CN110175967A - Image defogging processing method, system, computer equipment and storage medium - Google Patents
Image defogging processing method, system, computer equipment and storage medium Download PDFInfo
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- G—PHYSICS
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Abstract
This application involves a kind of image defogging processing method, system, computer equipment and storage mediums.Method includes: the original image obtained to defogging；Original image is converted into HIS image；Defogging processing is carried out to HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；Brightness, color saturation and tone are carried out to the HIS image after defogging to adjust, and obtain final mist elimination image.RGB is transformed into HIS space by this method, is carried out defogging processing in HIS space and is adjusted during defogging to its transmissivity, halation can be effectively reduced while defogging.In addition, its brightness, color saturation and tone are adjusted after defogging, the brightness of image after defogging is improved, and ensure that color saturation and tone are accurate, further improves the quality of image.
Description
Technical field
This application involves technical field of image processing, more particularly to a kind of image defogging processing method, system, computer
Equipment and storage medium.
Background technique
As smart city and security protection are fast-developing, video monitoring spreads over the every nook and cranny of our lives.But with big
The exacerbation of gas pollution, the frequency that haze weather occurs are higher and higher.Under haze weather, the fine particle and water that suspend in atmosphere
Drop can generate the effects of absorbing, scatter and reflecting to light, so that the image scene that the greasy weather generates is unintelligible, image detail is lost
It loses, limits Misty Image and video in the application in the fields such as traffic monitoring, target following, independent navigation.Therefore, in severe day
Under the conditions of gas, how to obtain the clear image of high quality is just particularly important with the accurate detection for realizing target object.
Currently, dark channel image defogging algorithm is generallyd use to carry out defogging processing, dark to image in the prior art
Image defogging algorithm is the perspective rate by estimating haze, so that reconstruction image, can mitigate mist (haze) to the shadow of image very well
It rings.However dark channel image defogging algorithm is used to be easy to have an impact the tone of image and will appear halation phenomenon.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide the image defogging processing side of the problem of being able to solve a kind of
Method, system, computer equipment and storage medium.
A kind of image defogging processing method, which comprises
Obtain the original image to defogging；
The original image is converted into HIS image；
Defogging processing is carried out to the HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；
Brightness, color saturation and tone are carried out to the HIS image after the defogging to adjust, and obtain final mist elimination image.
The calculation method of the transmissivity precalculated in one of the embodiments, comprising:
The original image is handled, the dark channel image of original image is obtained；
Steerable filter processing is carried out to the dark channel image, obtains filtered dark channel image；
The transmissivity for calculating the dark channel image, the transmissivity precalculated.
In the step of carrying out brightness to the HIS image after the defogging in one of the embodiments, comprising:
Brightness regulation is carried out to the HIS image after the defogging using brightness regulation function.
The brightness regulation function is luminance segmentation function in one of the embodiments, using brightness regulation function pair
In the step of HIS image after the defogging carries out brightness regulation, comprising:
Brightness regulation is carried out to the HIS image after the defogging using following luminance segmentation function:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.
The brightness regulation function is luminance gain function in one of the embodiments, using brightness regulation function pair
In the step of HIS image after the defogging carries out brightness regulation, comprising:
Brightness regulation is carried out to the HIS image after the defogging using following luminance gain function:
Y=xf (x)
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain letter
Number.
In the step of carrying out color saturation adjusting to the HIS image after the defogging in one of the embodiments, packet
It includes:
Color saturation adjusting is carried out to the HIS image after the defogging using the color saturation regulatory factor precalculated.
The calculation method of the color saturation regulatory factor precalculated in one of the embodiments, comprising:
Color saturation normalized is carried out to the original image；
The upper limit value and lower limit value of color saturation are determined according to the distribution probability of the image color saturation after normalized；
The first color saturation regulatory factor is determined according to the upper limit value and the lower limit value；
The first color saturation regulatory factor and pre-set second color saturation regulatory factor are modified, obtained
To the color saturation regulatory factor precalculated.
A kind of image defogging processing system, the system comprises:
Original image obtains module, for obtaining the original image to defogging；
HIS image conversion module, for the original image to be converted into HIS image；
Defogging module, for carrying out defogging processing to the HIS image using the transmissivity precalculated, after obtaining defogging
HIS image；
Final mist elimination image obtains module, for carrying out brightness, color saturation and color to the HIS image after the defogging
Tune section obtains final mist elimination image.
