CN110166707A - Image processing method, device, electronic equipment and storage medium - Google Patents
Image processing method, device, electronic equipment and storage medium Download PDFInfo
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- CN110166707A CN110166707A CN201910509580.XA CN201910509580A CN110166707A CN 110166707 A CN110166707 A CN 110166707A CN 201910509580 A CN201910509580 A CN 201910509580A CN 110166707 A CN110166707 A CN 110166707A
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- noise reduction
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- original image
- dynamic range
- multiframe
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/61—Control of cameras or camera modules based on recognised objects
- H04N23/611—Control of cameras or camera modules based on recognised objects where the recognised objects include parts of the human body
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/741—Circuitry for compensating brightness variation in the scene by increasing the dynamic range of the image compared to the dynamic range of the electronic image sensors
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
- H04N23/81—Camera processing pipelines; Components thereof for suppressing or minimising disturbance in the image signal generation
Abstract
This application discloses a kind of image processing method, device, electronic equipment and storage mediums, wherein method includes: acquisition preview screen, and determines the dynamic range of preview screen and acquire the picture moving degree of picture recently relatively；According to dynamic range and picture moving degree, evaluation of estimate is determined；If evaluation of estimate is less than first threshold, and picture moving degree is less than second threshold, it is determined that acquires multiframe original image using the under exposed mode of multiframe；It synthesizes to obtain high dynamic range images according to multiframe original image；According to ambient brightness, matched noise reduction model is determined；Using noise reduction model to high dynamic range images noise reduction, to obtain target night scene image, this method makes syncretizing effect more naturally, while reducing the discontinuous noise of image, ensure that image high dynamic and clarity, reduce extra image processing time.
Description
Technical field
This application involves technical field of image processing more particularly to a kind of image processing method, device, electronic equipment and
Computer readable storage medium.
Background technique
With the continuous development of intelligent terminal technology, more and more users like through the camera function on intelligent terminal
Carry out photograph taking.As the normalization for the demand taken pictures develops, the demand of taking pictures for how more preferably meeting user becomes development
Main way, for example, meeting clearly taking pictures demand in the more scenes of user at night, in the daytime.
In the related technology, under night scene or half-light environment, the identical exposure value of acquisition number frame and several deficient images exposed are right
The image of identical exposure value does multiframe noise reduction, and then and the deficient image exposed is high dynamic range images (High-Dynamic
Range, abbreviation HDR) fusion, high dynamic and clean night scene image are provided simultaneously with to reach.But the image of different exposure values
Noise performance differs greatly, and for the region of discontinuous noise caused by the frame fusion from different exposure values, carries out spatial domain
Noise reduction process, the phenomenon that mitigate discontinuous noise, will lead to the loss of the details of part luma.
Summary of the invention
The purpose of the application is intended to solve at least some of the technical problems in related technologies.
For this purpose, first purpose of the application is to propose a kind of image processing method, this method makes image syncretizing effect
More naturally, reducing the discontinuous noise of image, ensure that image high dynamic and it is clean while when reducing image procossing
Between.
Second purpose of the application is to propose a kind of image processing apparatus.
The third purpose of the application is to propose a kind of electronic equipment.
The 4th purpose of the application is to propose a kind of computer readable storage medium.
In order to achieve the above object, the application first aspect embodiment proposes a kind of image processing method, comprising: acquisition preview
Picture, and determine the dynamic range of the preview screen and acquire the picture moving degree of picture recently relatively；According to described dynamic
State range SdWith the picture moving degree Sm, determine evaluation of estimate Sf；Wherein, SfWith Sd(1-Sm) directly proportional；If institute's evaluation values
SfLess than the first threshold, and the picture moving degree SmLess than second threshold, it is determined that use the under exposed mode of multiframe
Acquire multiframe original image；It synthesizes to obtain high dynamic range images according to the multiframe original image；According to ambient brightness, determine
Matched noise reduction model；Using the noise reduction model to the high dynamic range images noise reduction, to obtain target night scene image.
The image processing method of the embodiment of the present application by acquiring preview screen, and determines the dynamic of the preview screen
Range and the picture moving degree for acquiring picture recently relatively；According to the dynamic range SdWith the picture moving degree Sm, really
Accepted opinion is worth Sf；Wherein, SfWith Sd(1-Sm) directly proportional；If institute evaluation values SfLess than the first threshold, and the picture moves
Traverse degree SmLess than second threshold, it is determined that acquire multiframe original image using the under exposed mode of multiframe；According to the multiframe
Original image synthesizes to obtain high dynamic range images；According to ambient brightness, matched noise reduction model is determined；Using the noise reduction mould
Type is to the high dynamic range images noise reduction, to obtain target night scene image.Dynamic range of this method based on preview screen and
Picture moving degree determines optimum exposure mode, and defines and carry out noise reduction after image co-registration under the under-exposure mode of multiframe, makes
Syncretizing effect more naturally, while reducing the discontinuous noise of image, ensure that image high dynamic and clarity, reduces
Extra image processing time.
In order to achieve the above object, the application second aspect embodiment proposes a kind of image processing apparatus, comprising: preview screen
Acquisition module, for acquiring preview screen；First determining module, for determining the dynamic range and relatively most of the preview screen
The picture moving degree of nearly acquisition picture；Second determining module, for according to the dynamic range SdWith the picture moving journey
Spend Sm, determine evaluation of estimate Sf；Wherein, SfWith Sd(1-Sm) directly proportional；Original image acquisition module, in institute evaluation values SfIt is small
In the first threshold, and the picture moving degree SmLess than second threshold, it is determined that adopted using the under exposed mode of multiframe
Collect multiframe original image；Image synthesis module, for synthesizing to obtain high dynamic range images according to the multiframe original image；Drop
It makes an uproar model determining module, for determining matched noise reduction model according to ambient brightness；Noise reduction module, for using the noise reduction
Model is to the high dynamic range images noise reduction, to obtain target night scene image.
