CN106683108A - Method and apparatus for determining the flat areas of video frame and electronic device - Google Patents
Method and apparatus for determining the flat areas of video frame and electronic device Download PDFInfo
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- CN106683108A CN106683108A CN201611115260.9A CN201611115260A CN106683108A CN 106683108 A CN106683108 A CN 106683108A CN 201611115260 A CN201611115260 A CN 201611115260A CN 106683108 A CN106683108 A CN 106683108A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
Abstract
The embodiments of the invention relate to the technical field of video image processing and more particularly, to a method and an apparatus for determining the flat areas of a video frame and an electronic device. The method comprises the following steps: determining the image area of a to-be-processed video frame; dividing the image area into a plurality of sub-areas; calculating the noise parameter values of the pixel points in each sub-area; according to the noise parameter values of the pixels in each sub-area, determining the pixel points at the non-image edges of each sub-area; calculating the average noise parameter value of the pixel points at the non-image edges of each sub-area and the average noise parameter value of all the pixel points of each sub-area; and according to the average noise parameter value of the pixel points at the non-image edges of each sub-area and the average noise parameter value of all the pixel points of each sub-area, determining the flat areas from the plurality of sub-areas. The method and the apparatus for determining the flat areas of video frame and the electronic device proposed by the invention are capable of increasing the efficiency to determine the flat areas in a video frame.
Description
Technical field
The present embodiments relate to flat site in technical field of video image processing, more particularly to a kind of determination frame of video
Method, device and electronic equipment.
Background technology
In the treatment technology of video image, it is often necessary to detect the noise grade of video frame images.Current detection side
Formula mainly includes：Target area is determined in pending frame of video, according to the noise parameter of each pixel in target area
Value determines the noise in pending frame of video.
In the noise in detecting video frame images, it is important to the target area is determined from pending frame of video, its
In, the target area refers to the relatively low region of color complexity, meets desired target area and is referred to as flat site.
It is of the prior art to determine that the mode of flat site includes in the video frame：A pixel is arbitrarily chosen from frame of video, is sentenced
Whether the noise parameter value of the disconnected pixel is less than given threshold, if it is less, the pixel is defined as into target pixel points；
The noise parameter value that will be distributed over the pixel around the target pixel points compares with the given threshold respectively, and by noise
Parameter value is less than the point of the given threshold as target pixel points ... the like, and the target pixel points institute that will be determined
The region of composition is used as target area.
Inventor realize it is of the invention during find, flat site in the determination frame of video for using in the prior art
Method, treatment effeciency compares relatively low.
The content of the invention
A kind of method for determining flat site in frame of video, device and electronic equipment are provided in the embodiment of the present invention, with
Flat site efficiency comparison is low in solving the problems, such as to determine frame of video in the prior art.
The embodiment of the invention discloses following technical scheme：
In a first aspect, a kind of method for determining flat site in frame of video is the embodiment of the invention provides, including：
Determine the image-region of pending frame of video；
It is many sub-regions by described image region division；
Calculate the noise parameter value of each pixel in each described subregion；
According to the noise parameter value of each pixel in each described subregion, the non-figure in each described subregion is determined
As edge pixel point；
Calculate the noise parameter average value of non-image edge pixel point described in each described subregion and each described son
The noise parameter average value of all pixels point in region；
The noise parameter average value and each described son of the described non-image edge pixel point according to each subregion
The noise parameter average value of all pixels point, flat site is determined from the multiple subregion in region.
Optionally, the image-region for determining pending frame of video, including：
Determine the black surround region of the pending frame of video；
Part in the pending frame of video in addition to the black surround region is defined as described image region.
Optionally, the black surround region of the pending frame of video is determined, including：
Calculate in the pending frame of video the often pixel average of row pixel；
Calculate the pixel average of each column pixel in the pending frame of video；
Pixel average is defined as black surround region less than the row pixel and row pixel of first threshold.
Optionally, according to the noise parameter value of each pixel in each described subregion, it is determined that in per sub-regions
Non-image edge pixel point, including：
Judge the noise parameter value of the pixel whether less than or equal to Second Threshold；
If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is non-image edge
Pixel.