A kind of computer equipment can be run on a memory and on a processor including memory, processor and storage
Computer program, the processor perform the steps of when executing the computer program
Obtain the original image to defogging；
The original image is converted into HIS image；
Defogging processing is carried out to the HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；
Brightness, color saturation and tone are carried out to the HIS image after the defogging to adjust, and obtain final mist elimination image.
A kind of computer readable storage medium, is stored thereon with computer program, and the computer program is held by processor
It is performed the steps of when row
Obtain the original image to defogging；
The original image is converted into HIS image；
Defogging processing is carried out to the HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；
Brightness, color saturation and tone are carried out to the HIS image after the defogging to adjust, and obtain final mist elimination image.
Above-mentioned image defogging processing method, system, computer equipment and storage medium obtain the original graph to defogging first
Original image is converted into HIS image by picture, then using the transmissivity precalculated to HIS image, to image after defogging
Brightness, color saturation and tone be adjusted.RGB is transformed into HIS space by above-mentioned method, carries out defogging in HIS space
It handles and its transmissivity is adjusted during defogging, halation can be effectively reduced while defogging.In addition, after defogging
Its brightness, color saturation and tone are adjusted, the brightness of image after defogging is improved, and ensure that color saturation and tone
Accurately, the quality of image is further improved.
Detailed description of the invention
Fig. 1 is schematic diagram of the implementation example figure as defogging processing method application environment；
Fig. 2 is the applied environment figure of image defogging processing method in one embodiment；
Fig. 3 is the flow diagram of image defogging processing method in one embodiment；
Fig. 4 is the flow diagram for calculating the transmissivity precalculated in one embodiment in image defogging processing method；
Fig. 5 is the flow diagram of image defogging processing method in another embodiment；
Fig. 6 is in one embodiment using the result schematic diagram of the processing picture of image defogging processing method of the invention；
Fig. 7 is the knot of the processing picture in another embodiment using image defogging processing method and other methods of the invention
Fruit schematic diagram；
Fig. 8 is the structural block diagram of image defogging processing system in one embodiment；
Fig. 9 is the internal structure chart of computer equipment in one embodiment.
Specific embodiment
It is with reference to the accompanying drawings and embodiments, right in order to which the objects, technical solutions and advantages of the application are more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the application, not
For limiting the application.
This method applies in the terminal 102 of Fig. 1, and terminal can be personal computer, laptop etc., terminal 102
Communication connection is carried out with detection device 104, detection device 104 can be image acquisition device, video camera etc..
Wherein, when terminal 102 is connect with detection device 104 using local interface, detection device 104 can be by the first of acquisition
Beginning image is sent in terminal 102.In addition, terminal 102 can also obtain the initial graph measured in detection device 104 by instruction
Picture.
In one embodiment, as shown in Fig. 2, providing a kind of image defogging processing method, it is applied to Fig. 1 in this way
In terminal for be illustrated, comprising the following steps:
Step S202 obtains the original image to defogging；
Original image is converted into HIS image by step S204；
Wherein, refer to any photo, picture etc. with mist (haze) to the original image of defogging.Picture is all under normal conditions
It is colored, and color image is indicated using R (red) G (green) B (indigo plant).RGB corresponds to monitor or scanner
Three values, they form three-dimensional reference system, and any color calculated in such a system all falls in RGB color cube
In vivo.RGB system defines different colors with the trichromatic mixed proportion of red, green and blue, is difficult to different colors with accurate
Numerical value come indicate carry out quantitative analysis.
HIS (Hue-Intensity-Saturation) color space is that the common color of another in image procossing is empty
Between, it is from the vision system of people, with tone (Hue), saturation degree (Saturation or Chroma) and brightness
(Intensity or Brightness) describes color.HIS color space can be described with the conical space model of Fig. 2-2.
Wherein, tone H is indicated by angle, indicates red with different angles, yellow, green, blue, magenta.Saturation degree S is HIS
To the radius length of color point, the distance of the off-axis line of color point is closer for color space central axes, indicates that the white light of color is more.By force
Degree I indicates that the axis of cone describes gray level with the height on axis direction, and when minimum of intensity is black, and intensity is most
It is white when big value.Point on each and section of axis vertical take-off, intensity value is all equal.Although this description HIS face
The conical model of the colour space is considerably complicated, but the variation situation of tone, brightness and saturation degree can be showed very clear.Usually
Tone and saturation degree are commonly referred to as coloration, for indicating the classification and depth degree of color.It in the present embodiment will be to defogging
Original image is changing into HIS from RGB.
