CN108174057A - It is a kind of using video image interframe difference to the method and device of picture fast noise reduction - Google Patents
It is a kind of using video image interframe difference to the method and device of picture fast noise reduction Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/14—Picture signal circuitry for video frequency region
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
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- H—ELECTRICITY
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Abstract
The present invention provides it is a kind of using video image interframe difference to the method for picture fast noise reduction, including：Video flowing, the video stream packets consecutive image containing multiframe are acquired under night low-light level environment；Using the key frame of video flowing as starting point, the non-key frame of video flowing is detected, the maximum brightness value of pixel and surrounding neighbor pixel in the non-key frame is obtained, the brightness value of the pixel and the maximum brightness value of neighbor point around the pixel are compared；If the brightness value of the pixel is the maximum brightness value, the maximum brightness value and the difference of time big brightness value in the pixel and surrounding neighbor pixel are calculated, if the luminance difference is more than luminance threshold, it is determined that the pixel is doubtful noise；The brightness value of the doubtful noise is replaced.Correspondingly the present invention also provides it is a kind of using video image interframe difference to the device of picture fast noise reduction.Solve the problems, such as that traditional noise reduction algorithm speed cannot have both with effect in the prior art.
Description
Technical field
The invention belongs to technical field of video image processing, and video image interframe difference is utilized more particularly, to a kind of
To the method and device of picture fast noise reduction.
Background technology
Digital picture in reality is subjected to imaging device in digitlization and transmission process and is interfered with external environmental noise
Deng influence, referred to as noisy image or noise image.The process for reducing noise in digital picture is known as image noise reduction, is sometimes also known as
For image denoising.Noise is the major reason of image interference.Piece image is made an uproar in practical applications there may be various
Sound, these noises may generate in the transmission, it is also possible to be generated in the processing such as quantization.It can be incited somebody to action according to the relationship of noise and signal
It is broadly divided into three kinds of forms:Additive noise, multiplicative noise and quantizing noise etc..
The method of conventional process noise includes mean filter, adaptive wiener filter, median filter, morphology
The methods of scratch filter and Wavelet Denoising Method.Static picture is only utilized in traditional noise reduction algorithm, carry out vedio noise reduction when
It waits, there is requirement of real-time, however, traditional algorithm processing speed can sacrifice certain effect soon, and effect is good can then sacrifice centainly
Speed, cause speed and treatment effect that cannot have both.
Invention content
For the disadvantages described above or Improvement requirement of the prior art, video image interframe difference is utilized the present invention provides a kind of
To the method and device of picture fast noise reduction, solve traditional noise reduction algorithm speed in the prior art and asked with what effect cannot have both
Topic.
To achieve these goals, one side according to the invention provides a kind of utilization video image interframe difference
To the method for picture fast noise reduction, including：
Determine to treat the first frame key frame of de-noising video stream, using the first frame key frame as starting point, to the video flowing
Non-key frame be detected, until encountering next frame key frame, then using the next frame key frame as starting point, to the video
The non-key frame of stream is detected and replaces, and repeats the above detection of the process until completing all non-key frames；It is wherein right
The non-key frame of the video flowing be detected and replace including：
Judge whether each pixel is neighbor pixel around the pixel and the pixel in the non-key frame
Maximum brightness value or minimum luminance value；If it is non-noise otherwise to determine the pixel；
If maximum brightness value, then adjacent picture around the brightness value and the pixel and the pixel of the pixel is calculated
The difference of time big brightness value of vegetarian refreshments；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, such as
Otherwise fruit calculates in the brightness value and previous frame of the pixel neighbor pixel around same position pixel and the pixel
The difference of maximum brightness value；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if otherwise
It is noise to determine the pixel；
If minimum luminance value, then adjacent picture around the brightness value and the pixel and the pixel of the pixel is calculated
The difference of time small brightness value of vegetarian refreshments；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, such as
Otherwise fruit calculates in the brightness value and previous frame of the pixel neighbor pixel around same position pixel and the pixel
The difference of minimum luminance value；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if otherwise
It is noise to determine the pixel；
The brightness value of noise is replaced.