The image processing apparatus of the embodiment of the present application by acquiring preview screen, and determines the dynamic of the preview screen
Range and the picture moving degree for acquiring picture recently relatively；According to the dynamic range SdWith the picture moving degree Sm, really
Accepted opinion is worth Sf；Wherein, SfWith Sd(1-Sm) directly proportional；If institute evaluation values SfLess than the first threshold, and the picture moves
Traverse degree SmLess than second threshold, it is determined that acquire multiframe original image using the under exposed mode of multiframe；According to the multiframe
Original image synthesizes to obtain high dynamic range images；According to ambient brightness, matched noise reduction model is determined；Using the noise reduction mould
Type is to the high dynamic range images noise reduction, to obtain target night scene image.The device can realize the dynamic based on preview screen
Range and picture moving degree, determine optimum exposure mode, and define and carry out after image co-registration under the under-exposure mode of multiframe
Noise reduction, make syncretizing effect more naturally, reduce the discontinuous noise of image, ensure that image high dynamic and clarity it is same
When, reduce extra image processing time.
In order to achieve the above object, the application third aspect embodiment proposes a kind of electronic equipment, including imaging sensor, deposit
Reservoir, processor and it is stored in the computer program that can be run on the memory and on the processor；Wherein, the place
Reason device is corresponding with the executable program code to run by reading the executable program code stored in the memory
Program, for realizing image processing method described in the application first aspect embodiment.
In order to achieve the above object, the application fourth aspect embodiment proposes a kind of computer readable storage medium, deposit thereon
Computer program is contained, which realizes when being executed by processor at image described in the application first aspect embodiment
Reason method.
The additional aspect of the application and advantage will be set forth in part in the description, and will partially become from the following description
It obtains obviously, or recognized by the practice of the application.
Detailed description of the invention
Fig. 1 is the flow diagram according to the image processing method of the application one embodiment；
Fig. 2 is the flow diagram according to the image processing method of second embodiment of the application；
Fig. 3 is the flow diagram according to the image processing method of the application third embodiment；
Fig. 4 is the structural schematic diagram according to the image processing apparatus of the application one embodiment；
Fig. 5 is the structural schematic diagram of the electronic equipment provided according to the application one embodiment；
Fig. 6 is the schematic illustration of the electronic equipment provided according to the application one embodiment；
Fig. 7 is the schematic illustration of the image processing circuit provided according to the application one embodiment.
Specific embodiment
Embodiments herein is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to for explaining the application, and should not be understood as the limitation to the application.
Below with reference to the accompanying drawings the image processing method of the embodiment of the present application, device, electronic equipment and computer-readable are described
Storage medium.
Fig. 1 is the flow diagram according to the image processing method of the application one embodiment.
Step 101, preview screen is acquired, and determines the dynamic range of preview screen and acquires the picture of picture recently relatively
Mobile degree.
In the embodiment of the present application, preview screen can be the image frame taken pictures on interface for being shown in imaging device,
During imaging device acquires image frame, preview interface can be shown according to the shooting operation of user, in electronic equipment
Preview interface carry out display image frame, and get the imaging device acquisition preview screen so that being adopted in image
User can clearly see the imaging effect of each frame image during collection.
Wherein, dynamic range refers in image frame brightest area to the range of most dark areas.
In the embodiment of the present application, it counts excessively sudden and violent region (brightness is greater than 220) in preview screen and crosses dark areas (brightness
Less than area 30), calculate these regions the gross area account for preview screen the gross area ratio, and the ratio is normalized to
The score as the dynamic range and is denoted as S by the score between 0~1d, work as SdIt is bigger, indicate that the dynamic range of picture is got over
It is high.
In the embodiment of the present application, count preview screen in moving area area, calculate moving area the gross area account for it is pre-
The ratio look in the picture gross area, and the ratio is normalized into the score between 0~1, it is denoted as Sm, relatively most for preview screen
The picture moving degree of nearly acquisition image.
Step 102, according to dynamic range SdWith picture moving degree Sm, determine evaluation of estimate Sf；Wherein, SfWith Sd(1-Sm) at
Direct ratio.
Specifically, SfWith Sd(1-Sm) directly proportional；That is, dynamic range is bigger, evaluation of estimate is bigger；Picture moving journey
Degree is bigger, and evaluation of estimate is smaller.
In the embodiment of the present application, determines the dynamic range of preview screen and acquire the picture moving degree of picture recently relatively
Afterwards, following formula can be used, determine evaluation of estimate.
Sf=Sd(1-Sm)*δ
Wherein, S in formuladFor dynamic range, SmFor picture moving degree, SfFor evaluation of estimate, δ is regulation coefficient.
Step 103, if evaluation of estimate SfLess than first threshold, and picture moving degree SmLess than second threshold, it is determined that use
The under exposed mode of multiframe acquires multiframe original image.
In the embodiment of the present application, evaluation of estimate S is being determinedfLess than first threshold, and picture moving degree SmLess than the second threshold
When value, determines and multiframe original image is acquired using the under exposed mode of multiframe.
It is understood that evaluation of estimate SfLess than first threshold, it may be possible to since the dynamic range of preview screen is smaller or
It is that picture moving degree is very big, further, if picture moving degree SmWhen less than second threshold, indicate that there is only small for picture
Partial movement degree and there are a degree of light ratio and dynamic ranges for preview screen is adopted using the under exposed mode of multiframe at this time
Collect multiframe original image, stronger can restore object to be captured, thus after multiframe original image synthesizes high dynamic range images,
The image of synthesis can be more reservation image details.