Step S206, carries out defogging processing to HIS image using the transmissivity precalculated, the HIS figure after obtaining defogging
Picture；
Wherein, image defogging be two kinds of technologies of image enhancement and image repair intersection with merge, if haze regarded as
It is a kind of noise, removal haze is namely gone out the noise of image, and image is restored to situation acquired in no haze；If
Regard the photo shot under haze environment as a kind of looks that image is original, then defogging is obviously exactly people to improve
Subjective visual quality and a kind of enhancing that image is carried out.It is a kind of currently used side for removing haze that dark, which removes haze,
Method, wherein transmissivity is very crucial factor during dark defogging；In other words its essence of dark defogging is exactly to count
Transmissivity is calculated, then image is adjusted according to transmissivity.In the present embodiment, transmissivity precalculates, and can adopt
Transmissivity is calculated with Steerable filter, and transmissivity is corrected, the transmissivity then precalculated.Wherein precalculate
Transmissivity can store in computer or terminal device, to image carry out defogging processing need using transmissivity Shi Congji
It is directly transferred in calculation machine or terminal device.
Step S208 carries out brightness, color saturation and tone to the HIS image after defogging and adjusts, obtains final defogging
Image.
After to the processing of HIS image defogging, brightness, color saturation and tone are carried out to the HIS image after defogging and adjusted,
In be usually to use some relevant adjustment functions, such as piecewise function, gain when to brightness, color saturation and hue adjustment
Function etc..In addition, when being adjusted to tone color can be carried out to the HIS image after defogging according to preset tone regulated value
Either one or two of tune section, wherein preset tone regulated value is not a unique value, a usually range, in this range
Value is ok.
Above-mentioned image defogging processing method obtains the original image to defogging first, and original image is converted into HIS image,
Then HIS image adjusts the brightness of image, color saturation and tone after defogging using the transmissivity precalculated
It is whole.RGB is transformed into HIS space by above-mentioned method, carries out defogging processing and during defogging to its transmissivity in HIS space
It is adjusted, halation can be effectively reduced while defogging.In addition, being carried out after defogging to its brightness, color saturation and tone
It adjusts, improves the brightness of image after defogging, and ensure that color saturation and tone are accurate, further improve the matter of image
Amount.
In one of the embodiments, as shown in figure 3, the calculation method of the transmissivity precalculated, comprising:
Step S302, handles original image, obtains the dark channel image of original image；
Step S304 carries out Steerable filter processing to dark channel image, obtains filtered dark channel image；
Step S306 calculates the transmissivity of dark channel image, the transmissivity precalculated.
Specifically, as shown in figure 4, the process for calculating transmissivity generally includes: dark channel image is extracted from original image,
Steerable filter is carried out to dark channel image, calculates the transmissivity of dark channel image in this process.
The filtering of guiding figure is a kind of image filtering technology, by guidance figure G, to target image P (input picture) into
Row filtering processing, so that last output image is generally similar to target image P, but texture part is similar to guidance figure G.
There are two its typical cases: guarantor's edge image is smooth, scratches figure.The purpose of Steerable filter is to keep advantage (the effectively holding side at edge
Edge, non-iterative calculate).Note guidance figure (guiding figure) is G, and input picture P, output image is Q, and the target of guiding figure filtering is just
It is so that original outputting and inputting is as identical as possible, while texture part is similar to guidance figure G.Since above formula is an office
Portion's linear model, therefore two coefficients are a variable related with position in fact.In order to determine its value, a small window is considered
Mouthful, so that the pixel in window meets both the above condition simultaneously, it can substitute the above in first formula and obtain target letter
Number.
In addition, transmissivity is determined according to the original image and global atmosphere light ingredient to defogging.It is thrown being calculated
Usually transmissivity is aligned after penetrating rate, thus the transmissivity precalculated.
In one embodiment, transmissivity is aligned using nonlinear function, wherein nonlinear function are as follows:txIndicate transmissivity, α, β are nonnegative real numbers.
In another optional embodiment, transmissivity can be aligned using a regulating constant, that is, given
Each brightness value distributes a positive, and is multiplied with original transmissivity, to change transmissivity, realizes the tune of defog effect
Section.Wherein the regulating constant can be configured according to the needs of users.
In the step of carrying out brightness to the HIS image after defogging in one of the embodiments, comprising:
Brightness regulation is carried out to the HIS image after defogging using brightness regulation function.
Specifically, carrying out brightness regulation to the HIS image after defogging, it is adjusted by using brightness regulation function.It adopts
Brightness regulation is carried out to the HIS image after defogging with brightness regulation function, may be implemented continuously to adjust image, convenient for selecting
Optimal Adjusted Option.