In one embodiment of the invention, the brightness value to noise is replaced, including：
The brightness value of the noise is replaced with to the average value of neighbor pixel around the noise；Alternatively,
If the noise has maximum brightness value, the brightness value of the noise is replaced with into the pixel and the pixel
The maximum brightness value of surrounding neighbor pixel and time weighted average of big brightness value, if the noise has minimum luminance value,
Then by the brightness value of the noise replace with around the pixel and the pixel minimum luminance value of neighbor pixel with it is time small
The weighted average of brightness value.
In one embodiment of the invention, the predetermined luminance threshold value is：
Maximum brightness error amount, the luminance errors do not see the maximum picture brightness value with black difference for naked eyes；Or
Person,
If the noise has maximum brightness value, for around the pixel and the pixel neighbor pixel it is time light
The 1/N of angle value；If the noise has minimum luminance value, for around the pixel and the pixel neighbor pixel it is time small
The 1/N of brightness value, N are the quantity of surrounding neighbor pixel；Alternatively,
If the noise has maximum brightness value, the geometry of brightness value and maximum brightness error amount for the pixel is put down
Mean value；If the noise has minimum luminance value, the geometric average of brightness value and minimum brightness error amount for the pixel
Value.
In one embodiment of the invention, the method is further included carries out color noise correction to image, including：
The picture frame of the video flowing is transformed into HSI color spaces；
If around the chromatic value of pixel and the pixel in neighbor pixel and previous frame same pixel point chromatic value
Chroma threshold is differed by more than, and the brightness value of the pixel is less than aforementioned predetermined luminance threshold value, the color saturation of the pixel is big
When color saturation threshold value, it is determined that the pixel is color noise；
Color correction is carried out to the color noise.
In one embodiment of the invention, it is described to be to color noise progress color correction：
The chromatic value of the color noise is replaced with into neighbor pixel and former frame identical bits around the color noise
Put in pixel with the immediate chromatic value of chromatic value of the color noise.
In one embodiment of the invention, the Chroma threshold takes pi/2, and color saturation threshold value takes 0.5.
In one embodiment of the invention, the non-key frame of the video flowing is detected and replaced and calculated using following
Method：
The maximum brightness value of neighbor pixel around each pixel and the pixel of the key frame is obtained, by described in
Maximum brightness value and respective coordinates are stored in first two-dimensional array；
Calculate in the non-key frame around each pixel and the pixel maximum brightness value of neighbor pixel and secondary
The maximum brightness value and respective coordinates are stored in second two-dimensional array by big brightness value；
Judge whether the brightness value of each pixel in the non-key frame is equal to around the pixel and the pixel
The maximum brightness value of neighbor pixel judges that neighbor pixel is most light around the pixel in the non-key frame if equal
Whether angle value and the difference of time big brightness value are more than luminance threshold, if more than then determining that the pixel is noise；
Exchange the pointer of first two-dimensional array and second two-dimensional array.
In one embodiment of the invention, the non-key frame of the video flowing is detected and replaced and calculated using following
Method：
The minimum luminance value of neighbor pixel around each pixel and the pixel of the key frame is obtained, by described in
Minimum luminance value and respective coordinates are stored in first two-dimensional array；
Calculate in the non-key frame around each pixel and the pixel minimum luminance value of neighbor pixel and secondary
The minimum luminance value and respective coordinates are stored in second two-dimensional array by small brightness value；
Judge whether the brightness value of each pixel in the non-key frame is equal to around the pixel and the pixel
The minimum luminance value of neighbor pixel judges that neighbor pixel minimum is bright around the pixel in the non-key frame if equal
Whether angle value and the difference of time small brightness value are more than luminance threshold, if more than then determining that the pixel is noise；
Exchange the pointer of first two-dimensional array and second two-dimensional array.
In one embodiment of the invention, the surrounding neighbor pixel is adjacent 8 neighborhood territory pixel point.
It is another aspect of this invention to provide that additionally provide it is a kind of using video image interframe difference to picture fast noise reduction
Device, described device include：Processor and the memory of computer program that can be run on a processor for storage；Its
In, the processor is above-mentioned quick to picture using video image interframe difference for when running the computer program, performing
The method of noise reduction.