Optionally, the noise parameter average value of the described non-image edge pixel point according to each subregion and each
The noise parameter average value of all pixels point in the subregion, determines flat site from the multiple subregion, including：
Chosen from the multiple subregion and meet pre-conditioned subregion, it is described it is pre-conditioned including：Non-image side
The noise parameter average value of edge pixel is more than or equal to the 3rd threshold value, and, the noise parameter of all pixels point in subregion
Average value is in setting span；
The noise parameter average value that non-image edge pixel point is chosen from the pre-conditioned subregion is met is minimum
Subregion as the flat site.
Second aspect, the embodiment of the invention provides a kind of device for determining flat site in frame of video, including：Determine mould
Block, division module and computing module；
The determining module, the image-region for determining pending frame of video；
The division module, for being many sub-regions by described image region division；
The computing module, the noise parameter value for calculating each pixel in each described subregion；
The determining module, is additionally operable to the noise parameter value according to each pixel in each subregion, it is determined that often
Non-image edge pixel point in the individual subregion；
The computing module, is additionally operable to calculate the noise parameter of non-image edge pixel point described in each described subregion
The noise parameter average value of all pixels point in average value and each described subregion；
The determining module, is additionally operable to the noise parameter of the described non-image edge pixel point according to each subregion
The noise parameter average value of all pixels point, determines flat from the multiple subregion in average value and each described subregion
Region.
Optionally, the determining module determines the image-region of pending frame of video, specifically includes execution：
Determine the black surround region of the pending frame of video；
Part in the pending frame of video in addition to the black surround region is defined as described image region.
Optionally, the computing module, the pixel for being additionally operable to calculate often row pixel in the pending frame of video is average
Value；And, calculate the pixel average of each column pixel in the pending frame of video；
The determining module, is additionally operable to be defined as pixel average less than the row pixel and row pixel of first threshold
Black surround region.
Optionally, the determining module is according to the noise parameter value of each pixel in each described subregion, it is determined that often
Non-image edge pixel point in sub-regions, specifically includes execution：
Judge the noise parameter value of the pixel whether less than or equal to Second Threshold；
If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is non-image edge
Pixel.
Optionally, noise parameter of the determining module according to the described non-image edge pixel point of each subregion
The noise parameter average value of all pixels point, determines flat from the multiple subregion in average value and each described subregion
Region, specifically includes execution：
Chosen from the multiple subregion and meet pre-conditioned subregion, it is described it is pre-conditioned including：Non-image side
The noise parameter average value of edge pixel is more than or equal to the 3rd threshold value, and, the noise parameter of all pixels point in subregion
Average value is in setting span；
The noise parameter average value that non-image edge pixel point is chosen from the pre-conditioned subregion is met is minimum
Subregion as the flat site.
The third aspect, the embodiment of the invention provides a kind of electronic equipment, including：
At least one processor；And,
The memory being connected with least one processor communication；Wherein,
The memory storage has can be by the instruction of one computing device, and the instruction is by by described at least one
Computing device, so that at least one processor can：
Determine the image-region of pending frame of video；
It is many sub-regions by described image region division；
Calculate the noise parameter value of each pixel in each described subregion；
According to the noise parameter value of each pixel in each described subregion, the non-figure in each described subregion is determined
As edge pixel point；
Calculate the noise parameter average value of non-image edge pixel point described in each described subregion and each described son
The noise parameter average value of all pixels point in region；
The noise parameter average value and each described son of the described non-image edge pixel point according to each subregion
The noise parameter average value of all pixels point, flat site is determined from the multiple subregion in region.
Fourth aspect, the embodiment of the present invention additionally provides a kind of non-transient computer readable storage medium storing program for executing, described non-transient
Computer-readable recording medium storage computer instruction, the computer instruction is used to make the computer perform above-mentioned first party
The method of flat site in the determination frame of video that any one embodiment of face is provided.
5th aspect, the embodiment of the present invention additionally provides a kind of computer program product, the computer program product bag
Calculation procedure of the storage on non-transient computer readable storage medium storing program for executing is included, the computer program includes programmed instruction, works as institute
When stating programmed instruction and being computer-executed, make that the computer performs that above-mentioned any one embodiment of first aspect provides is described
The method of flat site in frame of video.