In a wherein specific embodiment, brightness regulation function is luminance segmentation function, using brightness regulation function pair
In the step of HIS image after defogging carries out brightness regulation, comprising:
Brightness regulation is carried out to the HIS image after defogging using following luminance segmentation function:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.Wherein
When confirming the upper limit value of brightness, usually according to the brightness probability distribution of the HIS image after defogging, probability is taken to be greater than or equal to
The brightness of predetermined probabilities value is upper limit value.Predetermined probabilities value is determined according to picture treatment effect requirement in practice, is usually selected
Select 95%.
In another specific embodiment, brightness regulation function is luminance gain function, using brightness regulation function to going
In the step of HIS image after mist carries out brightness regulation, comprising:
Brightness regulation is carried out to the HIS image after defogging using following luminance gain function:
Y=xf (x)
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain letter
Number.
In the step of carrying out color saturation adjusting to the HIS image after defogging in one of the embodiments, comprising:
Color saturation adjusting is carried out to the HIS image after defogging using the color saturation regulatory factor precalculated.
In one of the embodiments, as shown in figure 5, the calculation method of the color saturation regulatory factor precalculated, packet
It includes:
Step S502 carries out color saturation normalized to original image；
Step S504 determines the upper limit value of color saturation according to the distribution probability of the image color saturation after normalized
And lower limit value；
Step S506 determines the first color saturation regulatory factor according to upper limit value and lower limit value；
Step S508 repairs the first color saturation regulatory factor and pre-set second color saturation regulatory factor
Just, the color saturation regulatory factor precalculated.
Specifically, color saturation normalized is carried out to original image first, then to normalized colour saturation
Degree is quantified, i.e., is rounded multiplied by after 255；The probability distribution of color saturation after statistic quantification；Take color after 5% corresponding quantization
The value of saturation degree similarly takes 95% corresponding quantization color saturation as upper limit value floor as lower limit value up；According to upper limit value
With lower limit value the first color saturation regulatory factor:
B=0.75 × up/floor
Colour saturation is formed further according to the first color saturation regulatory factor and pre-set second color saturation regulatory factor
Spend regulatory factor are as follows:Wherein a indicates pre-set second color saturation regulatory factor, and a is usually user setting
A nonnegative real number, b indicate the first color saturation regulatory factor.Then it is modified, obtains to color saturation regulatory factor
To the color saturation regulatory factor precalculatedWherein x is
Color saturation after quantization；According to the corresponding color saturation maximum value of each pixel of brightness calculation adjusted, adjustment is then utilized
Factor d is multiplied by original color saturation, color saturation after being corrected, and carries out anti-normalization processing, obtains final color saturation.
Effect example
In order to verify the effect of image defogging processing method in the present invention, an effect example is provided.As a result such as Fig. 6 institute
Show, a is original foggy image；B is automatic colour saturation, automatic brightness adjustment reconstruction image after defogging；C is that color saturation is 0.5
When reconstruction image；D be color saturation be 1.6 when reconstruction image；E be color saturation be 2.6 when reconstruction image；F is tone biasing-
Reconstruction image after 15 °；G is that reconstruction image after 90s is biased to green.From figure it is found that using defogging processing method of the invention
The haze in picture can be effectively removed, and effect is good.
Comparative example
In order to further verify the effect of image defogging processing method in the present invention, a comparative example is given, is tied
For fruit as shown in fig. 7, a is original image, b is the reconstruction image of the original defogging algorithm of rgb space；C is not using for HIS space
The reconstruction image of Steerable filter and transmissivity adaptively correcting；D is the reconstruction image that adaption brightness adjustment is not used；E is certainly
Adapt to brightness adjustment, Steerable filter and perspective rate adaptively reconstruction image adjusted；Find out from known to figure, using in this method
Image defogging method can effectively remove the haze in figure, and can effectively keep the details such as the edge of image, i.e. defog effect
It is good.
It should be understood that although each step in the flow chart of Fig. 2-5 is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, these steps can execute in other order.Moreover, at least one in Fig. 2-5
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, the execution sequence in these sub-steps or stage is also not necessarily successively
It carries out, but can be at least part of the sub-step or stage of other steps or other steps in turn or alternately
It executes.
In one embodiment, as shown in figure 8, providing a kind of image defogging processing system, comprising:
Original image obtains module 802, for obtaining the original image to defogging；
HIS image conversion module 804, for original image to be converted into HIS image；
Defogging module 806, for carrying out defogging processing to HIS image using the transmissivity precalculated, after obtaining defogging
HIS image；
Final mist elimination image obtains module 808, for carrying out brightness, color saturation and color to the HIS image after defogging
Tune section obtains final mist elimination image.