Step 104, it synthesizes to obtain high dynamic range images according to multiframe original image.
In the embodiment of the present application, it determines after acquiring multiframe original image using the under exposed mode of multiframe, by multiframe original
Beginning image inputs high dynamic synthetic model, to obtain the synthetic weight in each region in corresponding original image；According to synthetic weight, divide
Region synthesizes multiframe original image, to obtain high dynamic range images.Wherein, it should be noted that high dynamic synthesis
Model has passed through study and has obtained the mapping relations in original image between the feature and synthetic weight in each region；Wherein, feature is used
In the brightness of image of characterization light exposure and corresponding region.
Step 105, according to ambient brightness, matched noise reduction model is determined.
It is understood that due to the imaging sensor in electronic equipment will receive during shooting it is different degrees of
Photoelectricity magnetic disturbance between peripheral circuit and pixel itself, therefore the obtained original image of shooting inevitably exists and makes an uproar
Sound, also, the difference of annoyance level, the clarity of the image shot be not also identical.Therefore it is original to shoot obtained multiframe
Image also certainly exists noise, and the high dynamic range images that multiframe original image synthesizes also certainly exist noise, need into
One step carries out noise reduction process to high dynamic range images.For example, in night scene photographed scene, usually using biggish aperture and compared with
The long time for exposure shoots to obtain image, at this time if selecting higher sensitivity to reduce the time for exposure, shoots
Image will necessarily generate noise.
It is understood that selecting noise reduction model to carry out noise reduction to obtain the noise reduction effect of preferable artificial intelligence
When, as shown in Fig. 2, the noise reduction model is trained in advance using training sample set, it is special to improve noise reduction model identification noise
The ability of property.Specific step is as follows:
Step 201, training sample set is obtained, wherein it includes the sample graph shot under each ambient brightness that training sample, which is concentrated,.
In the embodiment of the present application, image that imaging device is shot under each ambient brightness can be used as sample graph.
Step 202, it is concentrated from training sample, chooses the target sample figure shot under identical ambient brightness.
Step 203, the sensitivity used when by target sample figure according to shooting is divided into multiple groups, the corresponding drop of training each group
It makes an uproar model, wherein noise reduction model has learnt to obtain the mapping relations between the sensitivity and noise characteristic of target sample figure.
Step 204, the sensitivity of the target sample figure used according to the accuracy of noise reduction model and training, it is corresponding from each group
Noise reduction model in, the determining noise reduction model with respective environment brightness matching.
Further, after being trained to the corresponding noise reduction model of each group, the noise reduction effect of each noise reduction model is commented
Estimate, to obtain the accuracy of each noise reduction model.In turn, the target sample figure used according to the accuracy of noise reduction model and training
Sensitivity, from the corresponding noise reduction model of each group, the determining noise reduction model with respective environment brightness matching, according to noise reduction model
To high dynamic range images noise reduction, to improve picture quality.
As a kind of possible implementation of the embodiment of the present application, used according to the accuracy of noise reduction model and training
The sensitivity of target sample figure, from the corresponding noise reduction model of each group, when determining the noise reduction model with respective environment brightness matching,
It can determine that accuracy is greater than the noise reduction model of threshold value, as candidate noise reduction model from the corresponding noise reduction model of each group.In turn
From candidate noise reduction model, choose the maximum candidate noise reduction model of target sample figure sensitivity that training uses as should with it is corresponding
The matched noise reduction model of ambient brightness.As a result, 201~204 different brightness values pair can be trained in advance through the above steps
Answer the noise reduction model of sensitivity.
In this step, the noise reduction of sensitivity can be corresponded to from the different brightness values trained in advance according to ambient brightness
In model, the noise reduction model with the current environment brightness matching is determined, image drop is carried out using the noise reduction model so as to subsequent
It makes an uproar.
Step 106, using noise reduction model to high dynamic range images noise reduction, to obtain target night scene image.
It is dynamic to height using the noise reduction model after determining matched noise reduction model according to ambient brightness in the embodiment of the present application
State range image carry out noise reduction process, can simultaneously in high dynamic range images highlight area and half-light region drop
It makes an uproar, and then the target night scene image of available preferable noise reduction effect.
As a kind of possible implementation, noise reduction model can be used, noise characteristic is carried out to high dynamic range images
Identification；Wherein, noise reduction model has learnt to obtain the mapping relations between the sensitivity of high dynamic range images and noise characteristic.
In turn, according to the noise characteristic identified, to high dynamic range images noise reduction, to obtain target noise-reduced image.Wherein, photosensitive
Degree, also known as ISO value refer to and measure egative film for the index of the sensitivity level of light.Egative film lower for sensitivity, needs to expose
The light longer time is to reach the identical imaging with the higher egative film of sensitivity.The sensitivity of digital camera is a kind of similar to glue
Roll up a kind of index of sensitivity, the ISO of digital camera can by adjusting sensor devices sensitivity or merge sensitivity speck
Adjustment, that is to say, that can be reached by promoting the light sensitivity of sensor devices or merging several adjacent sensitivity specks
Promote the purpose of ISO.
It should be noted that either digital or egative film photography, ISO value is lower, and the picture quality of acquisition is higher, image
Details performance is finer and smoother, and ISO value is higher, and light sensing performance is stronger, also more can receive more light, to generate more
Heat more noise therefore would generally be introduced using relatively high sensitivity, so as to cause picture quality reduction.
Since noise reduction model has learnt to obtain the mapping relations between the sensitivity of high dynamic range images and noise characteristic.