Compared with prior art, the present invention has the advantages that：
(1) different from traditional noise-reduction method, the present invention considers video image by the dependence before and after video image
Similitude, identification noise that can be rapidly and efficiently increases substantially the speed and efficiency of noise reduction；
(2) it further under low-light level environment, is particularly susceptible and noise occurs, present invention is specifically directed to the scenes to be calculated
Method optimizes, with obvious effects；
(3) general noise reduction is needed by optical hardware, and the present invention needs not rely on light then based on Digital Image Processing
Hardware is learned, can greatly reduce cost.
Description of the drawings
Fig. 1 is a kind of in the embodiment of the present invention flow of picture fast noise reduction method to be shown using video image interframe difference
It is intended to；
Fig. 2 is a kind of in the embodiment of the present invention structure of picture fast noise reduction device to be shown using video image interframe difference
It is intended to.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, it is right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below
It does not constitute a conflict with each other and can be combined with each other.
An embodiment of the present invention provides it is a kind of using video image interframe difference to the method for picture fast noise reduction, such as Fig. 1
Shown, this method is specially：
S101. video flowing, the video stream packets consecutive image containing multiframe are acquired under night low-light level environment；
The present invention be suitable for night low-light level environment under video acquisition, in the environment of night low-light level, noise compared with
It is more, using targetedly algorithm of the invention, it can effectively and quickly solve the problems, such as noise.
S102. using the key frame of the video flowing as starting point, the non-key frame of the video flowing is detected, obtains institute
The maximum brightness value of neighbor pixel around pixel and the pixel in non-key frame is stated, by the brightness value of the pixel and institute
Maximum brightness value is stated to be compared；
The embodiment of the present invention since the key frame of video flowing, only check non-key frame noise because key frame and
Previous frame is not necessarily present similarity relation.
The maximum brightness value of non-key frame pixel and surrounding neighbor pixel is obtained, bubbling algorithm can be used to obtain this
Maximum brightness value, in the embodiment of the present invention surrounding neighbor pixel can be centered on the pixel around 8 points.For
For noise, brightness value needs to traverse successively each in non-key frame image it is possible that more much bigger than the brightness value of surrounding
The brightness value of point and the comparison of surrounding neighbor pixel maximum brightness value, so that it is determined that the whether doubtful noise of the point.
If conversely, the brightness value of the pixel is not brightness maxima, it is not doubtful noise that can exclude the point.
If S103. the brightness value of the pixel is the maximum brightness value, the maximum brightness value and the pixel are calculated
The difference of time big brightness value in point and surrounding neighbor pixel, if the luminance difference is more than luminance threshold, it is determined that the pixel
Point is doubtful noise；
S103 is specifically as follows：
Obtain the every bit of the key frame and the maximum brightness value of 8 consecutive points of surrounding, by the maximum brightness value and
Respective coordinates are stored in first two-dimensional array, are denoted as lumax [width] [height], wherein width and height are regarded respectively
The width and height of frequency.；
The maximum brightness value max of the pixel and 8 consecutive points of surrounding in the non-key frame is calculated using bubbling algorithm
And second largest value next, the maximum brightness value and respective coordinates are stored in second two-dimensional array, are denoted as lumaxtemp [x]
[y], wherein x, y are point coordinates；
Judge whether the brightness value of the pixel in the non-key frame is equal to the maximum brightness value, if thinking, sentence
Whether neighbor pixel maximum brightness value and the difference of time big brightness value are more than brightness around the pixel in the non-key frame of breaking
Threshold value, if more than, it is determined that the pixel is doubtful noise；That is, it is judged that (max-next)<threshold&&(max-lumax
[x][y])<Whether threshhold is true, if it is true, average value of the replacement present intensity value for eight brightness of surrounding.
Threshhold is luminance threshold.
Exchange the pointer of first two-dimensional array and second two-dimensional array, and repeat the bubbling algorithm calculate step and
Luminance threshold judgment step.