Include: in one of the embodiments,
Dark channel image obtains module, for handling original image, obtains the dark channel image of original image；
Steerable filter module obtains filtered dark channel image for carrying out Steerable filter processing to dark channel image；
The transmissivity precalculated obtains module, and for calculating the transmissivity of dark channel image, what is precalculated is saturating
Penetrate rate.
Final mist elimination image acquisition module includes: in one of the embodiments,
Luminance adjustment module, for carrying out brightness regulation to the HIS image after defogging using brightness regulation function.
Brightness regulation function is luminance segmentation function in one of the embodiments, and luminance adjustment module is also used to use
Following luminance segmentation function carries out brightness regulation to the HIS image after defogging:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.
Brightness regulation function is luminance gain function in one of the embodiments, and luminance adjustment module is also used to use
Following luminance gain function carries out brightness regulation to the HIS image after defogging:
Y=xf (x)
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain letter
Number.
Final mist elimination image acquisition module includes: in one of the embodiments,
Color saturation adjustment module, for using the color saturation regulatory factor precalculated to the HIS image after defogging
Carry out color saturation adjusting.
Include: in one of the embodiments,
Module is normalized, for carrying out color saturation normalized to original image；
Limit value determining module, for determining color saturation according to the distribution probability of the image color saturation after normalized
Upper limit value and lower limit value；
First color saturation regulatory factor determining module, for determining the first color saturation tune according to upper limit value and lower limit value
Save the factor；
The color saturation regulatory factor precalculated obtains module, for setting to the first color saturation regulatory factor and in advance
The the second color saturation regulatory factor set is modified, the color saturation regulatory factor precalculated.
Specific about image defogging processing system limits the limit that may refer to above for image defogging processing method
Fixed, details are not described herein.Modules in above-mentioned image defogging processing system can fully or partially through software, hardware and its
Combination is to realize.Above-mentioned each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also be with
It is stored in the memory in computer equipment in a software form, in order to which processor calls the above modules of execution corresponding
Operation.
In one embodiment, a kind of computer equipment is provided, which can be server, internal junction
Composition can be as shown in Figure 7.The computer equipment include by system bus connect processor, memory, network interface and
Database.Wherein, the processor of the computer equipment is for providing calculating and control ability.The memory packet of the computer equipment
Include non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system, computer program and data
Library.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
Data of the database of machine equipment for memory resistor equivalent model, equivalent submodel, and obtained when storage execution calculating
Equivalent resistance, operating resistance and contact resistance.The network interface of the computer equipment is used to pass through network with external terminal
Connection communication.To realize a kind of image defogging processing method when the computer program is executed by processor.
It will be understood by those skilled in the art that structure shown in Fig. 7, only part relevant to application scheme is tied
The block diagram of structure does not constitute the restriction for the computer equipment being applied thereon to application scheme, specific computer equipment
It may include perhaps combining certain components or with different component layouts than more or fewer components as shown in the figure.
In one embodiment, a kind of computer equipment is provided, including memory, processor and storage are on a memory
And the computer program that can be run on a processor, processor perform the steps of acquisition to defogging when executing computer program
Original image；Original image is converted into HIS image；Defogging processing is carried out to HIS image using the transmissivity precalculated,
HIS image after obtaining defogging；Brightness, color saturation and tone are carried out to the HIS image after defogging to adjust, and are finally gone
Mist image.
In one embodiment, it also performs the steps of when processor executes computer program at original image
Reason, obtains the dark channel image of original image；Steerable filter processing is carried out to dark channel image, obtains filtered dark channel diagram
Picture；Calculate the transmissivity of dark channel image, the transmissivity precalculated.
In one embodiment, it also performs the steps of when processor executes computer program using brightness regulation function
Brightness regulation is carried out to the HIS image after defogging.
In one embodiment, it is also performed the steps of when processor executes computer program using following luminance segmentation
Function carries out brightness regulation to the HIS image after defogging:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.
In one embodiment, it is also performed the steps of when processor executes computer program using following luminance gain
Function carries out brightness regulation: y=xf (x) to the HIS image after defogging
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain letter
Number.
In one embodiment, it is also performed the steps of when processor executes computer program using the color precalculated
Saturation degree regulatory factor carries out color saturation adjusting to the HIS image after defogging.