Therefore, it can will be inputted in noise reduction model by the high dynamic range images of high dynamic synthesis, with dynamic to height using noise reduction model
State range image carries out noise characteristic identification and is made an uproar to identify the noise characteristic of high dynamic range images according to what is identified
Sound characteristics carry out noise reduction to high dynamic range images, obtain target noise-reduced image, to achieve the purpose that noise reduction, improve
The signal-to-noise ratio of image.In addition, multiframe original image by first being carried out the artificial intelligence just carried out after high dynamic fusion by the application
Noise reduction because the performance of identical under exposed noise be it is similar, it is owe exposure frames in addition to fused discontinuous noise is unobvious other than more
Blending algorithm is also more more natural using the syncretizing effect of time-domain noise reduction, does not need by the individual noise reductions of the input of so multiframe, only
The processing for doing an artificial intelligence noise reduction is all done noise reduction and merged again compared to every frame decreases many operation time.
In the embodiment of the present application, noise characteristic can be the statistical property of the random noise as caused by imaging sensor.This
In the noise said mainly include thermal noise and shot noise, wherein thermal noise meets Gaussian Profile, and shot noise meets Poisson point
Cloth, the statistical property in the embodiment of the present application can refer to the variance yields of noise, naturally it is also possible to it is the value of other possible situations,
This is without limitation.
Certainly, the noise reduction model in the present embodiment is only a kind of possible realization for realizing the noise reduction based on artificial intelligence
Mode can realize the noise reduction based on artificial intelligence by any other possible mode in practical implementation, than
Such as, it can also be realized using traditional programming technique (such as simulation and ergonomic method), for another example, can be calculated with science of heredity
Method is realized.
Based on the above embodiment, in step 103 determine using the under exposed mode of multiframe acquire multiframe original image it
Afterwards, as shown in figure 3, can also compensate according to exposure compensation mode to benchmark exposure time, each frame original image pair is determined
The compensation exposure time answered.Specific step is as follows:
Step 301, corresponding exposure compensation mode is determined according to the under exposed mode of multiframe；Wherein, exposure compensation mode,
It is used to indicate the frame number and the corresponding exposure compensating grade of each frame original image of original image.
In the present embodiment, according to the Exposure mode of exposure value different in the under exposed mode of multiframe, determine wait adopt
The number of image frames of collection can also be different, and when original image frame number difference to be collected, it needs using different exposure compensatings etc.
Grade.
Step 302, according to picture moving degree Sm, determine benchmark sensitivity.
It is understood that the picture of preview image is relative to nearest acquisition during acquiring multiframe original image
There is movement in the picture of image, be as caused by the shake of the imaging device of acquisition multiframe original image.Also, it draws
There are positively related relationships for the mobile degree in face and the degree of jitter of imaging device.It therefore, can be more according to acquiring in the present embodiment
The degree of jitter of the imaging device of frame original image determines benchmark sensitivity.
In the present embodiment, in the case where benchmark sensitivity is lower value when acquisition multiframe original image, figure can reduce
As noise, synthesize by acquiring the lower image of multiframe sensitivity simultaneously, and by the multiple image of acquisition to generate high dynamic range
The mode of image is enclosed, can not only promote the dynamic range and overall brightness of night scene shooting image, and pass through control sensitivity
Value, effectively inhibit image in noise, improve night scene shooting image quality.
It is understood that the sensitivity of acquisition image influences whether whole shooting duration of video, shooting duration of video is too long, may
The degree of jitter aggravation of imaging device when will lead to hand-held shooting, to influence picture quality.It therefore, can be according to imaging device
Current degree of jitter adjusts the corresponding benchmark sensitivity of each frame image to be collected, so that shooting duration of video control is suitable
In range.
Specifically, if imaging device it is current degree of jitter it is smaller, can be by the corresponding benchmark of every frame image to be collected
Sensitivity can the appropriate lesser value of boil down to, effectively to inhibit the noise of every frame image, improve the quality of shooting image；If at
As the current degree of jitter of equipment is larger, then the corresponding benchmark sensitivity of every frame image to be collected can be properly increased for
Biggish value, to shorten shooting duration of video.
For example, however, it is determined that the current degree of jitter of imaging device is " non-jitter ", then can be true by benchmark sensitivity
It is set to lesser value, to obtain higher-quality image as far as possible, for example determines that benchmark sensitivity is 100；If it is determined that imaging device
Current degree of jitter is " slight jitter ", then benchmark sensitivity can be determined as to biggish value, to reduce shooting duration of video, than
Such as determine that benchmark sensitivity is 200；If it is determined that the current degree of jitter of imaging device is " small shake ", then can further increase
Benchmark sensitivity to reduce shooting duration of video, for example determines that benchmark sensitivity is 220；If it is determined that the shake journey that imaging device is current
Degree is " big shake ", then can determine that current degree of jitter is excessive, can further increase benchmark sensitivity at this time, to reduce
Shooting duration of video, for example determine that benchmark sensitivity is 250.
It should be noted that the example above is exemplary only, the limitation to the application cannot be considered as.In actual use,
It, can be by adjusting benchmark sensitivity, to obtain optimal scheme when the variation of the degree of jitter of imaging device.Wherein, it is imaged
The mapping relations of the degree of jitter of equipment benchmark sensitivity corresponding with every frame image to be collected, can be pre- according to actual needs
If.
It should be noted that according to the degree of jitter of imaging device, when adjusting benchmark sensitivity corresponding with degree of jitter,
If current base sensitivity and degree of jitter are just adapted, adjusting the result is that benchmark sensitivity remains unchanged.It is such
Situation also belongs in the embodiment of the present application the scope of " adjustment ".