Technical scheme provided in an embodiment of the present invention can include the following benefits：
Embodiment of the present invention scheme is it is determined that during flat site in frame of video, it is first determined the image district in frame of video
Domain, and image-region is divided into many sub-regions, the non-image edge pixel point in determining per sub-regions afterwards, its
In, non-image edge pixel point refers to the improper pixel in frame of video, non-image edge in calculating per sub-regions afterwards
The noise parameter average value of all pixels point in the noise parameter average value of pixel and every sub-regions, and according to each height
The noise parameter of all pixels point is average in the noise parameter average value of the non-image edge pixel point in region and every sub-regions
Value determines flat site from many sub-regions.It can be seen that, embodiment of the present invention scheme is provided in a kind of new determination frame of video
The method of flat site, this kind of method can improve the efficiency for determining flat site in frame of video.
It should be appreciated that the general description of the above and detailed description hereinafter are only exemplary and explanatory, not
Can the limitation present invention.
Brief description of the drawings
Accompanying drawing herein is merged in specification and constitutes the part of this specification, shows and meets implementation of the invention
Example, and be used to explain principle of the invention together with specification.
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, for those of ordinary skill in the art
Speech, without having to pay creative labor, can also obtain other accompanying drawings according to these accompanying drawings.
One or more embodiments are illustrative by the picture in corresponding accompanying drawing, these exemplary theorys
The bright restriction not constituted to embodiment, the element with same reference numbers label is expressed as similar element in accompanying drawing, removes
It is non-to have especially statement, the figure not composition limitation in accompanying drawing.
Fig. 1 is the method flow diagram that the embodiment of the present invention one determines flat site in frame of video；
Fig. 2 is the method flow diagram that the embodiment of the present invention two determines flat site in frame of video；
Fig. 3 is the apparatus structure schematic diagram that the embodiment of the present invention three determines flat site in frame of video；
Fig. 4 is the hardware architecture diagram of embodiment of the present invention electronic equipment.
Specific embodiment
Here exemplary embodiment will be illustrated in detail, its example is illustrated in the accompanying drawings.Following description is related to
During accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawings represent same or analogous key element.Following exemplary embodiment
Described in implementation method do not represent and the consistent all implementation methods of the present invention.Conversely, they be only with it is such as appended
The example of the consistent apparatus and method of some aspects being described in detail in claims, of the invention.
In the fields such as video playback, video monitoring, it is often necessary to detect the noise grade of video image.In detection video
During the noise grade of image, it is important to determine the flat site in frame of video, that is, color complexity is relative in determining frame of video
Than relatively low region, in the prior art it is determined that during flat site in frame of video, more by the way of unrestrained growth, the effect for the treatment of
Rate compares relatively low.The treatment effeciency of flat site in frame of video is determined to improve, be the embodiment of the invention provides a kind of true
Determine the scheme of flat site in frame of video, determine the side of flat site in frame of video to the embodiment of the present invention below with reference to accompanying drawing
Method is described in detail.
Embodiment one
Fig. 1 is the method flow diagram that the embodiment of the present invention one determines flat site in frame of video.As shown in figure 1, the method
Process step include：
Step S101：Determine the image-region of pending frame of video.
When processing pending frame of video, it is first determined the image-region in pending video, such as what is had regards
Frequency frame has black surround, and the black surround in frame of video is typically what the later stage added up, when processing pending frame of video, it is first determined treat
The black surround region of frame of video is processed, and the part in pending frame of video in addition to the black surround region is defined as image district
Domain.
Step S102：It is many sub-regions by described image region division.
Determine after the image-region in pending frame of video, image-region is divided into many sub-regions, optionally, will
Described image region is divided into many sub-regions, for example, image-region is divided into 8 parts, 16 parts, 32 parts etc..
Step S103：Calculate the noise parameter value of each pixel in each described subregion.
Wherein, the noise parameter value of pixel can be the Grad of pixel, specifically, according to the Grad of pixel
Can determine that respective pixel point is noise, and noise intensity.In embodiment of the present invention scheme, pixel ladder is calculated
The method of angle value has various, it is for instance possible to use Sobel, Prewitt algorithm calculate the Grad of pixel.Optionally, can be with
The Grad of pixel is calculated using Sobel algorithms, the Grad for calculating pixel using Sobel algorithms can reduce calculating
Amount.
Step S104：According to the noise parameter value of each pixel in each described subregion, each described sub-district is determined
Non-image edge pixel point in domain.
