low resolution image into a gray scale image;
dividing the gray scale image into image blocks;
converting the image block into a binary image;
extracting the binary image characteristics of the binary image;
and performing dimension reduction processing on the binary image features to obtain the image features of the low-resolution image.
Optionally, the converting the image block into a binary image includes:
marking a center pixel of the image block; calculating a local binary pattern value for the center pixel using the formula:
；
wherein LBP (r, v) represents a local binary pattern value of the center pixel, U represents a sign function, gradient (r, v, b) represents a gradient value between the center pixel (r, v) and the neighborhood pixel, r represents an abscissa of the center pixel, and v represents an ordinate of the center pixel;
and constructing a binary image of the image block based on the local binary pattern value.
Optionally, the performing high-resolution reconstruction on the low-resolution image based on the mapping relationship to obtain a high-resolution image includes:
based on the mapping relation, carrying out high-resolution reconstruction on the image block corresponding to the low-resolution image to obtain a high-resolution image block;
fusing the high-resolution image blocks to obtain the fused high-resolution image blocks;
and carrying out smoothing treatment on the fused high-resolution image block to obtain the high-resolution image.
In order to solve the above problems, the present invention further provides a recording frame resolution improving system based on a panoramic automobile data recorder, the system comprising:
the illumination state analysis module is used for acquiring a driving record scene of the panoramic driving recorder, identifying illumination characteristics of the driving record scene and analyzing the illumination state of the driving record scene based on the illumination characteristics;
the illumination balancing module is used for identifying the illumination influence coefficient of the illumination state on the panoramic vehicle recorder and constructing a balanced illumination network of the panoramic vehicle recorder based on the illumination influence coefficient;
the video imaging module is used for carrying out driving recording by utilizing the panoramic driving recorder based on the balanced illumination network to obtain driving recording video, and framing the driving recording video to obtain driving recording frame images;
the high-resolution reconstruction module is used for identifying a low-resolution image of the driving record frame image, extracting image features of the low-resolution image, mapping the image features to obtain a mapping relation, and carrying out high-resolution reconstruction on the low-resolution image based on the mapping relation to obtain a high-resolution image;
and the image video module is used for constructing a high-resolution driving record video of the driving record video based on the high-resolution image.
According to the embodiment of the invention, the illumination conditions and scene attributes of the images can be reflected by identifying the illumination characteristics of the driving record scene, so that a data basis is provided for the identification, analysis and understanding of the later-stage images; based on the illumination characteristics, the embodiment of the invention analyzes the illumination state of the driving record scene to analyze whether the current illumination can realize the record of the driving recorder or not in the later stage; according to the embodiment of the invention, the illumination influence coefficient of the illumination state on the panoramic automobile data recorder is identified, so that the influence degree of the current illumination on the automobile data recorder can be analyzed, and a basis is provided for the reduction of the illumination influence in the later period; further, the embodiment of the invention can screen out the images with the resolution not meeting the requirement to improve the resolution by identifying the low-resolution images of the driving record frame images, and further, the embodiment of the invention obtains the mapping relationship by mapping the image characteristics, and the mapping relationship is based on the high-resolution reconstruction of the images in the later stage. The mapping relation refers to a relation between a low-resolution image and a high-resolution image obtained after mapping the image features into a nonlinear space, and finally, the embodiment of the invention can realize resolution improvement of the driving recording video by constructing the high-resolution driving recording video of the driving recording video based on the high-resolution image. Therefore, the method and the system for improving the resolution of the recorded picture based on the panoramic automobile data recorder can improve the optimization effect on the resolution of the recorded picture of the panoramic automobile data recorder.