Wherein, the luminance threshold can take fixed value or float value.Fixed value can be that maximum brightness error amount is (described
Luminance errors does not see the maximum picture brightness value with black difference for naked eyes), float value can take the pixel brightness value
1/8 or the geometrical mean (square root that the two is multiplied) of the pixel brightness value and maximum brightness value error.
If the difference of the pixel and time big brightness value is less than or equal to luminance threshold, also it is not considered as that the point is made an uproar to be doubtful
Point, then the brightness for continuing next point differentiates, until all the points traverse completely.
S104. the brightness value of the doubtful noise is replaced.
Step S104 is specifically as follows：The brightness value of the doubtful noise is replaced with into being averaged for around neighbor pixel
Value or, the weighted average that the brightness value of the doubtful noise is replaced with to the maximum brightness value and described time big brightness value.
For night scene, to consider that quickly movement causes bright spot always to remove our detection range (only one pixels to the independent bright spot of background
It is wide) occasion, such as distant place car bulb or distant place street lamp light.In view of distant place automobile little, most lamp is influenced on driving
Light is also impossible to always only have 1 pixel wide, can ignore, if having to consider such situation, can replace doubtful noise
Weighted average for most bright spot and time bright spot.
Further, in the step s103, if the luminance difference is more than luminance threshold, can also include：It calculates
In the brightness value and previous frame of the pixel around same position pixel and the pixel neighbor pixel maximum brightness value
Difference；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if otherwise determining the pixel
Point is noise；
After being compared i.e. in same frame with neighborhood territory pixel point, also with the brightness value of previous frame same position pixel into
Row comparison, to further determine whether as noise.
Still optionally further, for low-light level video intensified image, the correction of color noise can also be done.Then the method is also
Including：
The video frame images are converted into HSI color spaces；
If 8 points of chromatic value H and surrounding of the pixel differ by more than Chroma threshold, and the pixel is identical with previous frame
Location point colour difference is more than the Chroma threshold, and pixel brightness value I is less than aforementioned predetermined luminance threshold value, color saturation S
During more than color saturation threshold value, it is color noise to determine the pixel.Wherein, Chroma threshold can take pi/2, color saturation threshold value
0.5 can be taken；
The chromatic value of the color noise is replaced with around the pixel in 8 points and former frame same position point, with
The chromatic value of the immediate point of current color angle value.
Further, the situation that noise is maximum brightness value is only described in above-described embodiment, it, can for minimum luminance value
The rest may be inferred with corresponding, i.e., carries out comparison judgement using minimum luminance value as standard.
Different from traditional noise-reduction method, the present invention considers video image by the dependence before and after video image
Similitude, identification noise that can be rapidly and efficiently increase substantially the speed and efficiency of noise reduction, in addition, for low-light level environment
Under, it is particularly susceptible and noise occurs, present invention is specifically directed to the scenes to have carried out algorithm optimization, with obvious effects.Meanwhile general drop
Making an uproar needs by optical hardware, and the present invention needs not rely on optical hardware, can greatly reduce into then based on Digital Image Processing
This.
The embodiment of the present invention additionally provides a kind of device using video image interframe difference to picture fast noise reduction, the dress
Put including：Processor and the memory of computer program that can be run on a processor for storage, wherein, the processor
The above-mentioned method using video image interframe difference to picture fast noise reduction is performed during for running the computer program.
The embodiment of the present invention additionally provides a kind of storage medium, is stored thereon with computer instruction, and the instruction is by processor
The above-mentioned method using video image interframe difference to picture fast noise reduction is realized during execution.
Fig. 2 is a kind of server architecture schematic diagram provided in an embodiment of the present invention.The server 200 can include one or
More than one central processing unit (central processing units, CPU) 210 is (for example, one or more are handled
Device) and memory 220, one or more storage application programs 232 or data 234 storage medium 230 (such as one or
More than one mass memory unit).Wherein, memory 220 and storage medium 230 can be of short duration storage or persistent storage.It deposits
The program stored up in storage medium 230 can include one or more modules (diagram is not shown), and each module can include
Series of instructions in server are operated.Further, central processing unit 210 could be provided as logical with storage medium 230
Letter performs the series of instructions operation in storage medium 230 on server 200.Server 200 can also include one or one
A Yi Shang power supply 240, one or more wired or wireless network interfaces 250, one or more input/output interfaces
260 and/or, one or more operating systems 270, such as Windows ServerTM, Mac OS XTM, UnixTM,
LinuxTM, FreeBSDTM etc..Step performed by above method embodiment can be based on the server knot shown in Fig. 2
Structure.