In one embodiment, it is also performed the steps of when processor executes computer program and color is carried out to original image
Saturation degree normalized；The upper limit value of color saturation is determined according to the distribution probability of the image color saturation after normalized
And lower limit value；The first color saturation regulatory factor is determined according to upper limit value and lower limit value；To the first color saturation regulatory factor and
Pre-set second color saturation regulatory factor is modified, the color saturation regulatory factor precalculated.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of the original image obtained to defogging when being executed by processor；Original image is converted into HIS figure
Picture；Defogging processing is carried out to HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；After defogging
HIS image carries out brightness, color saturation and tone and adjusts, and obtains final mist elimination image.
In one embodiment, it is also performed the steps of when computer program is executed by processor and original image is carried out
Processing, obtains the dark channel image of original image；Steerable filter processing is carried out to dark channel image, obtains filtered dark
Image；Calculate the transmissivity of dark channel image, the transmissivity precalculated.
In one embodiment, it also performs the steps of when computer program is executed by processor using brightness regulation letter
HIS image after several pairs of defoggings carries out brightness regulation.
In one embodiment, it also performs the steps of when computer program is executed by processor using following brightness point
Section function carries out brightness regulation to the HIS image after defogging:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.
In one embodiment, it also performs the steps of when computer program is executed by processor and is increased using following brightness
Beneficial function carries out brightness regulation: y=xf (x) to the HIS image after defogging
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain letter
Number.
In one embodiment, also perform the steps of what use precalculated when computer program is executed by processor
Color saturation regulatory factor carries out color saturation adjusting to the HIS image after defogging.
In one embodiment, it is also performed the steps of when computer program is executed by processor and original image is carried out
Color saturation normalized；The upper limit of color saturation is determined according to the distribution probability of the image color saturation after normalized
Value and lower limit value；The first color saturation regulatory factor is determined according to upper limit value and lower limit value；To the first color saturation regulatory factor
It is modified with pre-set second color saturation regulatory factor, the color saturation regulatory factor precalculated.
It is that can pass through those of ordinary skill in the art will appreciate that realizing all or part of the process in embodiment method
Computer program is completed to instruct relevant hardware, computer program can be stored in a non-volatile computer and can be read and deposit
In storage media, the computer program is when being executed, it may include such as the process of the embodiment of each method.Wherein, provided herein
Each embodiment used in any reference to memory, storage, database or other media, may each comprise non-volatile
And/or volatile memory.Nonvolatile memory may include that read-only memory (ROM), programming ROM (PROM), electricity can be compiled
Journey ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include random access memory
(RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms, such as static state RAM
(SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhanced SDRAM
(ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) directly RAM (RDRAM), straight
Connect memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of above embodiments can be combined arbitrarily, for simplicity of description, not in embodiment
Each all possible combination of technical characteristic is all described, as long as however, there is no contradiction in the combination of these technical features, all
It is considered to be the range of this specification record.
Above embodiments only express the several embodiments of the application, and the description thereof is more specific and detailed, but can not
Therefore it is construed as limiting the scope of the patent.It should be pointed out that for those of ordinary skill in the art,
Under the premise of not departing from the application design, various modifications and improvements can be made, these belong to the protection scope of the application.
Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (10)
1. a kind of image defogging processing method, which comprises
Obtain the original image to defogging；
The original image is converted into HIS image；
Defogging processing is carried out to the HIS image using the transmissivity precalculated, the HIS image after obtaining defogging；
Brightness, color saturation and tone are carried out to the HIS image after the defogging to adjust, and obtain final mist elimination image.
2. the method according to claim 1, wherein the calculation method of the transmissivity precalculated, comprising:
The original image is handled, the dark channel image of original image is obtained；
Steerable filter processing is carried out to the dark channel image, obtains filtered dark channel image；
The transmissivity for calculating the dark channel image, the transmissivity precalculated.
3. the method according to claim 1, wherein the step of carrying out brightness to the HIS image after the defogging
In, comprising:
Brightness regulation is carried out to the HIS image after the defogging using brightness regulation function.
4. according to the method described in claim 3, it is characterized in that, the brightness regulation function is luminance segmentation function, use
In the step of brightness regulation function carries out brightness regulation to the HIS image after the defogging, comprising:
Brightness regulation is carried out to the HIS image after the defogging using following luminance segmentation function:
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, up indicate the upper limit value of brightness.