Drawings
Fig. 1 is a flow chart of a method for improving resolution of a recording image based on a panoramic recorder according to an embodiment of the present invention;
fig. 2 is a functional block diagram of a recording image resolution enhancing system based on a panoramic vehicle recorder according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device of a recording screen resolution enhancement system based on a panoramic vehicle recorder according to an embodiment of the present invention;
the achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a recording picture resolution improving method based on a panoramic automobile data recorder. The execution main body of the panoramic vehicle event data recorder-based recording picture resolution improvement method comprises at least one of a server side, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the method for improving the resolution of the recording picture based on the panoramic automobile data recorder can be executed by software or hardware installed in a terminal device or a server device, wherein the software can be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a method for improving resolution of a recording image based on a panoramic drive recorder according to an embodiment of the present invention is shown. In this embodiment, the method for improving resolution of a recording picture based on a panoramic vehicle recorder includes:
s1, acquiring a driving record scene of a panoramic driving recorder, identifying illumination characteristics of the driving record scene, and analyzing illumination states of the driving record scene based on the illumination characteristics.
In the embodiment of the present invention, the driving recording scene refers to a scene recorded by the panoramic driving recorder corresponding to a driving vehicle, for example, a scene of urban road driving, highway driving, night driving, irregular driving conditions, etc.
Furthermore, the embodiment of the invention can reflect the illumination condition and scene attribute of the image by identifying the illumination characteristic of the driving record scene, which provides a data basis for the identification, analysis and understanding of the later image. The illumination characteristic refers to a characteristic attribute of illumination in the driving record scene, such as a characteristic attribute of continuous darkness, partial exposure and the like.
As an embodiment of the present invention, the identifying the illumination feature of the driving record scene includes: acquiring a scene image of the driving recording scene; calculating the third-order moment of the image brightness of the scene image; analyzing the illumination distribution of the driving recording scene based on the third-order moment of the image brightness; and extracting the illumination characteristics of the driving record scene based on the illumination distribution.
The scene image is an image of a current scene of the driving recording scene, the third-order moment of the brightness of the image is a moment describing the brightness distribution condition of the image, and the illumination distribution is a brightness distribution state of an analysis image. For example, the distribution such as the brightness overall brightness level, the brightness dispersion level, and the brightness symmetry.
Optionally, as an optional embodiment of the present invention, the calculating an image brightness third moment of the scene image includes: marking image pixels of the scene image; based on the image pixel points, calculating the third-order moment of the image brightness of the scene image by using the following formula:
；
where m30 represents an image luminance third-order moment of the scene image in the x-axis direction, a represents an abscissa of an image pixel, c represents an ordinate of the image pixel, f (a, c) represents a pixel value of the image pixel, m03 represents an image luminance third-order moment of the scene image in the y-axis direction, and m12 represents a second-order mixed moment of the scene image in the x-axis and y-axis directions.
The second-order mixed moment refers to a moment describing the degree of correlation between the third-order moment of the image brightness of the scene image in the x-axis direction and the third-order moment of the image brightness of the scene image in the y-axis direction.
Based on the illumination characteristics, the embodiment of the invention analyzes the illumination state of the driving record scene to analyze whether the current illumination can realize the record of the driving recorder or not in the later stage. The illumination state refers to a current illumination condition of the driving recording scene, such as a condition that recording environment illumination is too dark, recording environment illumination exposure and the like.
As one embodiment of the present invention, the analyzing the illumination state of the driving record scene based on the illumination feature includes: training an illumination recognition model of the driving recording scene based on the illumination characteristics and the corresponding scene image of the driving recording scene; calculating the model recall rate of the illumination recognition model; and when the model recall rate meets the requirement, the illumination state of the driving record scene is identified by utilizing the illumination identification model.
The illumination recognition model is a model capable of recognizing illumination states in images, and training of the illumination recognition model can be performed by using a deep learning model after the extracted illumination features are obtained. Common models include linear classifiers, support Vector Machines (SVMs), decision trees, and the like. In the training process, the model can accurately identify the target object by optimizing the loss function, and the model recall rate refers to the accuracy degree of the identification result of the illumination identification model.
S2, identifying an illumination influence coefficient of the illumination state on the panoramic vehicle recorder, and constructing an equilibrium illumination network of the panoramic vehicle recorder based on the illumination influence coefficient.