In addition, under a kind of possible application scenarios, the camera module of imaging device be made of a plurality of lenses, thus
Different camera lenses can also correspond to different sensitivity under same shooting environmental, and the benchmark sensitivity adjusted in this step should
It is for the shooting process executed for a camera lens in a plurality of lenses, in this shooting process, acquisition multiple image is equal
Using same benchmark sensitivity.
In addition, being not limited to adjust benchmark sensitivity according only to the degree of jitter of imaging device, may be used also in the embodiment of the present application
To determine benchmark sensitivity according to the multiple parameters such as the luminance information of degree of jitter and photographed scene are comprehensive, do not limit herein
It is fixed.
Step 303, according to the benchmark sensitivity of the luminance information of photographed scene and setting, benchmark exposure time is determined.
Wherein, exposure time refers to time of the light by camera lens.
In the embodiment of the present application, the luminance information of photographed scene, the survey optical module survey light that can use in imaging device is obtained
It arrives, is also possible to get by the luminance information in preview screen, it is not limited here.The luminance information is usually with shooting
The illuminance of scene could be aware that as brightness measurement index, those skilled in the art, can also be carried out using other indexs bright
Degree is measured, within the scope of the present embodiment.
Specifically, it using auto-exposure control (Auto Exposure Control, abbreviation AEC) algorithm, determines current
The corresponding light exposure of luminance information is in turn more according to the luminance information of photographed scene and benchmark sensitivity these two aspects information
Each frame image to be collected determines benchmark exposure time in frame image to be collected.
Step 304, according to exposure compensation mode, benchmark exposure time is compensated, determines that each frame original image is corresponding
Compensation exposure time.
In the embodiment of the present application, when imaging device acquires the Exposure mode difference that multiframe original image uses, determine
The preset exposure bias value of each frame image to be collected is not also identical.In such a case, it is possible to the shake of default imaging device
Mapping relations between degree and exposure bias value, according to the degree of jitter of imaging device, to determine that current each frame is to be collected
The preset exposure bias value of image.
For example, when can be " non-jitter " by the degree of jitter of imaging device, the corresponding exposure of each frame image to be collected
The exposure value range of offset is preset as -6~2, and the difference between adjacent exposure value is 0.5；By the shake of imaging device
Degree is " slight jitter ", and the exposure value range of the corresponding exposure bias value of each frame image to be collected is preset as -5~1, and phase
Difference between adjacent exposure value is 1, etc..
As alternatively possible way of realization, whether the preview screen for detecting imaging device includes face, preview screen
In comprising face with do not include face when, the night scene mode for being applicable in present filming scene is not identical, and each frame thereby determined that waits adopting
It is also not identical to collect the preset exposure bias value of image.
Whether identical degree of jitter can be wrapped according in preview screen as another possible implementation
Containing face, determine each frame image to be collected using different exposure bias values.It therefore, can be right for identical degree of jitter
It should be in multiple exposure bias values.For example, the degree of jitter of imaging device is " slight jitter ", the preset exposure of each frame image to be collected
Light offset has comprising face and without two kinds of situations of face.
In night scene mode, when in image to be collected including face, the intensity of illumination of human face region is usually lower, thus
Lead to determining benchmark light exposure, it is higher compared with the benchmark light exposure determined when not including face, if when comprising face still
Excessive overexposure frame is so acquired, then is easy to cause human face region overexposure, the imaging effect so as to cause acquisition image is poor, right
The exposure compensation mode answered needs to have lower exposure compensating range.Therefore, for identical degree of jitter, in preview screen
Comprising face compared with when not including face, it is being determined whether the current degree of jitter of imaging device and preview screen wrap
After face, that is, it can determine that the preset exposure bias value being consistent with current actual conditions.
In the embodiment of the present application, after the benchmark sensitivity and corresponding compensation exposure time for determining each frame original image,
It controls imaging device and image is acquired according to the benchmark sensitivity of each frame original image and corresponding compensation exposure time, do not do herein
Specifically repeat.
According to the image processing method of the embodiment of the present application, by acquiring preview screen, and the dynamic of preview screen is determined
Range and the picture moving degree for acquiring picture recently relatively；According to dynamic range SdWith the picture moving degree Sm, determining to comment
It is worth Sf；Wherein, SfWith Sd(1-Sm) directly proportional；If evaluation of estimate SfLess than the first threshold, and picture moving degree SmIt is less than
Second threshold, it is determined that multiframe original image is acquired using the under exposed mode of multiframe；It synthesizes to obtain according to multiframe original image
High dynamic range images；According to ambient brightness, matched noise reduction model is determined；High dynamic range images are dropped using noise reduction model
It makes an uproar, to obtain target night scene image.Dynamic range and picture moving degree of this method based on preview screen, determine most preferably to expose
Light mode, and define and carry out noise reduction after image co-registration under the under-exposure mode of multiframe, make syncretizing effect more naturally, reducing figure
The discontinuous noise of picture while ensure that image high dynamic and clarity, reduces extra image processing time.
Corresponding with the image processing method that above-mentioned several embodiments provide, a kind of embodiment of the application also provides one kind
Image processing apparatus, due to the image procossing of image processing apparatus provided by the embodiments of the present application and above-mentioned several embodiment offers
Method is corresponding, therefore is also applied for image procossing dress provided in this embodiment in the embodiment of aforementioned image processing method
It sets, is not described in detail in the present embodiment.Fig. 4 is a kind of structural representation of image processing apparatus provided by the embodiments of the present application
Figure.As shown in figure 4, the image procossing 400 includes: preview screen acquisition module 410, the first determining module 420, second determines mould
Block 430, original image acquisition module 440, image synthesis module 450, noise reduction model determining module 460, noise reduction module 470.