In embodiment of the present invention scheme, noise parameter value and the predetermined threshold value of each pixel are compared, work as picture
The noise parameter value of vegetarian refreshments determines that the pixel, for normal image edge pixels point, works as pixel when being less than the predetermined threshold value
Noise parameter value be more than or equal to the predetermined threshold value when, determine the pixel be non-image edge pixel point.
Step S105：Calculate the noise parameter average value of non-image edge pixel point described in each described subregion and every
The noise parameter average value of all pixels point in the individual subregion.
Step S106：The noise parameter average value of the described non-image edge pixel point according to each subregion and every
The noise parameter average value of all pixels point, flat site is determined from the multiple subregion in the individual subregion.
In embodiment of the present invention scheme, the noise parameter of non-image edge pixel point is average in calculating per sub-regions
Value, wherein, the noise parameter average value according to non-image edge pixel point can determine whether filled in corresponding subregion
Have powerful connections color, and the noise parameter average value according to all pixels point in subregion can exclude bright or excessively dark subregion.Tool
Body, the noise parameter average value and each described subregion of the described non-image edge pixel point according to each subregion
The noise parameter average value of middle all pixels point, flat site is determined from the multiple subregion.
Using present invention method, color complexity can be selected from frame of video with treatment effeciency relatively higher
Relatively low region compare as flat site.
Embodiment two
Fig. 2 is the method flow diagram that the embodiment of the present invention two determines flat site in frame of video.As shown in Fig. 2 the method
Process step include：
Step S201：Determine the black surround region of pending frame of video.
In embodiment of the present invention scheme, when flat site is determined from pending frame of video, it is first determined pending
Image-region in frame of video.
In actual application scenarios, depositing the later stage in some frame of video is added with black surround, in order to determine pending frame of video
In image-region, it is first determined the black surround region in pending frame of video.
Optionally, in embodiment of the present invention scheme, determining the black surround region of pending frame of video includes：Treated described in calculating
The pixel average of every row pixel in treatment frame of video；The pixel for calculating each column pixel in the pending frame of video is average
Value；Pixel average is defined as black surround region less than the row pixel and row pixel of first threshold.
Step S202：Part in pending frame of video in addition to the black surround region is defined as described image region.
Step S203：Image-region is divided into many sub-regions.Image-region is divided into many sub-regions, it is therefore an objective to
It is that one of them in many sub-regions is defined as flat site.In equal portions image-region, can be by image-region decile
It is 8 parts, 16 parts, 32 parts etc..
Step S204：Calculate the noise parameter value of each pixel in each described subregion.
Wherein, the noise parameter value of pixel can be the Grad of pixel, specifically, according to the Grad of pixel
Can determine that respective pixel point is noise, and noise intensity.In embodiment of the present invention scheme, pixel ladder is calculated
The method of angle value has various, it is for instance possible to use Sobel, Prewitt algorithm calculate the Grad of pixel.Optionally, can be with
The Grad of pixel is calculated using Sobel algorithms, the Grad for calculating pixel using Sobel algorithms can reduce calculating
Amount.
Step S205：According to the noise parameter value of each pixel in each described subregion, it is determined that in per sub-regions
Non-image edge pixel point.
In embodiment of the present invention scheme, noise parameter value and the predetermined threshold value of each pixel are compared, work as picture
The noise parameter value of vegetarian refreshments determines that the pixel, for normal image edge pixels point, works as pixel when being less than the predetermined threshold value
Noise parameter value be more than or equal to the predetermined threshold value when, determine the pixel be non-image edge pixel point.Specifically, determining
One pixel is that the method for non-image edge pixel point includes：Judge whether the noise parameter value of the pixel is less than
Or equal to Second Threshold；If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is non-
Image edge pixels point.
Step S206：Calculate the noise parameter average value of non-image edge pixel point described in every sub-regions and per height
The noise parameter average value of all pixels point in region.
Step S207：Chosen from the multiple subregion and meet pre-conditioned subregion, it is described it is pre-conditioned including：
The noise parameter average value of non-image edge pixel point is more than or equal to the 3rd threshold value, and, all pixels point in subregion
Noise parameter average value is in setting span.
Step S208：The noise parameter that non-image edge pixel point is chosen from the pre-conditioned subregion is met is put down
The minimum subregion of average is used as the flat site.
