CN106303156B - To the method, device and mobile terminal of video denoising - Google Patents
To the method, device and mobile terminal of video denoising Download PDFInfo
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- CN106303156B CN106303156B CN201610750044.5A CN201610750044A CN106303156B CN 106303156 B CN106303156 B CN 106303156B CN 201610750044 A CN201610750044 A CN 201610750044A CN 106303156 B CN106303156 B CN 106303156B
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Abstract
The invention discloses method, application and the mobile terminals to video denoising.It include wherein image acquisition unit, noise grade calculating unit, smoothing factor computing unit, metrics calculation unit, weight calculation unit and luma processing unit to the application of video denoising.Image acquisition unit is suitable for obtaining the image frame sequence about video.Noise grade calculates the noise grade that unit is suitable for calculating each pixel to be denoised.Smoothing factor computing unit is suitable for noise grade and its brightness according to each pixel to be denoised, determines the brightness smoothing factor of this corresponding pixel to be denoised.Metrics calculation unit is suitable for calculating the pixel to be denoised at a distance from selected each associated pixel point based on block matching algorithm.Weight calculation unit is suitable for calculating the corresponding weight of each associated pixel point.Luma processing unit calculates all luminance weighted average values for being associated with pixel and the brightness through denoising as the pixel to be denoised for each pixel to be denoised.
Description
Technical field
The present invention relates to technical field of image processing, more particularly to the method to video denoising, application and mobile terminal.
Background technique
In the application scenarios of picture or video acquisition, acquired image unavoidably has signal noise.For example,
Captured picture or video usually have obvious noise in the scenes such as night.Image denoising is image procossing (single width figure
Piece processing or sequence of frames of video processing) in highly important link.
Currently, the processing mode of mainstream image denoising includes a variety of well known guarantor's side filtering algorithms, such as bilateral filtering side
Formula etc..When image frame sequence carries out denoising in video, traditional video denoising mode is to pixel in picture frame
Block- matching operation is carried out with its adjacent pixel on room and time, and then completes filtering operation.
Existing video denoising process usually requires to spend more time.In response to this, higher multimedia is configured
Equipment, which is passed through, carries out denoising acceleration frequently with hardware modes such as GPU.However, in a variety of portable electronic devices (such as mobile terminal
Deng) in using existing video denoising mode when, image denoising process needs take considerable time.
For this purpose, the invention proposes a kind of new technical solutions to video denoising.
Summary of the invention
For this purpose, the present invention provides a kind of new technical solution to video denoising, effective solution above at least one
Problem.
According to an aspect of the present invention, the method for a kind of pair of video denoising is provided, suitable for executing in the terminal.It should
Method includes the following steps.Obtain the image frame sequence about video.Calculate in each picture frame each pixel to be denoised
Noise grade.According to the noise grade and its brightness of each pixel to be denoised, the bright of this corresponding pixel to be denoised is determined
Spend smoothing factor.From each wait denoise in the multiple image adjacent with front and back of this frame locating for pixel, select and be somebody's turn to do picture to be denoised
The associated pixel of vegetarian refreshments, and based on block matching algorithm calculate the pixel to be denoised with select each associated pixel point away from
From.According to the brightness smoothing factor of each pixel to be denoised distance corresponding with pixel is each associated with, calculate each
The corresponding weight of associated pixel point.For each pixel to be denoised, according to each brightness and power for being associated with pixel
Weight calculates all luminance weighted average values for being associated with pixel and the brightness through denoising as the pixel to be denoised.
Optionally, in the method according to the present invention to video denoising, the step of the image frame sequence about video is obtained
It suddenly include: the original frame sequence for obtaining rgb pixel format sequentially in time；Brightness and coloration point are converted by original frame sequence
From sequence of data frames and as image frame sequence.
Optionally, in the method according to the present invention to video denoising, each picture to be denoised is calculated in each picture frame
The step of noise grade of vegetarian refreshments include: centered on the pixel to be denoised, select the image block of predetermined window size as
It should pixel neighborhood of a point block be denoised；The variance of brightness in the field block is calculated, to determine the noise etc. of the pixel to be denoised
Grade.
Optionally, in the method according to the present invention to video denoising, from each wait denoise this frame locating for pixel
In multiple image adjacent with front and back, selectes and be somebody's turn to do the associated pixel of pixel to be denoised, and being calculated based on block matching algorithm should
The step of pixel to be denoised is at a distance from selected each associated pixel point includes: the figure before counting the pixel to be denoised
Pixel similarity highest at least one in the pixel as associated by the pixel of corresponding position in frame, with corresponding position
Point；According to the positional relationship of the pixel of corresponding position and at least part pixel counted, selectes and be somebody's turn to do picture to be denoised
Vegetarian refreshments keeps the pixel of this positional relationship as pixel associated with the pixel to be denoised；Calculating should picture be denoised
Vegetarian refreshments is at a distance from each associated pixel.
Optionally, in the method according to the present invention to video denoising, calculate should pixel be denoised to it is each related
The pixel of connection apart from the step of include: obtain the pixel to be denoised neighborhood block to be matched about brightness feature to
Amount；Obtain feature vector of each associated pixel neighborhood of a point block about brightness；Calculate neighborhood block to be matched and each
Distance is as the corresponding distance of this associated pixel between the feature vector of associated pixel neighborhood of a point block.
Optionally, flat according to the brightness of each pixel to be denoised in the method according to the present invention to video denoising
Sliding coefficient and each the step of being associated with the corresponding distance of pixel, calculating each associated pixel point corresponding weight include
Following manner:
Wherein, x indicates that pixel to be denoised, y indicate a pixel associated with x,
||u(Nd(x))-u(Nd(y)) | | indicate x neighborhood block character pair vector and y character pair vector between away from
From d is the dimension of feature vector, and h indicates that the brightness smoothing factor of x, W (x) indicate corresponding with the associated all pixels of x
'sThe sum of, w (x, y) is the weight of y pixel.
Optionally, in the method according to the present invention to video denoising, for each pixel to be denoised, according to its
It is associated with the brightness and weight of each pixel, calculating is associated with the luminance weighted average value of pixel and as the picture to be denoised
The step of brightness through denoising of vegetarian refreshments includes following manner:
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the power of y pixel
Weight, u (y) indicate the brightness value of y.
Optionally, the method according to the present invention to video denoising further include: according to the smooth described image frame of following formula
The coloration of each pixel in sequence:
Wherein, ft(x) expression smoothed out chromatic value of pixel x on t frame image, exp (| | ut(x)-ut+Δ(x)|
|2Indicate on x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from, W (x) be with from-n
To the pixel of additional space position on all consecutive frames of n colour difference away from the sum of, ut+Δ(x) phase on Δ frame adjacent with x is indicated
The chromatic value of the pixel of spatial position is answered,Indicate the pixel of the additional space position
Chromatic value weight.
Another aspect according to the present invention provides the application of a kind of pair of video denoising, is suitable for being resident in the terminal, should
Unit, smoothing factor computing unit, metrics calculation unit, weight calculation are calculated using including image acquisition unit, noise grade
Unit and luma processing unit.Image acquisition unit is suitable for obtaining the image frame sequence about video.Noise grade calculates unit
Suitable for calculating in each picture frame each noise grade of pixel to be denoised.Smoothing factor computing unit be suitable for according to each to
The noise grade and its brightness of pixel are denoised, determines the brightness smoothing factor of this corresponding pixel to be denoised.Distance calculates
Unit is suitable for from each selecting wait denoise in the multiple image adjacent with front and back of this frame locating for pixel and being somebody's turn to do pixel to be denoised
Associated pixel, and the pixel to be denoised is calculated at a distance from selected each associated pixel point based on block matching algorithm.
Weight calculation unit is suitable for corresponding with each pixel is associated with according to each brightness smoothing factor of pixel to be denoised
Distance calculates the corresponding weight of each associated pixel point.Luma processing unit is suitable for root for each pixel to be denoised
According to each brightness and weight for being associated with pixel, all luminance weighted average values for being associated with pixel and conduct are calculated
The brightness through denoising of the pixel to be denoised.
Another aspect according to the present invention provides a kind of mobile terminal, answers including according to the present invention video denoising
With.
To sum up, noise-removed technology scheme according to the present invention can be selected accurately and the high picture of pixel similarity to be denoised
Vegetarian refreshments (in other words, excluding the low pixel of a large amount of similarities) is used as associated pixel point, and then is calculated really by Block- matching
The weight of fixed each associated pixel point.In addition, noise-removed technology scheme of the invention treat denoising pixel noise grade into
Row assessment, and then determine the brightness smoothing factor of corresponding noise grade.In conjunction with the noise grade and each it is associated each pixel
The weight and brightness of point, noise-removed technology scheme of the invention can will be luminance weighted with pixel associated pixel point to be denoised
Average value is as the brightness through denoising.It should be noted that noise-removed technology scheme of the invention can be to associated pixel point
It accurate selection (utilizing similar block transmitting operation) and excludes the very low pixel of similarity and (can ignore in denoising operation
Disregard), denoising speed can be greatly improved.In addition, noise-removed technology scheme of the invention quickly reduce noise while,
Still video details can be effectively maintained.In particular, when being applied to the portable multimedia apparatus such as mobile terminal, this hair
User experience can be greatly improved by efficiently completing denoising task in bright noise-removed technology scheme.
To individually wait denoise pixel for, it is that noise-removed technology scheme of the invention is accurately selected, associated there
Pixel (on this frame and before and after frames where pixel to be denoised) quantity has enough.Therefore, even if it is to be denoised
Pixel has very high noise grade, and noise-removed technology scheme of the invention can also obtain denoising effect well.
It is further to note that the broadcasting pictures through denoising rear video often have one kind not in existing denoising scheme
Continuous bounce sense.Noise-removed technology scheme of the invention can be carried out while be filtered to brightness and coloration, and video can be improved and broadcast
Put the fluency of picture.
Detailed description of the invention
To the accomplishment of the foregoing and related purposes, certain illustrative sides are described herein in conjunction with following description and drawings
Face, these aspects indicate the various modes that can practice principles disclosed herein, and all aspects and its equivalent aspect
It is intended to fall in the range of theme claimed.Read following detailed description in conjunction with the accompanying drawings, the disclosure it is above-mentioned
And other purposes, feature and advantage will be apparent.Throughout the disclosure, identical appended drawing reference generally refers to identical
Component or element.
Fig. 1 shows the schematic diagram of mobile terminal 100 according to some embodiments of the invention；
Fig. 2 shows the schematic diagrames of the application 200 to video denoising according to some embodiments of the invention；
Fig. 3 shows the schematic diagram of image frame sequence according to an embodiment of the invention；
Fig. 4 shows the schematic diagram of the application 400 to video denoising of other embodiment according to the present invention；
Fig. 5 shows the flow chart of the method 500 to video denoising according to some embodiments of the invention；
Fig. 6 shows a kind of flow chart of implementation method 600 of step S540 in Fig. 5；And
Fig. 7 shows the flow chart of the method 700 to video denoising according to some embodiments of the invention.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
It is fully disclosed to those skilled in the art.
Fig. 1 is the structural block diagram of mobile terminal 100.Mobile terminal 100 may include memory interface 102, one or more
A data processor, image processor and/or central processing unit 104 and peripheral interface 106.
Memory interface 102, one or more processors 104 and/or peripheral interface 106 either discrete component,
It can integrate in one or more integrated circuits.In the mobile terminal 100, various elements can pass through one or more communication
Bus or signal wire couple.Sensor, equipment and subsystem may be coupled to peripheral interface 106, a variety of to help to realize
Function.
For example, motion sensor 110, light sensor 112 and range sensor 114 may be coupled to peripheral interface 106,
To facilitate the functions such as orientation, illumination and ranging.Other sensors 116 can equally be connected with peripheral interface 106, such as positioning system
System (such as GPS receiver), temperature sensor, biometric sensor or other sensor devices, it is possible thereby to help to implement phase
The function of pass.
Camera sub-system 120 and optical sensor 122 can be used for the camera of convenient such as record photos and video clips
The realization of function, wherein the camera sub-system and optical sensor for example can be charge-coupled device (CCD) or complementary gold
Belong to oxide semiconductor (CMOS) optical sensor.It can help to realize by one or more radio communication subsystems 124
Communication function, wherein radio communication subsystem may include radio-frequency transmitter and transmitter and/or light (such as infrared) receiver
And transmitter.The particular design and embodiment of radio communication subsystem 124 can depend on what mobile terminal 100 was supported
One or more communication networks.For example, mobile terminal 100 may include being designed to support LTE, 3G, GSM network, GPRS net
Network, EDGE network, Wi-Fi or WiMax network and BlueboothTMThe communication subsystem 124 of network.
Audio subsystem 126 can be coupled with loudspeaker 128 and microphone 130, to help to implement to enable voice
Function, such as speech recognition, speech reproduction, digital record and telephony feature.I/O subsystem 140 may include touch screen control
Device 142 processed and/or other one or more input controllers 144.Touch screen controller 142 may be coupled to touch screen 146.It lifts
For example, any one of a variety of touch-sensing technologies are can be used to detect in the touch screen 146 and touch screen controller 142
The contact and movement or pause carried out therewith, wherein detection technology includes but is not limited to capacitive character, resistive, infrared and table
Face technology of acoustic wave.Other one or more input controllers 144 may be coupled to other input/control devicess 148, such as one
The pointer device of a or multiple buttons, rocker switch, thumb wheel, infrared port, USB port, and/or stylus etc.Institute
State one or more button (not shown)s may include for control 130 volume of loudspeaker 128 and/or microphone it is upward/to
Lower button.
Memory interface 102 can be coupled with memory 150.The memory 150 may include that high random access is deposited
Reservoir and/or nonvolatile memory, such as one or more disk storage equipments, one or more optical storage apparatus, and/
Or flash memories (such as NAND, NOR).Memory 150 can store an operating system 172, for example, Android, iOS or
The operating system of Windows Phone etc.The operating system 172 may include for handling basic system services and execution
The instruction of task dependent on hardware.Memory 150 can also be stored using 174.It, can be from memory in mobile device operation
Load operating system 172 in 150, and executed by processor 104.At runtime using 174, can also add from memory 150
It carries, and is executed by processor 104.It is operated on operating system 172 using 174, it is hard using operating system 172 and bottom
The interface that part provides realizes the various desired functions of user, such as instant messaging, web page browsing, pictures management.It can be with using 174
Operating system offer is provided, is also possible to what operating system carried.In addition, being mounted to mobile terminal 100 using 174
When middle, drive module can also be added to operating system.
In above-mentioned various applications 174, one such application is the application 200 according to the present invention to video denoising.
Using 200 denoising can be carried out to the image frame sequence about video.Below with reference to Fig. 2 to video according to the present invention
Denoising mode illustrates.
Fig. 2 shows the schematic diagrames of the application 200 to video denoising according to some embodiments of the invention.As shown in Fig. 2,
It include image acquisition unit 210, noise grade calculating unit 220, smoothing factor computing unit 230, distance calculating list using 200
Member 240, weight calculation unit 250 and luma processing unit 260.
Image acquisition unit 210 is suitable for obtaining the image frame sequence about video.Here, original video to be denoised can be with
It is the image frame sequence of mobile terminal (100) captured in real-time, is also possible to carry out the video data of automatic network, or be locally stored
The video data stored in device (150), the present invention do not do excessive limitation to this.The picture frame of original video for example can be
The various pixel formats such as RGB, YUV or YCbCr.
It should be noted that being suitable for executing denoising to the picture frame of brightness and chrominance separation using 200.According to this hair
Bright one embodiment, when the picture frame of original video is the pixel format of the brightness such as YUV or YCbCr and chrominance separation expression,
Image acquisition unit 210 can be using original image frame sequence as the direct process object for applying 200.According to the present invention another
Embodiment, when the picture frame of original video is, for example, that RGB etc. does not separate the pixel format of brightness and coloration, image acquisition unit
210 pairs of original frame sequences obtained sequentially in time carry out conversion operation.Original frame sequence in an rgb format is converted to below
For YCbCr, the conversion operation of image acquisition unit 210 is illustrated.
Illustrate first, the relational expression of YCbCr format and rgb format is as follows:
Y=KRR+KGG+KBB
Wherein, KRWith KBIt is predetermined, KG=1-KB-KR.For example, according to the definition in ITU-R BT.601: KB=
0.114, KR=0.299, KG=1-KB-KR=0.587.
Therefore, image acquisition unit 210 can carry out conversion operation according to following Matrix Formulas in the present embodiment.
Wherein, Y is brightness value, CbAnd CrRespectively chromatic value.
For the image frame sequence of brightness provided by image acquisition unit 210 and chrominance separation, noise grade calculates single
Member 220 is suitable for calculating in each picture frame each noise grade of pixel to be denoised.In other words, noise grade calculates unit
220 can carry out noise grade estimation (noise level estimation) to each pixel to be denoised.Here, noise grade
Computing unit 220 can carry out noise grade estimation using a variety of well known algorithms, and the present invention does not make too many restrictions this.
In an embodiment in accordance with the invention, noise calculating unit 220 can use " Practical Signal-
Dependent Noise Parameter Estimation From a Single Noisy Image” (IEEE
TRANSACTIONS ON IMAGE PROCESSING, VOL.23, NO.10, OCTOBER 2014) disclosed in noise grade
Algorithm for estimating.
In another embodiment according to the present invention, in order to assess the noise grade of a pixel to be denoised, noise meter
Unit 220 is calculated centered on the pixel to be denoised, selects the image block of predetermined window size as the pixel to be denoised
Neighborhood block.On this basis, noise calculating unit 220 calculates the variance of brightness in the field block, is somebody's turn to do pixel to be denoised to determine
The noise grade of point.In general, variance is bigger, noise intensity is bigger (that is, noise grade is higher).
Smoothing factor computing unit 230 is suitable for noise grade and its brightness according to each pixel to be denoised, determination pair
Answer the brightness smoothing factor of this pixel to be denoised.
Metrics calculation unit 240 is suitable for from each wait denoise in the multiple image adjacent with front and back of this frame locating for pixel,
It selectes and is somebody's turn to do the associated pixel of pixel to be denoised, and calculated based on block matching algorithm and be somebody's turn to do pixel to be denoised and select often
The distance of a associated pixel point.Here, block matching algorithm can for example use " Nonlocal Image and Movie
Denoising " (Int J Comput Vis (2008) 76:123-139 DOI 10.1007/s11263-007-0052-1) institute
Disclosed algorithm, but not limited to this.
In an embodiment in accordance with the invention, metrics calculation unit 240 is in the selected and associated picture of pixel to be denoised
Before vegetarian refreshments, pretreatment operation is carried out.Here, pretreatment operation is that exclusion and pixel similarity degree to be denoised are lower (i.e.
The degree of association is lower) pixel.The low pixel of these similarity degrees influences very little to the denoising in later period.In other words, institute
The pixel of exclusion can be ignored later period denoising influence.In this way, metrics calculation unit 240 passes through pretreatment operation
Can largely reduce with the quantity of the associated pixel of pixel to be denoised, so that the time for reducing metrics calculation unit 240 disappears
Consumption.
In another embodiment according to the present invention, metrics calculation unit 240 is mentioned in addition to that can execute in above-described embodiment
It, can also be using the mode of operation of similar block transmitting (patch propagation) to association picture other than the pretreatment operation arrived
Vegetarian refreshments is selected.Then, according to the pixel of corresponding position and the positional relationship of at least part pixel that is counted, away from
From computing unit 240 can select with should pixel be denoised keep the pixel of this positional relationship as with the picture to be denoised
The associated pixel of vegetarian refreshments.Specifically, metrics calculation unit 240 can count the picture frame before the pixel to be denoised
Highest at least part of pixel similarity in pixel associated by the pixel of middle corresponding position, with corresponding position.
It is illustrated below with reference to process of the Fig. 3 to the selected associated pixel point transmitted based on similar block.
Fig. 3 shows pixel a to be denoised0The picture frame T at place0With in T0Before via metrics calculation unit
240 carry out the picture frame T apart from calculating-1、T-2、T-3, in T0Picture frame T to be processed later1、T2、T3.Pixel a is in image
Frame T-1、T-2、T-3Additional space position on pixel be respectively a-1、a-2、a-3.Typically, in the image frame sequence of video
In column in the adjacent picture frame in front and back, the pixel of additional space position (spatial position of the pixel in picture frame) (for example,
a0、a-1、a-2And a-3) time interval with very little.Correspondingly, the motion change very little of these pixels.In general, a0It is similar
Spend the distributing position and a of the pixel of higher (being closer)-1、a-2And a-3This respective similitude distributing position base of 3 points
This is consistent.Therefore, metrics calculation unit 240 can be counted first and a-1、 a-2And a-3The highest picture of at least part similarity
The distributing position of vegetarian refreshments.In this way, metrics calculation unit 240 can select and a0Maintain like the pixel of distributing position relationship
As pixel associated there.Obviously, the selected mode that metrics calculation unit 240 is transmitted by above-mentioned similar block, can be with
It is accurate and be quickly found out and a0The high pixel of similarity, and eliminate usually and a0The low pixel of similarity, thus greatly
Reduce the subsequent calculation amount for carrying out Block- matching operation.Then, metrics calculation unit 240 can calculate pixel a to be denoised0
At a distance from each associated pixel.It here, is, for example, to calculate about the calculation of the distance between two pixels
The distance between two pixel neighborhood of a point blocks.Specifically, the neighborhood block to be matched for obtaining the pixel to be denoised first closes
In the feature vector of brightness.Pixel a to be denoised0Neighborhood block to be matched with a0Centered on, the image block of predetermined window size.
a0Corresponding feature vector includes that (each brightness value is feature point for the brightness of each pixel in its corresponding neighborhood block
Amount).Similarly, metrics calculation unit 240 obtains feature vector of each associated pixel neighborhood of a point block about brightness.?
On the basis of this, metrics calculation unit 240 can calculate neighborhood block to be matched and each associated pixel neighborhood of a point block
Distance is as the corresponding distance of this associated pixel between feature vector.Typically, distance is for example between feature vector
It is Euclidean distance, but not limited to this.Here, distance is closer, and the similarity between pixel is higher.
To sum up, smoothing factor computing unit 230 has determined the brightness smoothing factor of pixel to be denoised, metrics calculation unit
240 have determined pixel to be denoised distance corresponding with each associated pixel point.On this basis, weight calculation unit 250 is suitable
According to each brightness smoothing factor of pixel to be denoised distance corresponding with pixel is each associated with, each phase is calculated
The corresponding weight of associated pixel point.For each pixel to be denoised, luma processing unit 260 is suitable for basis and is each associated with
The brightness and weight of pixel calculate all luminance weighted average values for being associated with pixel and as the pixel to be denoised
The brightness through denoising.
In an embodiment in accordance with the invention, weight calculation unit 250 carries out weight calculation according to following formula, but not
It is limited to this.
Wherein, x indicates that pixel to be denoised, y indicate a pixel associated with x.
||u(Nd(x))-u(Nd(y)) | | indicate x neighborhood block character pair vector and y character pair vector between away from
From d is the dimension of feature vector, and h indicates that the brightness smoothing factor of x, W (x) indicate corresponding with the associated all pixels of x
'sThe sum of, w (x, y) is the weight of y pixel.
On this basis, it is bright through what is denoised can to calculate pixel to be denoised according to following formula for luma processing unit 260
Degree.
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the power of y pixel
Weight, u (y) indicate the brightness value of y.
To sum up, application 200 can be selected accurately with the high pixel of pixel similarity to be denoised as associated pixel
Point, and then carry out Block- matching and calculate with the weight of each associated pixel point of determination.In addition, denoising picture can be treated using 200
The noise grade of vegetarian refreshments is assessed, and then determines the brightness smoothing factor of corresponding noise grade.In conjunction with the noise grade and often
A weight and brightness for being associated each pixel, application 200 can be by the brightness with pixel associated pixel point to be denoised
Weighted average is as the brightness through denoising.It should be noted that using metrics calculation unit 240 in 200 to associated pixel
The accurate selection of point, can be greatly improved the denoising speed using 200.In addition, quickly reducing the same of noise using 200
When, it still can be effectively maintained video details.To individually wait denoise pixel for, using it is 200 accurately selecting, with its phase
Associated pixel (on this frame and before and after frames where pixel to be denoised) quantity has enough.Therefore, though to
The pixel of denoising has very high noise grade, can also obtain denoising effect well using 200.
Fig. 4 shows the schematic diagram of the application 400 to video denoising of other embodiment according to the present invention.Such as Fig. 4 institute
Show, includes image acquisition unit 410, noise grade calculating unit 420, smoothing factor computing unit 430, distance meter using 400
Calculate unit 440, weight calculation unit 450, luma processing unit 460 and coloration processing unit 470.Wherein, image acquisition unit
410, noise grade calculates unit 420, smoothing factor computing unit 430, metrics calculation unit 440,450 and of weight calculation unit
Luma processing unit 460 calculates unit 220, smoothing factor computing unit with image acquisition unit 210, noise grade respectively
230, metrics calculation unit 240, weight calculation unit 250 are consistent with the embodiment of luma processing unit 260, no longer superfluous here
It states.
In addition, coloration processing unit 470 is suitable for the coloration according to each pixel in following formula smoothed image frame sequences:
Wherein, ft(x) the smoothed out chromatic value of pixel x on t frame image is indicated. exp(||ut(x)-ut+Δ(x)|
|2Indicate on x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from.Here, each pixel
The coloration of point may include two components (for example, C in YCbCr formatbAnd Cr).Each component can by above-mentioned formula into
Row smoothing processing.In addition, colour difference away from above in connection with pixel to be denoised in brightness space and associated pixel point away from
It is similar from calculating, but calculation amount becomes coloration from brightness, which is not described herein again.
W (x) be with the colour difference of the pixel of additional space position on all consecutive frames from-n to n away from the sum of.ut+Δ
(x) chromatic value of the pixel of additional space position on Δ frame adjacent with x is indicated.It indicates
The weight of the chromatic value of the pixel of the additional space position.
It should be noted that the broadcasting pictures through denoising rear video often have a kind of discontinuous in existing denoising scheme
Bounce sense.Application 400 of the invention can be carried out while be filtered to brightness and coloration, and the stream of video playing picture can be improved
Smooth property.
Fig. 5 shows the flow chart of the method 500 to video denoising according to some embodiments of the invention.Method 500 is suitable
It is executed in the equipment such as mobile terminal (100).
As shown in figure 5, method 500 starts from step S510.In step S510, the image frame sequence about video is obtained.
According to an embodiment of the present invention, in step S510, the primitive frame sequence of rgb pixel format is obtained first, in accordance with time sequencing
Column.Then, by original frame sequence the sequence of data frames of brightness and chrominance separation is converted and as described image frame sequence.Step
The more specific embodiment of S510 is consistent with above image acquisition unit 210, and which is not described herein again.
For image frame sequence obtained in step S510, method 500 executes step S520.In step S520, calculate
Each noise grade of pixel to be denoised in each picture frame.According to an embodiment of the present invention, step S520 is more specific
Embodiment is as follows.Firstly, selecting the image block of predetermined window size as this wait denoise centered on the pixel to be denoised
Pixel neighborhood of a point block.Then, the variance of brightness in the field block is calculated, to determine the noise grade of the pixel to be denoised.
Here, the more specific embodiment of step S520 calculates unit 220 unanimously with above noise grade, and which is not described herein again.
According to the noise grade of pixel to be denoised identified in step S520 and the brightness of this pixel, method
500 can execute step S530, determine the brightness smoothing factor of this corresponding pixel to be denoised.Step S530 is more specifically real
It is consistent with above smoothing factor computing unit 230 to apply mode, which is not described herein again.
Method 500 further includes step S540.In step S540, from each wait denoise this frame locating for pixel and front and back
In adjacent multiple image, selectes and be somebody's turn to do the associated pixel of pixel to be denoised, and being calculated based on block matching algorithm should be wait denoise
Pixel is at a distance from selected each associated pixel point.
According to an embodiment of the present invention, step S540 may be implemented as method 600 as shown in FIG. 6.Such as Fig. 6 institute
Show, method 600 starts from step S610, counts in the picture frame before the pixel to be denoised associated by the pixel of corresponding position
Pixel in, with highest at least part of pixel similarity of corresponding position.Then, method 600 executes step S620,
According to the positional relationship of the pixel of corresponding position and at least part pixel counted, selectes and be somebody's turn to do pixel to be denoised
Keep the pixel of this positional relationship as pixel associated with the pixel to be denoised.Then, method 600 executes step
Rapid S630 calculates the pixel to be denoised at a distance from each associated pixel.According to an embodiment of the present invention, exist
In step S630, feature vector of the neighborhood block to be matched of the pixel to be denoised about brightness is obtained first.Then, it obtains
Feature vector of each associated pixel neighborhood of a point block about brightness.On this basis, calculate neighborhood block to be matched with
Distance is as the corresponding distance of this associated pixel between the feature vector of each associated pixel neighborhood of a point block.
The more specific embodiment of step S540 is consistent with above metrics calculation unit 240, and which is not described herein again.
Based on each associated pixel point pair determined in the brightness smoothing factor and step S540 determined in step S530
The distance answered, method 500 can execute step S550.In step S550, the corresponding weight of each associated pixel point is calculated.
According to an embodiment of the present invention, step S550 calculates the corresponding weight of each associated pixel point according to following formula.
Wherein, x indicates pixel to be denoised.Y indicates a pixel associated with x.
||u(Nd(x))-u(Nd(y)) | | indicate x neighborhood block character pair vector and y character pair vector between away from
From.D is the dimension of feature vector.The brightness smoothing factor of h expression x.W (x) indicates corresponding with the associated all pixels of x
'sThe sum of.W (x, y) is the weight of y pixel.The more specific embodiment party of step S550
Formula is consistent with above weight calculation unit 250, and which is not described herein again.
For each pixel to be denoised, method 500 can execute step S560.In step S560, according to it is each with
The brightness and weight of its associated pixel point calculate all luminance weighted average values for being associated with pixel and wait denoising as this
The brightness through denoising of pixel.According to an embodiment of the present invention, step S560 calculates pixel through going according to following formula
The brightness made an uproar.
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the power of y pixel
Weight, u (y) indicate the brightness value of y.The more specific embodiment of step S560 is consistent with above luma processing unit 260, here
It repeats no more.
Fig. 7 shows the flow chart of the method 700 to video denoising according to some embodiments of the invention.Method 700 is wrapped
Include step S710, S720, S730, S740, S750, S760 and S770.Wherein, the embodiment of step S710-S760 respectively with
Step S510-S560 is consistent in Fig. 5, and which is not described herein again.
In step S770, according to the coloration of each pixel in the smooth described image frame sequence of following formula:
Wherein, ft(x) the smoothed out chromatic value of pixel x on t frame image is indicated. exp(||ut(x)-ut+Δ(x)|
|2Indicate on x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from.W (x) be with from-n
To the pixel of additional space position on all consecutive frames of n colour difference away from the sum of.ut+Δ(x) phase on Δ frame adjacent with x is indicated
Answer the chromatic value of the pixel of spatial position.Indicate the pixel of the additional space position
Chromatic value weight.The more specific embodiment of step S770 is consistent with above coloration processing unit 470, here no longer
It repeats.
A10, the application as described in A9, wherein described image acquiring unit is suitable for being obtained according to following manner about video
Image frame sequence:
The original frame sequence of rgb pixel format is obtained sequentially in time；
The sequence of data frames of brightness and chrominance separation is converted by original frame sequence and as described image frame sequence.
A11, the application as described in A9 or A10, wherein the noise grade calculates unit and is suitable for being calculated according to following manner
Each noise grade of pixel to be denoised in each picture frame:
Centered on the pixel to be denoised, select the image block of predetermined window size as the neighbour of the pixel to be denoised
Domain block；
The variance of brightness in the field block is calculated, to determine the noise grade of the pixel to be denoised.
A12, the application as described in any one of A9-A11, wherein the metrics calculation unit is suitable for according to following manner
From each wait denoise in the multiple image adjacent with front and back of this frame locating for pixel, select and be somebody's turn to do the associated picture of pixel to be denoised
Vegetarian refreshments, and the pixel to be denoised is calculated at a distance from selected each associated pixel point based on block matching algorithm:
In picture frame before counting the pixel to be denoised in pixel associated by the pixel of corresponding position, with it is right
Answer highest at least part of pixel similarity of position；
According to the positional relationship of the pixel of corresponding position and at least part pixel counted, selectes and be somebody's turn to do wait go
Pixel of making an uproar keeps the pixel of this positional relationship as pixel associated with the pixel to be denoised；And
The pixel to be denoised is calculated at a distance from each associated pixel.
A13, the application as described in A12, wherein the metrics calculation unit is suitable for being calculated according to following manner should be wait denoise
Pixel is at a distance from each associated pixel:
Obtain feature vector of the neighborhood block to be matched of the pixel to be denoised about brightness；
Obtain feature vector of each associated pixel neighborhood of a point block about brightness；And
Calculate distance conduct between neighborhood block and the feature vector of each associated pixel neighborhood of a point block to be matched
The corresponding distance of this associated pixel.
A14, the application as described in any one of A9-13, wherein the weight calculation unit executes institute according to following formula
The distance corresponding with pixel is each associated with according to each brightness smoothing factor of pixel to be denoised is stated, each phase is calculated
The corresponding weight of associated pixel point:
Wherein, x indicates that pixel to be denoised, y indicate a pixel associated with x,
||u(Nd(x))-u(Nd(y)) | | indicate x neighborhood block character pair vector and y character pair vector between away from
From d is the dimension of feature vector, and h indicates that the brightness smoothing factor of x, W (x) indicate corresponding with the associated all pixels of x
'sThe sum of, w (x, y) is the weight of y pixel.
A15, the application as described in A14, wherein the luma processing unit is suitable for base for each pixel to be denoised
To calculate according to the brightness and weight for being associated with each pixel and be associated with the luminance weighted flat of pixel in following manner
Mean value and the brightness through denoising as the pixel to be denoised:
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the power of y pixel
Weight, u (y) indicate the brightness value of y.
A16, the application as described in any one of A9-15 further include coloration processing unit, are suitable for smooth according to following formula
The coloration of each pixel in described image frame sequence:
Wherein, ft(x) expression smoothed out chromatic value of pixel x on t frame image, exp (| | ut(x)-ut+Δ(x)|
|2Indicate on x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from, W (x) be with from-n
To the pixel of additional space position on all consecutive frames of n colour difference away from the sum of, ut+Δ(x) phase on Δ frame adjacent with x is indicated
The chromatic value of the pixel of spatial position is answered,Indicate the pixel of the additional space position
Chromatic value weight.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that implementation of the invention
Example can be practiced without these specific details.In some instances, well known method, knot is not been shown in detail
Structure and technology, so as not to obscure the understanding of this specification.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of the various inventive aspects,
Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the disclosed method should not be interpreted as reflecting the following intention: i.e. required to protect
Shield the present invention claims than feature more features expressly recited in each claim.More precisely, as following
As claims reflect, inventive aspect is all features less than single embodiment disclosed above.Therefore, it abides by
Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, wherein each claim itself
As a separate embodiment of the present invention.
Those skilled in the art should understand that the module of the equipment in example disclosed herein or unit or groups
Part can be arranged in equipment as depicted in this embodiment, or alternatively can be positioned at and the equipment in the example
In different one or more equipment.Module in aforementioned exemplary can be combined into a module or furthermore be segmented into multiple
Submodule.
Those skilled in the art will understand that can be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more devices different from this embodiment.It can be the module or list in embodiment
Member or component are combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it can use any
Combination is to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed
All process or units of what method or apparatus are combined.Unless expressly stated otherwise, this specification is (including adjoint power
Benefit require, abstract and attached drawing) disclosed in each feature can carry out generation with an alternative feature that provides the same, equivalent, or similar purpose
It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included certain features rather than other feature, but the combination of the feature of different embodiments mean it is of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment claimed is appointed
Meaning one of can in any combination mode come using.
In addition, be described as herein can be by the processor of computer system or by executing by some in the embodiment
The combination of method or method element that other devices of the function are implemented.Therefore, have for implementing the method or method
The processor of the necessary instruction of element forms the device for implementing this method or method element.In addition, Installation practice
Element described in this is the example of following device: the device be used for implement as in order to implement the purpose of the invention element performed by
Function.
As used in this, unless specifically stated, come using ordinal number " first ", " second ", " third " etc.
Description plain objects, which are merely representative of, is related to the different instances of similar object, and is not intended to imply that the object being described in this way must
Must have the time it is upper, spatially, sequence aspect or given sequence in any other manner.
Although the embodiment according to limited quantity describes the present invention, above description, the art are benefited from
It is interior it is clear for the skilled person that in the scope of the present invention thus described, it can be envisaged that other embodiments.Additionally, it should be noted that
Language used in this specification primarily to readable and introduction purpose and select, rather than in order to explain or limit
Determine subject of the present invention and selects.Therefore, without departing from the scope and spirit of the appended claims, for this
Many modifications and changes are obvious for the those of ordinary skill of technical field.For the scope of the present invention, to this
Invent done disclosure be it is illustrative and not restrictive, it is intended that the scope of the present invention be defined by the claims appended hereto.
Claims (15)
1. the method for a kind of pair of video denoising, suitable for executing in the terminal, this method comprises:
Obtain image frame sequence about video, wherein in the picture frame of original video be the pixel for not separating brightness and coloration
When format, the sequence of data frames of brightness and chrominance separation is converted into the original frame sequence obtained sequentially in time and as institute
State image frame sequence；
Calculate in each picture frame each noise grade of pixel to be denoised；
According to the noise grade and its brightness of each pixel to be denoised, determine that the brightness of this corresponding pixel to be denoised is smooth
Coefficient；
For each pixel to be denoised, the pixel of corresponding position is closed in the picture frame before counting the pixel to be denoised
Highest at least part of pixel similarity in the pixel of connection, with corresponding position；
According to the positional relationship of the pixel of corresponding position and at least part pixel counted, selectes and be somebody's turn to do picture to be denoised
Vegetarian refreshments keeps the pixel of this positional relationship as pixel associated with the pixel to be denoised；
The pixel to be denoised is calculated at a distance from each associated pixel；
According to the brightness smoothing factor of each pixel to be denoised distance corresponding with pixel is each associated with, calculate each
The corresponding weight of associated pixel point；And
All be associated with is calculated according to each brightness and weight for being associated with pixel for each pixel to be denoised
The luminance weighted average value of pixel and the brightness through denoising as the pixel to be denoised.
2. the method for claim 1, wherein the step of image frame sequence obtained about video includes:
The original frame sequence of rgb pixel format is obtained sequentially in time；
The sequence of data frames of brightness and chrominance separation is converted by original frame sequence and as described image frame sequence.
3. method according to claim 1 or 2, wherein described to calculate in each picture frame making an uproar for each pixel to be denoised
The step of sound grade includes:
Centered on the pixel to be denoised, select the image block of predetermined window size as the pixel neighborhood of a point to be denoised
Block；
The variance of brightness in the neighborhood block is calculated, to determine the noise grade of the pixel to be denoised.
4. the method for claim 1, wherein described calculating pixel to be denoised and each associated pixel
Apart from the step of include:
Obtain feature vector of the neighborhood block to be matched of the pixel to be denoised about brightness；
Obtain feature vector of each associated pixel neighborhood of a point block about brightness；And
Distance is calculated between neighborhood block and the feature vector of each associated pixel neighborhood of a point block to be matched as this
The corresponding distance of associated pixel.
5. the method for claim 1, wherein each brightness smoothing factor of pixel to be denoised and each of the basis
The step of being associated with the corresponding distance of pixel, calculating each associated pixel point corresponding weight includes following manner:
Wherein, x indicates that pixel to be denoised, y indicate pixel associated with x,
||u(Nd(x))-u(Nd(y)) | | indicate the distance between neighborhood block character pair vector and y character pair vector of x, d
For the dimension of feature vector, h indicates that the brightness smoothing factor of x, W (x) indicate corresponding with the associated all pixels of xThe sum of, w (x, y) is the corresponding weight of y pixel.
6. method as claimed in claim 5, wherein it is described for each pixel to be denoised, according to being associated with each picture
The brightness and weight of vegetarian refreshments, calculating are associated with the luminance weighted average value of pixel and being gone as the pixel to be denoised
The step of brightness made an uproar includes following manner:
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the weight of y pixel, u
(y) brightness value of y is indicated.
7. the method as described in claim 1, further includes: according to each pixel in the smooth described image frame sequence of following formula
Coloration:
Wherein, ft(x) expression smoothed out chromatic value of pixel x on t frame image, exp (| | ut(x)-ut+Δ(x)||2It indicates
On x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from, W (x) for the institute from-n to n
Have the colour difference of the pixel of additional space position on consecutive frame away from the sum of, ut+Δ(x) additional space on Δ frame adjacent with x is indicated
The chromatic value of the pixel of position,Indicate the coloration of the pixel of the additional space position
The weight of value.
8. the device of a kind of pair of video denoising is suitable for being resident in the terminal, which includes:
Image acquisition unit, suitable for obtaining image frame sequence about video, wherein in the picture frame of original video be not separate
When the pixel format of brightness and coloration, the number of brightness and chrominance separation is converted into the original frame sequence obtained sequentially in time
According to frame sequence and as described image frame sequence；
Noise grade calculates unit, suitable for calculating in each picture frame each noise grade of pixel to be denoised；
Smoothing factor computing unit determines suitable for the noise grade and its brightness according to each pixel to be denoised and corresponds to this
The brightness smoothing factor of pixel to be denoised；
Metrics calculation unit is right in the picture frame before counting the pixel to be denoised suitable for for each pixel to be denoised
Answer highest at least part of pixel similarity in pixel associated by the pixel of position, with corresponding position；According to
The positional relationship of the pixel of corresponding position and at least part pixel counted is selected and is somebody's turn to do pixel holding to be denoised
The pixel of this positional relationship is as pixel associated with the pixel to be denoised；Calculating should pixel be denoised and every
The distance of a associated pixel；
Weight calculation unit, suitable for being associated with pixel pair with each according to each brightness smoothing factor of pixel to be denoised
The distance answered calculates the corresponding weight of each associated pixel point；And
Luma processing unit is each associated with the brightness and weight of pixel suitable for basis for each pixel to be denoised,
Calculate all luminance weighted average values for being associated with pixel and the brightness through denoising as the pixel to be denoised.
9. device as claimed in claim 8, wherein described image acquiring unit is suitable for being obtained according to following manner about video
Image frame sequence:
The original frame sequence of rgb pixel format is obtained sequentially in time；
The sequence of data frames of brightness and chrominance separation is converted by original frame sequence and as described image frame sequence.
10. device as claimed in claim 8 or 9, wherein the noise grade calculates unit and is suitable for being calculated according to following manner
Each noise grade of pixel to be denoised in each picture frame:
Centered on the pixel to be denoised, select the image block of predetermined window size as the pixel neighborhood of a point to be denoised
Block；
The variance of brightness in the neighborhood block is calculated, to determine the noise grade of the pixel to be denoised.
11. device as claimed in claim 8, wherein the metrics calculation unit is suitable for being calculated according to following manner should be wait go
Pixel make an uproar at a distance from each associated pixel:
Obtain feature vector of the neighborhood block to be matched of the pixel to be denoised about brightness；
Obtain feature vector of each associated pixel neighborhood of a point block about brightness；And
Distance is calculated between neighborhood block and the feature vector of each associated pixel neighborhood of a point block to be matched as this
The corresponding distance of associated pixel.
12. device as claimed in claim 8, wherein the weight calculation unit is every according to following formula execution basis
The brightness smoothing factor of a pixel to be denoised distance corresponding with pixel is each associated with, calculates each associated pixel
The corresponding weight of point:
Wherein, x indicates that pixel to be denoised, y indicate a pixel associated with x,
||u(Nd(x))-u(Nd(y)) | | indicate the distance between neighborhood block character pair vector and y character pair vector of x, d
For the dimension of feature vector, h indicates that the brightness smoothing factor of x, W (x) indicate corresponding with the associated all pixels of xThe sum of, w (x, y) is the weight of y pixel.
13. device as claimed in claim 12, wherein the luma processing unit is suitable for each pixel to be denoised
Based on following manner come according to the brightness and weight for being associated with each pixel, calculating is associated with the luminance weighted of pixel
Average value and the brightness through denoising as the pixel to be denoised:
Wherein, x indicates that pixel to be denoised, y indicate that pixel associated with x, w (x, y) are the weight of y pixel, u
(y) brightness value of y is indicated.
14. device as claimed in claim 8 further includes coloration processing unit, it is suitable for according to the smooth described image of following formula
The coloration of each pixel in frame sequence:
Wherein, ft(x) expression smoothed out chromatic value of pixel x on t frame image, exp (| | ut(x)-ut+Δ(x)||2It indicates
On x and adjacent Δ frame between the pixel of additional space position about the colour difference of neighborhood block away from, W (x) for the institute from-n to n
Have the colour difference of the pixel of additional space position on consecutive frame away from the sum of, ut+Δ(x) additional space on Δ frame adjacent with x is indicated
The chromatic value of the pixel of position,Indicate the coloration of the pixel of the additional space position
The weight of value.
15. a kind of mobile terminal, comprising: the device to video denoising as described in any one of claim 8-14.
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| CN107172322B (en) * | 2017-06-16 | 2020-02-18 | 北京飞识科技有限公司 | Video noise reduction method and device |
| CN107454284B (en) * | 2017-09-13 | 2020-05-15 | 厦门美图之家科技有限公司 | Video denoising method and computing device |
| CN107786780B (en) * | 2017-11-03 | 2021-04-16 | 深圳Tcl新技术有限公司 | Video image noise reduction method and device and computer readable storage medium |
| CN109410145B (en) * | 2018-11-01 | 2020-12-18 | 北京达佳互联信息技术有限公司 | Time sequence smoothing method and device and electronic equipment |
| CN112565915B (en) * | 2020-06-04 | 2023-05-05 | 海信视像科技股份有限公司 | Display apparatus and display method |
| CN111754493A (en) * | 2020-06-28 | 2020-10-09 | 北京百度网讯科技有限公司 | Method and device for evaluating image noise intensity, electronic equipment and storage medium |
| CN113240608A (en) * | 2021-05-26 | 2021-08-10 | Oppo广东移动通信有限公司 | Image denoising method and device, electronic equipment and readable storage medium |
| CN115330628B (en) * | 2022-08-18 | 2023-09-12 | 盐城众拓视觉创意有限公司 | Video frame-by-frame denoising method based on image processing |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1638428A (en) * | 2004-01-02 | 2005-07-13 | Lg电子有限公司 | Image processing device and method |
| CN1723691A (en) * | 2003-09-29 | 2006-01-18 | 三星电子株式会社 | Noise-reduction method and equipment |
| CN101473656A (en) * | 2006-06-29 | 2009-07-01 | 汤姆森许可贸易公司 | Adaptive filtering based on pixel |
| CN103559684A (en) * | 2013-10-08 | 2014-02-05 | 清华大学深圳研究生院 | Method for restoring images based on smooth correction |
| CN104010114A (en) * | 2014-05-29 | 2014-08-27 | 广东威创视讯科技股份有限公司 | Video denoising method and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8675102B2 (en) * | 2012-06-08 | 2014-03-18 | Apple Inc. | Real time denoising of video |
-
2016
- 2016-08-29 CN CN201610750044.5A patent/CN106303156B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1723691A (en) * | 2003-09-29 | 2006-01-18 | 三星电子株式会社 | Noise-reduction method and equipment |
| CN1638428A (en) * | 2004-01-02 | 2005-07-13 | Lg电子有限公司 | Image processing device and method |
| CN101473656A (en) * | 2006-06-29 | 2009-07-01 | 汤姆森许可贸易公司 | Adaptive filtering based on pixel |
| CN103559684A (en) * | 2013-10-08 | 2014-02-05 | 清华大学深圳研究生院 | Method for restoring images based on smooth correction |
| CN104010114A (en) * | 2014-05-29 | 2014-08-27 | 广东威创视讯科技股份有限公司 | Video denoising method and device |
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