Specifically, preview screen acquisition module 410, for acquiring preview screen.
First determining module 420, for determining the dynamic range and the picture shifting of acquisition picture recently relatively of preview screen
Traverse degree.
Second determining module 430, for according to dynamic range SdWith picture moving degree Sm, determine evaluation of estimate Sf；Wherein,
SfWith Sd(1-Sm) directly proportional.
Original image acquisition module 440, in evaluation of estimate SfLess than the first threshold, and picture moving degree SmIt is small
In second threshold, it is determined that acquire multiframe original image using the under exposed mode of multiframe.
Image synthesis module 450, for synthesizing to obtain high dynamic range images according to multiframe original image.Show as one kind
Example, image synthesis module 450 is specifically used for multiframe original image inputting high dynamic synthetic model, to obtain corresponding original image
In each region synthetic weight；According to synthetic weight, subregion synthesizes multiframe original image, to obtain high dynamic range
Image.Wherein, high dynamic synthetic model has learnt to obtain the mapping in original image between the feature and synthetic weight in each region
Relationship；The feature is used to characterize the brightness of image of light exposure and corresponding region.
Noise reduction model determining module 460, for determining matched noise reduction model according to ambient brightness.
As an example, noise reduction model determining module 450 is specifically used for: determining exposure corresponding to each frame original image
Value；According to exposure value corresponding to each frame original image, multiple noise reduction models corresponding to multiframe original image are determined.
Wherein, in one embodiment of the application, noise reduction model is trained in advance in the following way: obtaining training
Sample set, wherein it includes the sample graph shot under each ambient brightness that training sample, which is concentrated,；It concentrates, chooses identical from training sample
The target sample figure shot under ambient brightness；The sensitivity used when by target sample figure according to shooting is divided into multiple groups, training
The corresponding noise reduction model of each group, wherein noise reduction model has learnt to obtain between the sensitivity and noise characteristic of target sample figure
Mapping relations；According to the sensitivity for the target sample figure that the accuracy of noise reduction model and training use, from the corresponding noise reduction of each group
In model, the determining noise reduction model with respective environment brightness matching.
In embodiments herein, according to the photosensitive of the target sample figure of the accuracy of noise reduction model and training use
Degree, from the corresponding noise reduction model of each group, the determining specific implementation process with the noise reduction model of respective environment brightness matching can be such as
Under: from the corresponding noise reduction model of each group, determine that accuracy is greater than the candidate noise reduction model of threshold value；The target sample that training is used
The maximum candidate noise reduction model of the sensitivity of this figure is as the noise reduction model with respective environment brightness matching.
Noise reduction module 470, for using noise reduction model to high dynamic range images noise reduction, to obtain target night scene image.
In one embodiment of the application, which may also include that exposure compensation mode determining module, base
Quasi- exposure time determining module and compensation exposure time determining module.Wherein, exposure compensation mode determining module is used in determination
After acquiring multiframe original image using the under-exposure mode of multiframe, corresponding exposure compensating mould is determined according to the under-exposure mode of multiframe
Formula；Wherein, exposure compensation mode is used to indicate the frame number and the corresponding exposure compensating grade of each frame original image of original image.
Benchmark exposure time determining module is used to determine that benchmark exposes according to the luminance information of photographed scene and the benchmark sensitivity of setting
Duration.It compensates exposure time determining module to be used to compensate benchmark exposure time according to the exposure compensation mode, determine
The corresponding compensation exposure time of each frame original image.
In embodiments herein, original image acquisition module 440 is specifically used for: former according to benchmark sensitivity and each frame
The corresponding compensation exposure time of beginning image carries out Image Acquisition.
In embodiments herein, benchmark exposure time determining module is also used in the luminance information according to photographed scene
With the benchmark sensitivity of setting, before determining benchmark exposure time, according to picture moving degree Sm, determine benchmark sensitivity.
According to the image processing apparatus of the embodiment of the present application, by acquiring preview screen, and the dynamic of preview screen is determined
Range and the picture moving degree for acquiring picture recently relatively；According to dynamic range SdWith picture moving degree Sm, determine evaluation of estimate
Sf；Wherein, SfWith Sd(1-Sm) directly proportional；If evaluation of estimate SfLess than first threshold, and picture moving degree SmLess than second threshold,
It then determines and multiframe original image is acquired using the under exposed mode of multiframe；It synthesizes to obtain high dynamic range according to multiframe original image
Image；According to ambient brightness, matched noise reduction model is determined；Using noise reduction model to high dynamic range images noise reduction, to obtain
Target night scene image.The device can realize dynamic range and picture moving degree based on preview screen, determine optimum exposure
Mode, and define and carry out noise reduction after image co-registration under the under-exposure mode of multiframe, make syncretizing effect more naturally, reducing image
Discontinuous noise, while ensure that image high dynamic and clarity, reduce extra image processing time.
In order to realize above-described embodiment, the embodiment of the present application also proposes a kind of electronic equipment 500, referring to Fig. 5, comprising: figure
As sensor 510, processor 520, memory 530 and it is stored in the calculating that can be run on memory 530 and on processor 520
Machine program, described image sensor 510 are electrically connected with the processor 520, real when the processor 520 executes described program
Now such as above-mentioned image processing method as described in the examples.
As a kind of possible situation, processor 520 may include: image signal process (Image Signal
Processor, abbreviation ISP) processor, graphics processor (the Graphics Processing that is connect with ISP processor
Unit, abbreviation GPU).