In embodiment of the present invention scheme, the noise parameter of non-image edge pixel point is average in calculating per sub-regions
Value, wherein, whether the noise parameter average value of non-image edge pixel point is judged more than or equal to the 3rd threshold value, when a sub-district
When the noise parameter average value of the non-image edge pixel point in domain is more than or equal to three threshold values, it may be determined that corresponding subregion
In be effective edge pixel, rather than filled with background colour；Further, when the noise parameter of all pixels point in subregion is average
When setting in span, it was bright or excessively dark subregion that can exclude the subregion to value.
When meeting the pre-conditioned subregion and having multiple, choose non-image from pre-conditioned subregion is met
The minimum subregion of the noise parameter average value of edge pixel point is used as the flat site.All it is discontented with if all of subregion
Foot is described pre-conditioned, can directly abandon current video frame, it is also possible to non-image edge pixel is chosen from many sub-regions
The minimum subregion of the noise parameter average value of point is used as flat site.
Using present invention method, color complexity can be selected from frame of video with treatment effeciency relatively higher
Relatively low region compare as flat site.
Embodiment three
Fig. 3 is the apparatus structure schematic diagram that the embodiment of the present invention three determines flat site in frame of video.As shown in figure 3, should
Device includes：Determining module 301, division module 302 and computing module 303；
The determining module 301, the image-region for determining pending frame of video；
The division module 302, for being many sub-regions by described image region division；
The computing module 303, the noise parameter value for calculating each pixel in each described subregion；
The determining module 301, is additionally operable to the noise parameter value according to each pixel in each subregion, it is determined that
Non-image edge pixel point in per sub-regions；
The computing module 303, is additionally operable to calculate the noise parameter of non-image edge pixel point described in every sub-regions
The noise parameter average value of all pixels point in average value and every sub-regions；
The determining module 301, is additionally operable to the noise of the described non-image edge pixel point according to each subregion
The noise parameter average value of all pixels point in mean parameter and each described subregion, determines from the multiple subregion
Flat site.
Optionally, the determining module 301 determines the image-region of pending frame of video, specifically includes execution：Determine institute
State the black surround region of pending frame of video；Part in the pending frame of video in addition to the black surround region is defined as described
Image-region.
Optionally, the computing module 303, is additionally operable to calculate in the pending frame of video that often the pixel of row pixel is put down
Average；And, calculate the pixel average of each column pixel in the pending frame of video；The determining module 301, is additionally operable to
Pixel average is defined as black surround region less than the row pixel and row pixel of first threshold.
Optionally, described image region division is many sub-regions by the division module 302, specifically includes execution：Will
Described image region is divided into many sub-regions.
Optionally, the determining module 301 is according to the noise parameter value of each pixel in each described subregion, it is determined that
Non-image edge pixel point in per sub-regions, specifically includes execution：Judge whether the noise parameter value of the pixel is small
In or equal to Second Threshold；If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is
Non-image edge pixel point.
Optionally, the noise parameter value is the Grad of pixel.
Optionally, noise of the determining module 301 according to the described non-image edge pixel point of each subregion
The noise parameter average value of all pixels point in mean parameter and each described subregion, determines from the multiple subregion
Flat site, specifically includes execution：Chosen from the multiple subregion and meet pre-conditioned subregion, it is described pre-conditioned
Including：The noise parameter average value of non-image edge pixel point is more than or equal to the 3rd threshold value, and, all pixels in subregion
The noise parameter average value of point is in setting span；Non-image edge is chosen from the pre-conditioned subregion is met
The minimum subregion of the noise parameter average value of pixel is used as the flat site.
Using present invention method, color complexity can be selected from frame of video with treatment effeciency relatively higher
Relatively low region compare as flat site.
Example IV
The embodiment of the invention provides a kind of non-transient computer storage medium, the computer-readable storage medium is stored with meter
Calculation machine executable instruction, the computer can perform the side of flat site in the determination frame of video in above-mentioned any means embodiment
Method.
One of ordinary skill in the art will appreciate that all or part of flow in realizing above-described embodiment method, can be
The hardware of correlation is instructed to complete by computer program, described program can be stored in a computer read/write memory medium
In, the program is upon execution, it may include such as the flow of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random
AccessMemory, RAM) etc..
Embodiment five
Fig. 4 is the hard of the electronic equipment of the method that the execution that the embodiment of the present invention five is provided determines flat site in frame of video
Part structural representation, as shown in figure 4, the equipment includes：
One or more processors 410 and memory 420, in Fig. 4 by taking a processor 410 as an example.