According to the embodiment of the invention, the illumination influence coefficient of the illumination state on the panoramic automobile data recorder is identified, so that the influence degree of the current illumination on the automobile data recorder can be analyzed, and a basis is provided for the reduction of the illumination influence in the later period. The illumination influence coefficient refers to the influence degree of the current illumination condition on the panoramic automobile data recorder automobile data record.
Optionally, as an embodiment of the present invention, the identifying an illumination influence coefficient of the illumination state on the panoramic automobile data recorder includes: identifying an illumination influence factor of the panoramic automobile data recorder; analyzing the illumination influence relation of the illumination influence factors on the panoramic automobile data recorder; based on the illumination state, quantifying the illumination influence factor to obtain a quantified illumination influence factor; and calculating the illumination influence coefficient of the panoramic automobile data recorder based on the illumination influence relation and the quantized illumination influence factor.
The illumination influence factors refer to factors which influence the illumination factors recorded by the panoramic automobile data recorder, such as environmental exposure, environment darkness and the like, the illumination influence relationship refers to the influence relationship of the illumination influence factors on the recorded pictures of the panoramic automobile data recorder, such as the more serious the exposure is, the less clear the recorded pictures of the panoramic automobile data recorder are, and the quantized illumination influence factors refer to the quantized values of the illumination influence factors, such as exposure degree, brightness equivalence.
Optionally, as an optional embodiment of the present invention, the calculating, based on the illumination influence relation and the quantized illumination influence factor, an illumination influence coefficient of the panoramic roadway includes: determining the influence factor weight of the corresponding illumination influence factor of the panoramic automobile data recorder based on the illumination influence relation; based on the influence factor weight and the quantized illumination influence factor, calculating an illumination influence coefficient of the panoramic automobile data recorder by using the following formula:
；
wherein,representing illumination influence coefficients of the panoramic automobile data recorder, m represents the quantity of illumination influence factors corresponding to the panoramic automobile data recorder, and E i Representing quantized illumination influence factor corresponding to ith illumination influence factor of panoramic automobile data recorder, and Q i Influence factor weight indicating that panoramic automobile data recorder corresponds to ith illumination influence factor, and +.>And the factor mutual influence coefficient of the ith illumination influence factor corresponding to the scene driving recorder on other illumination influence factors is represented.
The influence factor weight refers to the influence degree of the illumination influence factor on the panoramic automobile data recorder picture record, the factor mutual influence coefficient refers to the influence degree of a certain illumination influence factor on other illumination influence factors, and the quantitative illumination influence factors can be listed so as to extract the numerical relation between the certain illumination influence factor and the other illumination influence factors, thereby analyzing the factor mutual influence coefficient of the illumination influence factor.
According to the embodiment of the invention, based on the illumination influence coefficient, the balanced illumination network of the panoramic automobile data recorder is constructed, so that the automobile data recorder can record in a special environment, and the resolution of pictures is improved. The balanced illumination network is a network for adjusting illumination of the panoramic automobile data recorder in a special illumination environment, and can be realized through an infrared technology.