It as an example, is the embodiment of the present application in Fig. 6 referring to Fig. 6, on the basis of the electronic equipment described in Fig. 6
The principle exemplary diagram of a kind of electronic equipment of offer.The memory 530 of electronic equipment 500 includes nonvolatile memory 60, interior
Memory 62 and processor 520.Computer-readable instruction is stored in memory 530.Computer-readable instruction, which is stored by, to be held
When row, so that processor 530 executes the image processing method of any of the above-described embodiment.
As shown in fig. 6, the electronic equipment 500 includes the processor 520 connected by system bus 61, non-volatile memories
Device 60, built-in storage 62, display screen 63 and input unit 64.Wherein, the nonvolatile memory 60 of electronic equipment 500 is stored with
Operating system and computer-readable instruction.The computer-readable instruction can be executed by processor 520, to realize the application embodiment party
The image processing method of formula.The processor 520 supports the operation of entire electronic equipment 500 for providing calculating and control ability.
The built-in storage 62 of electronic equipment 500 provides environment for the operation of the computer-readable instruction in nonvolatile memory 60.Electricity
The display screen 83 of sub- equipment 500 can be liquid crystal display or electric ink display screen etc., and input unit 64 can be display
The touch layer that covers on screen 63, is also possible to key, trace ball or the Trackpad being arranged on 500 shell of electronic equipment, can also be with
It is external keyboard, Trackpad or mouse etc..The electronic equipment 500 can be mobile phone, tablet computer, laptop, individual
Digital assistants or wearable device (such as Intelligent bracelet, smartwatch, intelligent helmet, intelligent glasses) etc..Those skilled in the art
Member is it is appreciated that structure shown in Fig. 6, and only the schematic diagram of part-structure relevant to application scheme, is not constituted
Restriction to the electronic equipment 500 that application scheme is applied thereon, specific electronic equipment 500 may include than institute in figure
Show more or fewer components, perhaps combines certain components or with different component layouts.
In order to realize above-described embodiment, the application also proposes a kind of image processing circuit, referring to Fig. 7, Fig. 7 is the application
The schematic illustration for a kind of image processing circuit that embodiment provides, as shown in fig. 7, image processing circuit 70 includes picture signal
Handle ISP processor 71 (ISP processor 71 is used as processor 520) and graphics processor GPU.
The image data that camera 73 captures is handled by ISP processor 71 first, and ISP processor 71 carries out image data
It analyzes to capture the image statistics for the one or more control parameters that can be used for determining camera 73.Camera module 710 can
Including one or more lens 732 and imaging sensor 734.Imaging sensor 734 may include colour filter array (such as Bayer
Filter), imaging sensor 734 can obtain the luminous intensity and wavelength information that each imaging pixel captures, and provide and can be handled by ISP
One group of raw image data of the processing of device 71.Sensor 74 (such as gyroscope) can be based on 74 interface type of sensor the figure of acquisition
As the parameter (such as stabilization parameter) of processing is supplied to ISP processor 71.74 interface of sensor can be SMIA (Standard
Mobile Imaging Architecture, Standard Mobile Imager framework) interface, other serial or parallel camera interfaces or
The combination of above-mentioned interface.
In addition, raw image data can also be sent to sensor 74 by imaging sensor 734, sensor 94 can be based on sensing
Raw image data is supplied to ISP processor 71 or sensor 74 and arrives raw image data storage by 74 interface type of device
In video memory 75.
ISP processor 71 handles raw image data pixel by pixel in various formats.For example, each image pixel can have
There is the bit depth of 8,10,12 or 14 bits, ISP processor 71 can carry out one or more image procossing behaviour to raw image data
Make, statistical information of the collection about image data.Wherein, image processing operations can by identical or different bit depth precision into
Row.
ISP processor 71 can also receive image data from video memory 75.For example, 74 interface of sensor is by original image
Data are sent to video memory 75, and the raw image data in video memory 75 is available to ISP processor 71 for place
Reason.Video memory 75 can be independent in memory 530, a part of memory 530, storage equipment or electronic equipment
Private memory, and may include DMA (Direct Memory Access, direct direct memory access (DMA)) feature.
When receiving the original from 734 interface of imaging sensor or from 74 interface of sensor or from video memory 75
When beginning image data, ISP processor 71 can carry out one or more image processing operations, such as time-domain filtering.Treated image
Data can be transmitted to video memory 75, to carry out other processing before shown.ISP processor 71 is stored from image
Device 75 receives processing data, and carries out at the image data in original domain and in RGB and YCbCr color space to processing data
Reason.Treated that image data may be output to display 77 (display 77 may include display screen 63) for ISP processor 71, for
Family is watched and/or is further processed by graphics engine or GPU.It is stored in addition, the output of ISP processor 71 also can be transmitted to image
Device 75, and display 77 can read image data from video memory 75.In one embodiment, video memory 75 can be matched
It is set to the one or more frame buffers of realization.In addition, the output of ISP processor 71 can be transmitted to encoder/decoder 76, so as to
Encoding/decoding image data.The image data of coding can be saved, and decompress before being shown in 77 equipment of display.
Encoder/decoder 76 can be realized by CPU or GPU or coprocessor.
The statistical data that ISP processor 71 determines, which can be transmitted, gives control logic device Unit 72.For example, statistical data may include
The imaging sensors such as automatic exposure, automatic white balance, automatic focusing, flicker detection, black level compensation, 732 shadow correction of lens
734 statistical informations.Control logic device 72 may include the processing element and/or microcontroller for executing one or more routines (such as firmware)
Device, one or more routines can statistical data based on the received, determine the control parameter of camera 73 and the control of ISP processor 71
Parameter processed.For example, the control parameter of camera 73 may include 74 control parameter of sensor (such as the integral of gain, spectrum assignment
Time, stabilization parameter etc.), camera flash control parameter, 732 control parameter of lens (such as focus or zoom focal length) or
The combination of these parameters.ISP control parameter may include for automatic white balance and color adjustment (for example, during RGB processing)
732 shadow correction parameter of gain level and color correction matrix and lens.