5. according to the method described in claim 4, it is characterized in that, the brightness regulation function is luminance gain function, use
In the step of brightness regulation function carries out brightness regulation to the HIS image after the defogging, comprising:
Brightness regulation is carried out to the HIS image after the defogging using following luminance gain function:
Y=xf (x)
Wherein, y indicates that brightness value adjusted, x indicate that the brightness value before adjustment, f (x) indicate pre-set gain function.
6. method according to any one of claims 1 to 5, which is characterized in that carry out color to the HIS image after the defogging
In the step of saturation degree is adjusted, comprising:
Color saturation adjusting is carried out to the HIS image after the defogging using the color saturation regulatory factor precalculated.
7. according to the method described in claim 6, it is characterized in that, the calculating of the color saturation regulatory factor precalculated
Method, comprising:
Color saturation normalized is carried out to the original image；
The upper limit value and lower limit value of color saturation are determined according to the distribution probability of the image color saturation after normalized；
The first color saturation regulatory factor is determined according to the upper limit value and the lower limit value；
The first color saturation regulatory factor and pre-set second color saturation regulatory factor are modified, institute is obtained
State the color saturation regulatory factor precalculated.
8. a kind of image defogging processing system, which is characterized in that the system comprises:
Original image obtains module, for obtaining the original image to defogging；
HIS image conversion module, for the original image to be converted into HIS image；
Defogging module, for carrying out defogging processing to the HIS image using the transmissivity precalculated, after obtaining defogging
HIS image；
Final mist elimination image obtains module, for carrying out brightness, color saturation and tone tune to the HIS image after the defogging
Section, obtains final mist elimination image.
9. a kind of computer equipment including memory, processor and stores the meter that can be run on a memory and on a processor
Calculation machine program, which is characterized in that the processor realizes any one of claims 1 to 7 institute when executing the computer program
The step of stating method.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of any one of claims 1 to 7 the method is realized when being executed by processor.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110648297A (en) * | 2019-09-26 | 2020-01-03 | 邓诗雨 | Image defogging method and system, electronic equipment and storage medium |
| CN112488954A (en) * | 2020-12-07 | 2021-03-12 | 江苏理工学院 | Self-adaptive image enhancement method and device based on image gray level |
| WO2022213372A1 (en) * | 2021-04-09 | 2022-10-13 | 深圳市大疆创新科技有限公司 | Image dehazing method and apparatus, and electronic device and computer-readable medium |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102663694A (en) * | 2012-03-30 | 2012-09-12 | 大连理工大学 | Digital fog effect filter method based on dark primary color channel prior principle |
| CN102968772A (en) * | 2012-12-04 | 2013-03-13 | 电子科技大学 | Image defogging method based on dark channel information |
| US20130071043A1 (en) * | 2011-09-08 | 2013-03-21 | Fujitsu Limited | Image defogging method and system |
| CN104252698A (en) * | 2014-06-25 | 2014-12-31 | 西南科技大学 | Semi-inverse method-based rapid single image dehazing algorithm |
| CN104715239A (en) * | 2015-03-12 | 2015-06-17 | 哈尔滨工程大学 | Vehicle color identification method based on defogging processing and weight blocking |
| CN104978719A (en) * | 2015-06-16 | 2015-10-14 | 浙江工业大学 | Self-adaptive traffic video real-time defogging method based on temporal-spatial coherence |
| CN105118027A (en) * | 2015-07-28 | 2015-12-02 | 北京航空航天大学 | Image defogging method |
| CN105608683A (en) * | 2016-03-11 | 2016-05-25 | 北京理工大学 | Defogging method of single image |
| CN105631829A (en) * | 2016-01-15 | 2016-06-01 | 天津大学 | Night haze image defogging method based on dark channel prior and color correction |
| CN106127715A (en) * | 2016-08-29 | 2016-11-16 | 程建 | A kind of image defogging method and system |
| CN106886985A (en) * | 2017-04-25 | 2017-06-23 | 哈尔滨工业大学 | A kind of self adaptation enhancement method of low-illumination image for reducing colour cast |