The equipment for performing the method for determining flat site in frame of video can also include：Input unit 430 and output device
440。
Processor 410, memory 420, input unit 430 and output device 440 can be by bus or other modes
Connection, in Fig. 4 as a example by being connected by bus.
Memory 420 can be used to store non-volatile software journey as a kind of non-volatile computer readable storage medium storing program for executing
Sequence, non-volatile computer executable program and module, flat site in the determination frame of video such as in the embodiment of the present application
Corresponding programmed instruction/the module of method is (for example, determining module 301, division module 302 and computing module shown in accompanying drawing 3
303).Processor 410 is by running the non-volatile software program stored in memory 420, instructing and module, so as to hold
The various function application of row server and data processing, that is, realize that above method embodiment determines flat site in frame of video
Method.
Memory 420 can include storing program area and storage data field, wherein, storing program area can store operation system
Application program required for system, at least one function；Storage data field can be stored according to the dress for determining flat site in frame of video
That puts uses created data etc..Additionally, memory 420 can include high-speed random access memory, can also include non-
Volatile memory, for example, at least one disk memory, flush memory device or other non-volatile solid state memory parts.
In some embodiments, memory 420 is optional including the memory remotely located relative to processor 410, these remote memories
Can be by network connection to the device for determining flat site in frame of video.The example of above-mentioned network includes but is not limited to interconnection
Net, intranet, LAN, mobile radio communication and combinations thereof.
Input unit 430 can receive the numeral or character information of input, and produce the processing unit with list items operation
User set and function control it is relevant key signals input.Output device 440 may include the display devices such as display screen.
One or more of modules are stored in the memory 420, when by one or more of processors
During 410 execution, the method for performing flat site in the determination frame of video in above-mentioned any means embodiment.
The method that the executable the embodiment of the present application of the said goods is provided, possesses the corresponding functional module of execution method and has
Beneficial effect.Not ins and outs of detailed description in the present embodiment, reference can be made to the method that the embodiment of the present application is provided.
The electronic equipment of the embodiment of the present application exists in a variety of forms, including but not limited to:
(1) mobile communication equipment:The characteristics of this kind equipment is that possess mobile communication function, and to provide speech, data
It is main target to communicate.This Terminal Type includes:Smart mobile phone (such as iPhone), multimedia handset, feature mobile phone, and it is low
End mobile phone etc..
(2) super mobile personal computer equipment:This kind equipment belongs to the category of personal computer, there is calculating and treatment work(
Can, typically also possess mobile Internet access characteristic.This Terminal Type includes:PDA, MID and UMPC equipment etc., such as iPad.
(3) portable entertainment device:This kind equipment can show and play content of multimedia.The kind equipment includes:Audio,
Video player (such as iPod), handheld device, e-book, and intelligent toy and portable car-mounted navigation equipment.
(4) server:The equipment for providing the service of calculating, the composition of server includes that processor, hard disk, internal memory, system are total
Line etc., server is similar with general computer architecture, but due to needing to provide highly reliable service, therefore in treatment energy
The requirement of the aspects such as power, stability, reliability, security, scalability, manageability is higher.
(5) other have the electronic installation of data interaction function.
Device embodiment described above is only schematical, wherein the unit illustrated as separating component can
To be or may not be physically separate, the part shown as unit can be or may not be physics list
Unit, you can with positioned at a place, or can also be distributed on multiple NEs.It can according to the actual needs be selected
In some or all of module realize the purpose of this embodiment scheme.
Through the above description of the embodiments, those skilled in the art can be understood that each implementation method can
Realized by the mode of software plus general hardware platform, naturally it is also possible to by hardware.Based on such understanding, above-mentioned technology
The part that scheme substantially contributes to correlation technique in other words can be embodied in the form of software product, the computer
Software product can be stored in a computer-readable storage medium, and such as ROM/RAM, magnetic disc, CD, including some instructions are used to
So that computer equipment (can be personal computer, server, or network equipment etc.) perform each embodiment or
Method described in some parts of embodiment.
Finally it should be noted that：Above example is only used to illustrate the technical scheme of the application, rather than its limitations；Although
The application has been described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：It still may be used
Modified with to the technical scheme described in foregoing embodiments, or equivalent is carried out to which part technical characteristic；
And these modification or replace, do not make appropriate technical solution essence depart from each embodiment technical scheme of the application spirit and
Scope.