In order to realize above-described embodiment, the application also proposes a kind of computer readable storage medium, is stored thereon with calculating
Machine program realizes such as above-mentioned image processing method as described in the examples when the program is executed by processor.
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, can integrate in a processing module in each functional unit in each embodiment of the application
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized and when sold or used as an independent product in the form of software function module, also can store in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..Although having been shown and retouching above
Embodiments herein is stated, it is to be understood that above-described embodiment is exemplary, and should not be understood as the limit to the application
System, those skilled in the art can be changed above-described embodiment, modify, replace and become within the scope of application
Type.
Claims (11)
1. a kind of image processing method, which is characterized in that the described method comprises the following steps:
Preview screen is acquired, and determines the dynamic range of the preview screen and acquires the picture moving journey of picture recently relatively
Degree；
According to the dynamic range SdWith the picture moving degree Sm, determine evaluation of estimate Sf；Wherein, SfWith Sd(1-Sm) at just
Than；
If institute evaluation values SfLess than the first threshold, and the picture moving degree SmLess than second threshold, it is determined that use
The under exposed mode of multiframe acquires multiframe original image；
It synthesizes to obtain high dynamic range images according to the multiframe original image；
According to ambient brightness, matched noise reduction model is determined；
Using the noise reduction model to the high dynamic range images noise reduction, to obtain target night scene image.
2. image processing method according to claim 1, which is characterized in that described determining using the under exposed mode of multiframe
After acquisition multiframe original image, further includes:
Corresponding exposure compensation mode is determined according to the under exposed mode of the multiframe；Wherein, the exposure compensation mode, is used for
Indicate the frame number and the corresponding exposure compensating grade of each frame original image of original image；
According to the benchmark sensitivity of the luminance information of photographed scene and setting, benchmark exposure time is determined；
According to the exposure compensation mode, the benchmark exposure time is compensated, determines the corresponding benefit of each frame original image
Repay exposure time.
3. image processing method according to claim 2, which is characterized in that the acquisition multiframe original image, comprising:
Image Acquisition is carried out according to the benchmark sensitivity and the corresponding compensation exposure time of each frame original image.
4. image processing method according to claim 2, which is characterized in that the luminance information according to photographed scene and
The benchmark sensitivity of setting, before determining benchmark exposure time, further includes:
According to the picture moving degree Sm, determine the benchmark sensitivity.
5. image processing method according to claim 1, which is characterized in that described to be synthesized according to the multiframe original image
Obtain high dynamic range images, comprising:
The multiframe original image is inputted into high dynamic synthetic model, to obtain the synthesis power in each region in corresponding original image
Weight；
According to the synthetic weight, subregion synthesizes the multiframe original image, to obtain the high dynamic range figure
Picture.
6. image processing method according to claim 5, which is characterized in that the high dynamic synthetic model has learnt
Mapping relations into original image between the feature and synthetic weight in each region；The feature is for characterizing light exposure and corresponding
The brightness of image in region.
7. image processing method according to claim 1, which is characterized in that the noise reduction model is pre- in the following way
First training:
Obtain training sample set, wherein it includes the sample graph shot under each ambient brightness that the training sample, which is concentrated,；
It is concentrated from the training sample, chooses the target sample figure shot under identical ambient brightness；
The sensitivity used when by the target sample figure according to shooting is divided into multiple groups, trains the corresponding noise reduction model of each group,
Wherein, the noise reduction model has learnt to obtain the mapping relations between the sensitivity and noise characteristic of target sample figure；
According to the sensitivity for the target sample figure that the accuracy of noise reduction model and training use, from the corresponding noise reduction model of each group
In, the determining noise reduction model with respective environment brightness matching.
8. image processing method according to claim 7, which is characterized in that the accuracy and instruction according to noise reduction model
The sensitivity for practicing the target sample figure used, from the corresponding noise reduction model of each group, the determining drop with respective environment brightness matching
It makes an uproar model, comprising:
From the corresponding noise reduction model of each group, determine that accuracy is greater than the candidate noise reduction model of threshold value；
The maximum candidate noise reduction model of the sensitivity for the target sample figure that training is used is as described and respective environment brightness
The noise reduction model matched.
9. a kind of image processing apparatus, which is characterized in that described device includes:
Preview screen acquisition module, for acquiring preview screen；
First determining module, for determining the dynamic range of the preview screen and the picture moving journey of relatively nearest acquisition picture
Degree；
Second determining module, for according to the dynamic range SdWith the picture moving degree Sm, determine evaluation of estimate Sf；Wherein,
SfWith Sd(1-Sm) directly proportional；
Original image acquisition module, in institute evaluation values SfLess than the first threshold, and the picture moving degree SmIt is small
In second threshold, it is determined that acquire multiframe original image using the under exposed mode of multiframe；
Image synthesis module, for synthesizing to obtain high dynamic range images according to the multiframe original image；
Noise reduction model determining module, for determining matched noise reduction model according to ambient brightness；
Noise reduction module, for using the noise reduction model to the high dynamic range images noise reduction, to obtain target night scene image.
10. a kind of electronic equipment characterized by comprising imaging sensor, memory, processor and storage are on a memory
And the computer program that can be run on a processor, described image sensor are electrically connected with the processor, the processor is held
When row described program, such as image processing method described in any item of the claim 1 to 8 is realized.
11. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is by processor
Such as image processing method described in any item of the claim 1 to 8 is realized when execution.
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