Claims (4)
1. A method for improving resolution of a recorded picture based on a panoramic automobile data recorder is characterized by comprising the following steps:
acquiring a driving record scene of a panoramic driving recorder, acquiring a scene image of the driving record scene, marking image pixel points of the scene image, and calculating the third-order moment of the image brightness of the scene image based on the image pixel points by using the following formula:
；
wherein,representing scene image in->Third moment of image brightness in axial direction, +.>Representing the abscissa of the pixel points of the image,representing the ordinate of the image pixel, +.>Pixel value representing the pixel point of the image, < >>Representing scene image in->Third moment of image brightness in axial direction, +.>Representing scene image in->Shaft and->The second-order hybrid moment in the axial direction is used for analyzing the illumination distribution of the driving record scene based on the third-order moment of the image brightness, extracting the illumination characteristics of the driving record scene based on the illumination distribution, and analyzing the illumination state of the driving record scene based on the illumination characteristics;
identifying the illumination influence factors of the panoramic automobile data recorder, analyzing the illumination influence relation of the illumination influence factors to the panoramic automobile data recorder, quantifying the illumination influence factors based on the illumination state to obtain quantified illumination influence factors, determining the influence factor weights of the illumination influence factors corresponding to the panoramic automobile data recorder based on the illumination influence relation, and calculating the illumination influence coefficients of the panoramic automobile data recorder based on the influence factor weights and the quantified illumination influence factors by using the following formula:
；
wherein,indicating illumination influence coefficient of panoramic automobile data recorder, < ->Indicating the quantity of corresponding illumination influence factors of the panoramic automobile data recorder, < ->Indicate panoramic event data recorder corresponds to +.>Quantization of individual illumination influencing factors, < ->Indicate panoramic event data recorder corresponds to +.>Influence factor weights of individual illumination influence factors, +.>Indicate panoramic event data recorder corresponds to +.>Factors of individual illumination influence factors on other illumination influence factors influence coefficients mutually, and an equilibrium illumination network of the panoramic vehicle recorder is constructed based on the illumination influence coefficients, wherein the equilibrium illumination network refers to a network for illumination adjustment of the panoramic vehicle recorder in a special illumination environment, and the equilibrium illumination network is realized through an infrared technology;
based on the balanced illumination network, using the panoramic automobile data recorder to record an automobile to obtain an automobile data record video, and framing the automobile data record video to obtain an automobile data record frame image;
identifying a low-resolution image of the driving record frame image, converting the low-resolution image into a gray image, dividing the gray image into image blocks, marking central pixels of the image blocks, and calculating local binary pattern values of the central pixels by using the following formula:
；
wherein,local binary pattern value representing the center pixel, is->Representing a symbolic function +_>Representing the center pixel +.>And neighborhood pixels->Gradient values between->Represents the abscissa of the center pixel, +.>Representing the ordinate of a center pixel, constructing a binary image of the image block based on the local binary pattern value, extracting binary image features of the binary image, performing dimension reduction processing on the binary image features to obtain image features of the low-resolution image, mapping the image features to obtain a mapping relation, and performing high-resolution reconstruction on the low-resolution image based on the mapping relation to obtain a high-resolution image;
and constructing the high-resolution driving recording video of the driving recording video based on the high-resolution image.
2. The panorama-recorder-based recording screen resolution improvement method according to claim 1, wherein the analyzing the illumination state of the driving recording scene based on the illumination features comprises:
training an illumination recognition model of the driving recording scene based on the illumination characteristics and the corresponding scene image of the driving recording scene;
calculating the model recall rate of the illumination recognition model;
and when the model recall rate meets the requirement, the illumination state of the driving record scene is identified by utilizing the illumination identification model.
3. The method for improving resolution of a recording picture based on a panoramic drive recorder according to claim 1, wherein the performing high-resolution reconstruction on the low-resolution image based on the mapping relationship to obtain a high-resolution image comprises:
based on the mapping relation, carrying out high-resolution reconstruction on the image block corresponding to the low-resolution image to obtain a high-resolution image block;
fusing the high-resolution image blocks to obtain fused high-resolution image blocks;
and carrying out smoothing treatment on the fused high-resolution image block to obtain the high-resolution image.