Claims (11)
1. it is a kind of determine frame of video in flat site method, it is characterised in that including：
Determine the image-region of pending frame of video；
It is many sub-regions by described image region division；
Calculate the noise parameter value of each pixel in each described subregion；
According to the noise parameter value of each pixel in each described subregion, the non-image side in each described subregion is determined
Edge pixel；
Calculate the noise parameter average value of non-image edge pixel point described in each described subregion and each described subregion
The noise parameter average value of middle all pixels point；
The noise parameter average value and each described subregion of the described non-image edge pixel point according to each subregion
The noise parameter average value of middle all pixels point, flat site is determined from the multiple subregion.
2. method according to claim 1, it is characterised in that the image-region of the pending frame of video of determination, including：
Determine the black surround region of the pending frame of video；
Part in the pending frame of video in addition to the black surround region is defined as described image region.
3. method according to claim 2, it is characterised in that determine the black surround region of the pending frame of video, including：
Calculate in the pending frame of video the often pixel average of row pixel；
Calculate the pixel average of each column pixel in the pending frame of video；
Pixel average is defined as black surround region less than the row pixel and row pixel of first threshold.
4. method according to claim 1, it is characterised in that according to the noise of each pixel in each described subregion
Parameter value, it is determined that the non-image edge pixel point in per sub-regions, including：
Judge the noise parameter value of the pixel whether less than or equal to Second Threshold；
If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is non-image edge pixel
Point.
5. method according to any one of claim 1 to 4, it is characterised in that according to each described subregion
The noise parameter average value of all pixels point in the noise parameter average value and each described subregion of non-image edge pixel point,
Flat site is determined from the multiple subregion, including：
Chosen from the multiple subregion and meet pre-conditioned subregion, it is described it is pre-conditioned including：Non-image edge picture
The noise parameter average value of vegetarian refreshments is more than or equal to the 3rd threshold value, and, the noise parameter of all pixels point is average in subregion
Value is in setting span；
The minimum son of the noise parameter average value of non-image edge pixel point is chosen from the pre-conditioned subregion is met
Region is used as the flat site.
6. it is a kind of determine frame of video in flat site device, it is characterised in that including：Determining module, division module and calculating
Module；
The determining module, the image-region for determining pending frame of video；
The division module, for being many sub-regions by described image region division；
The computing module, the noise parameter value for calculating each pixel in each described subregion；
The determining module, is additionally operable to the noise parameter value according to each pixel in each subregion, determines each institute
State the non-image edge pixel point in subregion；
The computing module, the noise parameter for being additionally operable to calculate non-image edge pixel point described in each described subregion is average
The noise parameter average value of all pixels point in value and each described subregion；
The determining module, the noise parameter for being additionally operable to described non-image edge pixel point according to each subregion is average
The noise parameter average value of all pixels point, flat region is determined from the multiple subregion in value and each described subregion
Domain.
7. device according to claim 6, it is characterised in that the determining module determines the image district of pending frame of video
Domain, specifically includes execution：
Determine the black surround region of the pending frame of video；
Part in the pending frame of video in addition to the black surround region is defined as described image region.
8. device according to claim 7, it is characterised in that the computing module, is additionally operable to calculate described pending regard
The every pixel average of row pixel in frequency frame；And, the pixel for calculating each column pixel in the pending frame of video is average
Value；
The determining module, is additionally operable to for pixel average to be defined as black surround less than the row pixel and row pixel of first threshold
Region.
9. device according to claim 6, it is characterised in that the determining module according in each described subregion each
The noise parameter value of pixel, it is determined that the non-image edge pixel point in per sub-regions, specifically includes execution：
Judge the noise parameter value of the pixel whether less than or equal to Second Threshold；
If the noise parameter value of the pixel is less than or equal to Second Threshold, the pixel is non-image edge pixel
Point.
10. the device according to any one of claim 6 to 9, it is characterised in that the determining module is according to each
All pixels point makes an uproar in the noise parameter average value and each described subregion of the described non-image edge pixel point of subregion
Sound mean parameter, flat site is determined from the multiple subregion, specifically includes execution：
Chosen from the multiple subregion and meet pre-conditioned subregion, it is described it is pre-conditioned including：Non-image edge picture
The noise parameter average value of vegetarian refreshments is more than or equal to the 3rd threshold value, and, the noise parameter of all pixels point is average in subregion
Value is in setting span；
The minimum son of the noise parameter average value of non-image edge pixel point is chosen from the pre-conditioned subregion is met
Region is used as the flat site.