| CN107424198A (en) * | 2017-07-27 | 2017-12-01 | 广东欧珀移动通信有限公司 | Image processing method, device, mobile terminal and computer-readable recording medium |
| CN107886480A (en) * | 2017-11-06 | 2018-04-06 | 北方工业大学 | Image defogging method based on V system |
| CN107977941A (en) * | 2017-12-04 | 2018-05-01 | 国网山东省电力公司电力科学研究院 | A kind of bright areas color fidelity and the image defogging method of contrast enhancing |
| CN108133462A (en) * | 2017-12-08 | 2018-06-08 | 泉州装备制造研究所 | A kind of restored method of the single image based on gradient fields region segmentation |
| CN108389175A (en) * | 2018-04-26 | 2018-08-10 | 长安大学 | Merge the image defogging method of variogram and color decaying priori |
| CN108416745A (en) * | 2018-02-02 | 2018-08-17 | 中国科学院西安光学精密机械研究所 | A kind of image adaptive defogging Enhancement Method with color constancy |
| CN108416739A (en) * | 2018-01-16 | 2018-08-17 | 辽宁师范大学 | Traffic image defogging method based on non-down sampling contourlet and Markov random field |
| CN108876743A (en) * | 2018-06-26 | 2018-11-23 | 中山大学 | A kind of image rapid defogging method, system, terminal and storage medium |
-
2019
- 2019-06-05 CN CN201910485387.7A patent/CN110175967B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130071043A1 (en) * | 2011-09-08 | 2013-03-21 | Fujitsu Limited | Image defogging method and system |
| CN102663694A (en) * | 2012-03-30 | 2012-09-12 | 大连理工大学 | Digital fog effect filter method based on dark primary color channel prior principle |
| CN102968772A (en) * | 2012-12-04 | 2013-03-13 | 电子科技大学 | Image defogging method based on dark channel information |
| CN104252698A (en) * | 2014-06-25 | 2014-12-31 | 西南科技大学 | Semi-inverse method-based rapid single image dehazing algorithm |
| CN104715239A (en) * | 2015-03-12 | 2015-06-17 | 哈尔滨工程大学 | Vehicle color identification method based on defogging processing and weight blocking |
| CN104978719A (en) * | 2015-06-16 | 2015-10-14 | 浙江工业大学 | Self-adaptive traffic video real-time defogging method based on temporal-spatial coherence |
| CN105118027A (en) * | 2015-07-28 | 2015-12-02 | 北京航空航天大学 | Image defogging method |
| CN105631829A (en) * | 2016-01-15 | 2016-06-01 | 天津大学 | Night haze image defogging method based on dark channel prior and color correction |
| CN105608683A (en) * | 2016-03-11 | 2016-05-25 | 北京理工大学 | Defogging method of single image |
| CN106127715A (en) * | 2016-08-29 | 2016-11-16 | 程建 | A kind of image defogging method and system |
| CN106886985A (en) * | 2017-04-25 | 2017-06-23 | 哈尔滨工业大学 | A kind of self adaptation enhancement method of low-illumination image for reducing colour cast |
| CN107424198A (en) * | 2017-07-27 | 2017-12-01 | 广东欧珀移动通信有限公司 | Image processing method, device, mobile terminal and computer-readable recording medium |
| CN107886480A (en) * | 2017-11-06 | 2018-04-06 | 北方工业大学 | Image defogging method based on V system |
| CN107977941A (en) * | 2017-12-04 | 2018-05-01 | 国网山东省电力公司电力科学研究院 | A kind of bright areas color fidelity and the image defogging method of contrast enhancing |
| CN108133462A (en) * | 2017-12-08 | 2018-06-08 | 泉州装备制造研究所 | A kind of restored method of the single image based on gradient fields region segmentation |
| CN108416739A (en) * | 2018-01-16 | 2018-08-17 | 辽宁师范大学 | Traffic image defogging method based on non-down sampling contourlet and Markov random field |
| CN108416745A (en) * | 2018-02-02 | 2018-08-17 | 中国科学院西安光学精密机械研究所 | A kind of image adaptive defogging Enhancement Method with color constancy |
| CN108389175A (en) * | 2018-04-26 | 2018-08-10 | 长安大学 | Merge the image defogging method of variogram and color decaying priori |
| CN108876743A (en) * | 2018-06-26 | 2018-11-23 | 中山大学 | A kind of image rapid defogging method, system, terminal and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 王建新: ""基于HIS空间的单幅图像去雾算法研究"", 《信息科技辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110648297A (en) * | 2019-09-26 | 2020-01-03 | 邓诗雨 | Image defogging method and system, electronic equipment and storage medium |
| CN112488954A (en) * | 2020-12-07 | 2021-03-12 | 江苏理工学院 | Self-adaptive image enhancement method and device based on image gray level |
| CN112488954B (en) * | 2020-12-07 | 2023-09-22 | 江苏理工学院 | Adaptive image enhancement method and device based on image gray level |
| WO2022213372A1 (en) * | 2021-04-09 | 2022-10-13 | 深圳市大疆创新科技有限公司 | Image dehazing method and apparatus, and electronic device and computer-readable medium |
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