4. A panorama-recorder-based recorded picture resolution enhancement system for performing the panorama-recorder-based recorded picture resolution enhancement method according to any one of claims 1-3, the system comprising:
the illumination state analysis module is used for acquiring a driving record scene of the panoramic driving recorder, acquiring a scene image of the driving record scene, marking image pixel points of the scene image, and calculating the third-order moment of the image brightness of the scene image based on the image pixel points by using the following formula:
；
wherein,representing scene image in->Third moment of image brightness in axial direction, +.>Representing the abscissa of the pixel points of the image,representing the ordinate of the image pixel, +.>Pixel value representing the pixel point of the image, < >>Representing scene image in->Third moment of image brightness in axial direction, +.>Representing scene image in->Shaft and->The second-order hybrid moment in the axial direction is used for analyzing the illumination distribution of the driving record scene based on the third-order moment of the image brightness, extracting the illumination characteristics of the driving record scene based on the illumination distribution, and analyzing the illumination state of the driving record scene based on the illumination characteristics;
the illumination balancing module is used for identifying illumination influence factors of the panoramic automobile data recorder, analyzing illumination influence relation of the illumination influence factors to the panoramic automobile data recorder, quantifying the illumination influence factors based on the illumination state to obtain quantified illumination influence factors, determining influence factor weights of the panoramic automobile data recorder corresponding to the illumination influence factors based on the illumination influence relation, and calculating illumination influence coefficients of the panoramic automobile data recorder based on the influence factor weights and the quantified illumination influence factors by using the following formula:
；
wherein,indicating illumination influence coefficient of panoramic automobile data recorder, < ->Indicating the quantity of corresponding illumination influence factors of the panoramic automobile data recorder, < ->Indicate panoramic event data recorder corresponds to +.>Quantization of individual illumination influencing factors, < ->Indicate panoramic event data recorder corresponds to +.>Influence factor weights of individual illumination influence factors, +.>Indicate panoramic event data recorder corresponds to +.>Factors of each illumination influence factor on other illumination influence factors are mutually influenced, and an balanced illumination network of the panoramic automobile data recorder is constructed based on the illumination influence factors, wherein the balanced illumination network refers to a network for adjusting illumination of the panoramic automobile data recorder in a special illumination environment, and the balanced illumination network is composed of the following componentsThe balanced illumination network is realized by an infrared technology;
the video imaging module is used for carrying out driving recording by utilizing the panoramic driving recorder based on the balanced illumination network to obtain driving recording video, and framing the driving recording video to obtain driving recording frame images;
the high-resolution reconstruction module is used for identifying a low-resolution image of the driving record frame image, converting the low-resolution image into a gray image, dividing the gray image into image blocks, marking a central pixel of the image block, and calculating a local binary pattern value of the central pixel by using the following formula:
；
wherein,local binary pattern value representing the center pixel, is->Representing a symbolic function +_>Representing the center pixel +.>And neighborhood pixels->Gradient values between->Represents the abscissa of the center pixel, +.>Representing the ordinate of the center pixel, constructing a binary image of the image block based on the local binary pattern value, extracting thePerforming dimension reduction processing on the binary image features of the binary image to obtain image features of the low-resolution image, mapping the image features to obtain a mapping relation, and performing high-resolution reconstruction on the low-resolution image based on the mapping relation to obtain a high-resolution image;
and the image video module is used for constructing a high-resolution driving record video of the driving record video based on the high-resolution image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311788192.2A CN117455762B (en) | 2023-12-25 | 2023-12-25 | Method and system for improving resolution of recorded picture based on panoramic automobile data recorder |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311788192.2A CN117455762B (en) | 2023-12-25 | 2023-12-25 | Method and system for improving resolution of recorded picture based on panoramic automobile data recorder |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117455762A CN117455762A (en) | 2024-01-26 |
| CN117455762B true CN117455762B (en) | 2024-04-12 |
Family
ID=89593307