11. a kind of electronic equipment, including：
At least one processor；And,
The memory being connected with least one processor communication；Wherein,
The memory storage has can be processed by the instruction of one computing device, the instruction by described at least one
Device is performed, so that at least one processor can：
Determine the image-region of pending frame of video；
It is many sub-regions by described image region division；
Calculate the noise parameter value of each pixel in each described subregion；
According to the noise parameter value of each pixel in each described subregion, the non-image side in each described subregion is determined
Edge pixel；
Calculate the noise parameter average value of non-image edge pixel point described in each described subregion and each described subregion
The noise parameter average value of middle all pixels point；
The noise parameter average value and each described subregion of the described non-image edge pixel point according to each subregion
The noise parameter average value of middle all pixels point, flat site is determined from the multiple subregion.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109089121A (en) * | 2018-10-19 | 2018-12-25 | 北京金山云网络技术有限公司 | A kind of method for estimating based on Video coding, device and electronic equipment |
| CN110083740A (en) * | 2019-05-07 | 2019-08-02 | 深圳市网心科技有限公司 | Video finger print extracts and video retrieval method, device, terminal and storage medium |
| CN111046727A (en) * | 2019-10-31 | 2020-04-21 | 咪咕文化科技有限公司 | Video feature extraction method and device, electronic equipment and storage medium |
| CN111062878A (en) * | 2019-10-31 | 2020-04-24 | 深圳先进技术研究院 | Image denoising method and device and computer readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103079028A (en) * | 2011-10-25 | 2013-05-01 | 联咏科技股份有限公司 | Black edge detection method for image picture and image processing device |
| CN104134191A (en) * | 2014-07-11 | 2014-11-05 | 三星电子（中国）研发中心 | Image denoising method and image denoising device |
| CN104778669A (en) * | 2015-04-16 | 2015-07-15 | 北京邮电大学 | Fast image denoising method and device |
-
2016
- 2016-12-07 CN CN201611115260.9A patent/CN106683108A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103079028A (en) * | 2011-10-25 | 2013-05-01 | 联咏科技股份有限公司 | Black edge detection method for image picture and image processing device |
| CN104134191A (en) * | 2014-07-11 | 2014-11-05 | 三星电子（中国）研发中心 | Image denoising method and image denoising device |
| CN104778669A (en) * | 2015-04-16 | 2015-07-15 | 北京邮电大学 | Fast image denoising method and device |
Non-Patent Citations (2)
| Title |
|---|
| 冷璐等: "高边界精度和抗噪的均值漂移图像分割算法", 《计算机工程与设计》 * |
| 史雪静等: "保持边缘细节的SAR图像斑点噪声抑制方法", 《遥感信息》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109089121A (en) * | 2018-10-19 | 2018-12-25 | 北京金山云网络技术有限公司 | A kind of method for estimating based on Video coding, device and electronic equipment |
| CN109089121B (en) * | 2018-10-19 | 2021-06-22 | 北京金山云网络技术有限公司 | Motion estimation method and device based on video coding and electronic equipment |
| CN110083740A (en) * | 2019-05-07 | 2019-08-02 | 深圳市网心科技有限公司 | Video finger print extracts and video retrieval method, device, terminal and storage medium |
| CN110083740B (en) * | 2019-05-07 | 2021-04-06 | 深圳市网心科技有限公司 | Video fingerprint extraction and video retrieval method, device, terminal and storage medium |
| CN111046727A (en) * | 2019-10-31 | 2020-04-21 | 咪咕文化科技有限公司 | Video feature extraction method and device, electronic equipment and storage medium |
| CN111062878A (en) * | 2019-10-31 | 2020-04-24 | 深圳先进技术研究院 | Image denoising method and device and computer readable storage medium |
| CN111062878B (en) * | 2019-10-31 | 2023-04-18 | 深圳先进技术研究院 | Image denoising method and device and computer readable storage medium |
| CN111046727B (en) * | 2019-10-31 | 2023-10-20 | 咪咕文化科技有限公司 | Video feature extraction method and device, electronic equipment and storage medium |
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