It should be understood that in the various embodiments of the application, the size of the serial number of each process is not meant to execution sequence
Successively, the execution sequence of each process should be determined with its function and internal logic, the implementation process without coping with the embodiment of the present application
Form any restriction.
Those of ordinary skill in the art may realize that each exemplary moulds described with reference to the embodiments described herein
Block and method and step can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is performed with hardware or software mode, specific application and design constraint depending on technical solution.Professional technician
Described function can be realized using distinct methods to each specific application, but this realization is it is not considered that exceed
Scope of the present application.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and module can refer to the corresponding process in preceding method embodiment, and details are not described herein.
The various pieces of this specification are described by the way of progressive, identical similar portion between each embodiment
Point just to refer each other, and what each embodiment introduced is and other embodiment difference.Especially for device and it is
For embodiment of uniting, since it is substantially similar to embodiment of the method, so description is fairly simple, related part is referring to method reality
Apply the explanation of example part.
Finally, it should be noted that：The foregoing is merely the preferred embodiments of technical scheme, are not intended to
Limit the protection domain of the application.Obviously, those skilled in the art can carry out the application various modification and variations without de-
From scope of the present application.If these modifications and variations of the application belong to the range of the application claim and its equivalent technologies
Within, then any modification, equivalent replacement, improvement and so on, should be included within the protection domain of the application.
Claims (10)
1. it is a kind of using video image interframe difference to the method for picture fast noise reduction, which is characterized in that including：
Determine to treat the first frame key frame of de-noising video stream, using the first frame key frame as starting point, to the non-of the video flowing
Key frame is detected, until encountering next frame key frame, then using the next frame key frame as starting point, to the video flowing
Non-key frame is detected and replaces, and repeats the above detection of the process until completing all non-key frames；Wherein to described
The non-key frame of video flowing be detected and replace including：
Judge each pixel in the non-key frame whether be neighbor pixel around the pixel and the pixel maximum
Brightness value or minimum luminance value；If it is non-noise otherwise to determine the pixel；
If maximum brightness value, then neighbor pixel around the brightness value and the pixel and the pixel of the pixel is calculated
Time big brightness value difference；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if not
Then calculate the maximum of neighbor pixel around same position pixel and the pixel in the brightness value and previous frame of the pixel
The difference of brightness value；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if otherwise determined
The pixel is noise；
If minimum luminance value, then neighbor pixel around the brightness value and the pixel and the pixel of the pixel is calculated
Time small brightness value difference；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if not
Then calculate the minimum of neighbor pixel around same position pixel and the pixel in the brightness value and previous frame of the pixel
The difference of brightness value；If the difference is less than predetermined luminance threshold value, it is determined that the pixel is non-noise, if otherwise determined
The pixel is noise；
The brightness value of noise is replaced.
2. it is according to claim 1 using video image interframe difference to the method for picture fast noise reduction, which is characterized in that
The brightness value to noise is replaced, including：
The brightness value of the noise is replaced with to the average value of neighbor pixel around the noise；Alternatively,
If the noise has maximum brightness value, the brightness value of the noise is replaced with around the pixel and the pixel
The maximum brightness value of neighbor pixel and time weighted average of big brightness value, will if the noise has minimum luminance value
The brightness value of the noise replaces with the minimum luminance value of neighbor pixel and time small brightness around the pixel and the pixel
The weighted average of value.
3. it is according to claim 1 or 2 using video image interframe difference to the method for picture fast noise reduction, feature exists
In the predetermined luminance threshold value is：
Maximum brightness error amount, the luminance errors do not see the maximum picture brightness value with black difference for naked eyes；Alternatively,
If the noise has maximum brightness value, time big brightness value for neighbor pixel around the pixel and the pixel
1/N；If the noise has minimum luminance value, time small brightness for neighbor pixel around the pixel and the pixel
The 1/N of value, N are the quantity of surrounding neighbor pixel；Alternatively,
If the noise has maximum brightness value, the geometric average of brightness value and maximum brightness error amount for the pixel
Value；If the noise has minimum luminance value, the geometrical mean of brightness value and minimum brightness error amount for the pixel.
4. it is according to claim 1 or 2 using video image interframe difference to the method for picture fast noise reduction, feature exists
In, the method is further included carries out color noise correction to image, including：
The picture frame of the video flowing is transformed into HSI color spaces；
If around the chromatic value of pixel and the pixel in neighbor pixel and previous frame same pixel point chromatic value difference
More than Chroma threshold, and the brightness value of the pixel is less than aforementioned predetermined luminance threshold value, and the color saturation of the pixel is more than color
During saturation degree threshold value, it is determined that the pixel is color noise；
Color correction is carried out to the color noise.
5. it is according to claim 4 using video image interframe difference to the method for picture fast noise reduction, which is characterized in that
It is described to be to color noise progress color correction：
The chromatic value of the color noise is replaced with into neighbor pixel and former frame same position picture around the color noise
In vegetarian refreshments with the immediate chromatic value of chromatic value of the color noise.
6. it is according to claim 4 using video image interframe difference to the method for picture fast noise reduction, which is characterized in that
The Chroma threshold takes pi/2, and color saturation threshold value takes 0.5.
7. it is according to claim 1 or 2 using video image interframe difference to the method for picture fast noise reduction, feature exists
In being detected and replaced using following algorithm to the non-key frame of the video flowing：
The maximum brightness value of neighbor pixel around each pixel and the pixel of the key frame is obtained, by the maximum
Brightness value and respective coordinates are stored in first two-dimensional array；
Calculate in the non-key frame around each pixel and the pixel maximum brightness value of neighbor pixel and secondary light
The maximum brightness value and respective coordinates are stored in second two-dimensional array by angle value；
Judge whether the brightness value of each pixel in the non-key frame is adjacent equal to around the pixel and the pixel
The maximum brightness value of pixel judges in the non-key frame neighbor pixel maximum brightness value around the pixel if equal
And whether the difference of secondary big brightness value is more than luminance threshold, if more than then determining that the pixel is noise；
Exchange the pointer of first two-dimensional array and second two-dimensional array.
8. it is according to claim 1 or 2 using video image interframe difference to the method for picture fast noise reduction, feature exists
In being detected and replaced using following algorithm to the non-key frame of the video flowing：
The minimum luminance value of neighbor pixel around each pixel and the pixel of the key frame is obtained, by the minimum
Brightness value and respective coordinates are stored in first two-dimensional array；
Calculate in the non-key frame around each pixel and the pixel minimum luminance value of neighbor pixel and secondary small bright
The minimum luminance value and respective coordinates are stored in second two-dimensional array by angle value；
Judge whether the brightness value of each pixel in the non-key frame is adjacent equal to around the pixel and the pixel
The minimum luminance value of pixel judges in the non-key frame neighbor pixel minimum luminance value around the pixel if equal
And whether the difference of secondary small brightness value is more than luminance threshold, if more than then determining that the pixel is noise；
Exchange the pointer of first two-dimensional array and second two-dimensional array.
9. it is according to claim 1 or 2 using video image interframe difference to the method for picture fast noise reduction, feature exists
In the surrounding neighbor pixel is adjacent 8 neighborhood territory pixel point.
10. it is a kind of using video image interframe difference to the device of picture fast noise reduction, which is characterized in that described device includes：
Processor and the memory of computer program that can be run on a processor for storage；Wherein, the processor is used to transport
During the row computer program, perform claim requires 1 to 9 any one of them quick to picture using video image interframe difference
The method of noise reduction.
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| CN112052726A (en) * | 2020-07-28 | 2020-12-08 | 北京极豪科技有限公司 | Image processing method and device |
| CN112950489A (en) * | 2021-01-12 | 2021-06-11 | 辽宁省视讯技术研究有限公司 | Three-dimensional field noise reduction method based on multiple exposures |
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