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311788192.2A Active CN117455762B (en) | 2023-12-25 | 2023-12-25 | Method and system for improving resolution of recorded picture based on panoramic automobile data recorder |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117455762B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117893989B (en) * | 2024-03-14 | 2024-06-04 | 盯盯拍（深圳）技术股份有限公司 | Sequential picture tracing method and system based on panoramic automobile data recorder |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160040335A (en) * | 2014-10-02 | 2016-04-14 | 전자부품연구원 | Low Power Vehicle Video Recorder with Infrared Lighting Functions for Vision Recognition Enhancement in Low Level Light Environment and Vehicle Video Recording Method thereof |
| CN111536970A (en) * | 2020-05-08 | 2020-08-14 | 中国航空工业集团公司西安航空计算技术研究所 | Infrared inertial integrated navigation method for low-visibility large-scale scene |
| CN112699833A (en) * | 2021-01-12 | 2021-04-23 | 上海海事大学 | Ship target identification method based on convolutional neural network under complex illumination environment |
| CN113012175A (en) * | 2021-03-15 | 2021-06-22 | 南京理工大学 | Road airborne scene semantic segmentation method with infrared image enhancement |
| CN115689892A (en) * | 2022-11-14 | 2023-02-03 | 华南理工大学 | Vehicle-mounted image super-resolution reconstruction method, system, device and storage medium |
| CN115936785A (en) * | 2022-12-19 | 2023-04-07 | 招商银行股份有限公司 | Advertisement pushing method, equipment and storage medium |
-
2023
- 2023-12-25 CN CN202311788192.2A patent/CN117455762B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20160040335A (en) * | 2014-10-02 | 2016-04-14 | 전자부품연구원 | Low Power Vehicle Video Recorder with Infrared Lighting Functions for Vision Recognition Enhancement in Low Level Light Environment and Vehicle Video Recording Method thereof |
| CN111536970A (en) * | 2020-05-08 | 2020-08-14 | 中国航空工业集团公司西安航空计算技术研究所 | Infrared inertial integrated navigation method for low-visibility large-scale scene |
| CN112699833A (en) * | 2021-01-12 | 2021-04-23 | 上海海事大学 | Ship target identification method based on convolutional neural network under complex illumination environment |
| CN113012175A (en) * | 2021-03-15 | 2021-06-22 | 南京理工大学 | Road airborne scene semantic segmentation method with infrared image enhancement |
| CN115689892A (en) * | 2022-11-14 | 2023-02-03 | 华南理工大学 | Vehicle-mounted image super-resolution reconstruction method, system, device and storage medium |
| CN115936785A (en) * | 2022-12-19 | 2023-04-07 | 招商银行股份有限公司 | Advertisement pushing method, equipment and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 基于MATLAB的数字图像复原的研究;宋美萍;;《电子世界》;20200814(第15期);第21-22页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117455762A (en) | 2024-01-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117455762B (en) | Method and system for improving resolution of recorded picture based on panoramic automobile data recorder | |
| CN112862702B (en) | Image enhancement method, device, equipment and storage medium | |
| CN108615226B (en) | Image defogging method based on generation type countermeasure network | |
| CN111292264A (en) | Image high dynamic range reconstruction method based on deep learning | |
| CN110751630B (en) | Power transmission line foreign matter detection method and device based on deep learning and medium | |
| CN109377494B (en) | Semantic segmentation method and device for image | |
| CN112270309A (en) | Vehicle access point equipment snapshot quality evaluation method and device and readable medium | |
| CN113435407B (en) | Small target identification method and device for power transmission system | |
| CN114120272A (en) | Multi-supervision intelligent lane line semantic segmentation method fusing edge detection | |
| CN113515655A (en) | Fault identification method and device based on image classification | |
| CN114697212A (en) | Device parameter processing method, device, system and medium | |
| CN116052090A (en) | Image quality evaluation method, model training method, device, equipment and medium | |
| CN117152513A (en) | Vehicle boundary positioning method for night scene | |
| CN117395424B (en) | Video optimization method for video wireless transmission monitoring system | |
| CN110569698A (en) | Image target detection and semantic segmentation method and device | |
| Fu et al. | Low-light image enhancement base on brightness attention mechanism generative adversarial networks | |
| CN114677670B (en) | Method for automatically identifying and positioning identity card tampering | |
| CN111311584A (en) | Video quality evaluation method and device, electronic equipment and readable medium | |
| CN116363100A (en) | Image quality evaluation method, device, equipment and storage medium | |
| CN110765940A (en) | Target object statistical method and device | |
| CN115690934A (en) | Master and student attendance card punching method and device based on batch face recognition | |
| CN110766153A (en) | Neural network model training method and device and terminal equipment | |
| CN113011268A (en) | Intelligent vehicle navigation method and device, electronic equipment and storage medium | |
| CN114565597A (en) | Nighttime road pedestrian detection method based on YOLOv3-tiny-DB and transfer learning | |
| CN112183183A (en) | Target detection method and device and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |