CN108830805A - Image processing method, device and readable storage medium storing program for executing, electronic equipment - Google Patents
Image processing method, device and readable storage medium storing program for executing, electronic equipment Download PDFInfo
- Publication number
- CN108830805A CN108830805A CN201810517005.XA CN201810517005A CN108830805A CN 108830805 A CN108830805 A CN 108830805A CN 201810517005 A CN201810517005 A CN 201810517005A CN 108830805 A CN108830805 A CN 108830805A
- Authority
- CN
- China
- Prior art keywords
- spread function
- function information
- point
- point spread
- camera
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 21
- 239000011159 matrix material Substances 0.000 claims abstract description 50
- 238000012545 processing Methods 0.000 claims abstract description 49
- 238000000034 method Methods 0.000 claims abstract description 25
- 230000006870 function Effects 0.000 claims description 165
- 230000000007 visual effect Effects 0.000 claims description 26
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 11
- 238000004891 communication Methods 0.000 description 10
- 238000009792 diffusion process Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 7
- 230000003287 optical effect Effects 0.000 description 4
- 230000005236 sound signal Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 230000001133 acceleration Effects 0.000 description 2
- 230000000712 assembly Effects 0.000 description 2
- 238000000429 assembly Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- KLDZYURQCUYZBL-UHFFFAOYSA-N 2-[3-[(2-hydroxyphenyl)methylideneamino]propyliminomethyl]phenol Chemical compound OC1=CC=CC=C1C=NCCCN=CC1=CC=CC=C1O KLDZYURQCUYZBL-UHFFFAOYSA-N 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 201000001098 delayed sleep phase syndrome Diseases 0.000 description 1
- 208000033921 delayed sleep phase type circadian rhythm sleep disease Diseases 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G06T5/90—
-
- 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
Abstract
The disclosure is directed to a kind of image processing method, device and readable storage medium storing program for executing, electronic equipment, the method includes：Obtain the original image captured by camera；Image procossing is carried out to the original image, generates target image, wherein described image processing includes at least：Based on the corresponding point spread function information matrix of the camera, the brightness of the original image is adjusted.In the image processing process that the disclosure provides, matrix is formed by by the corresponding point spread function information of each pixel of application camera, the brightness of original image is adjusted, so as to according to the corresponding point spread function information of each pixel of camera and original image, adjustment obtains the brightness of more accurate target image, so that the brightness of target image is more nearly the brightness of object to be shot reflection light, to obtain the image being more clear.
Description
Technical field
This disclosure relates to field of image processing more particularly to a kind of image processing method, device and readable storage medium storing program for executing, electricity
Sub- equipment.
Background technique
At present the electronic equipments such as mobile phone usually all can have camera function, shooting image clarity by camera lens property
It can be codetermined with components such as imaging sensors, meanwhile, improve the striving direction that image definition is also industry.
In the related technology, image definition there are mainly two types of the mode of electronic equipment shooting is improved：
One, lens design is promoted to promote the parsing power of camera lens, to improve the clarity of shooting picture.Due to pixel ruler
Very little is smaller and smaller, and the parsing power bottleneck of final camera is actually increasingly determined by lens quality.However in lens module
In the case that size dimension determines, lens design can also reach a limit eventually, especially for small pixel size, high-resolution
For the camera of rate.
Two, it is sharpened by software to promote the parsing power of camera, to improve the clarity of shooting picture.Software sharpens
It is the profile by compensating image, enhances the edge of image and the part of Gray Level Jump, become more fully apparent image.However it is soft
The method that part sharpens is easy to obscure the marginal information and noise signal of image when judging image edge information, so that noise quilt
Amplification, influences imaging effect.
Summary of the invention
To overcome the problems in correlation technique, the disclosure provides a kind of image processing method, device and readable storage
Medium, electronic equipment.
According to the first aspect of the embodiments of the present disclosure, a kind of image processing method is provided, including：Acquisition is captured by camera
Original image；Image procossing is carried out to the original image, generates target image, wherein described image processing includes at least：
Based on the corresponding point spread function information matrix of the camera, the brightness of the original image is adjusted, the point expands
Dissipating function information matrix is to be formed by matrix by the corresponding point spread function information of each pixel of the camera.
Optionally, it is described obtain captured by camera original image the step of before, the method also includes：It obtains
The point spread function information of pre-stored basic pixel point, wherein the basic pixel point includes the multiple of the camera
Pixel corresponding to the predefined visual field of each of predefined visual field；Believed according to the point spread function of the basic pixel point
Breath, determines the point spread function information of the residual pixel point of the camera；According to the point spread function of the basic pixel point
The point spread function information of information and residual pixel point obtains the point spread function information matrix.
Optionally, the point spread function information of the basic pixel point is stored in advance in the following manner：It obtains respectively
The line spread function information of each basic pixel point in the first direction and a second direction, wherein the first direction and
The second direction is orthogonal；For each basic pixel point, the line of the basic pixel point in said first direction is expanded
Dissipate function information and in this second direction line spread function information progress multiplying, obtain the point of the basic pixel point
Spread function information；Store the point spread function information of each basic pixel point.
Optionally, the point spread function information according to the basic pixel point, determines the remaining picture of the camera
The point spread function information of vegetarian refreshments, including：According to the point spread function information of the basic pixel point, calculated by bilinear interpolation
Method determines the point spread function information of the residual pixel point.
Optionally, described to be based on the corresponding point spread function information matrix of the camera, to the bright of the original image
Degree is adjusted, including：In the channel Y in the domain YUV, the brightness of the original image is carried out with the point spread function information
Matrix is the inverse convolutional calculation of convolution kernel.
According to the second aspect of an embodiment of the present disclosure, a kind of image processing apparatus is provided, including：First obtains module, quilt
It is configured to obtain the original image captured by camera；Processing module is configured as carrying out image procossing to the original image,
Generate target image, wherein described image processing includes at least：Based on the corresponding point spread function information square of the camera
Battle array, is adjusted the brightness of the original image, the point spread function information matrix is each picture by the camera
The corresponding point spread function information of vegetarian refreshments is formed by matrix.
Optionally, described device further includes：Second obtains module, is configured as obtaining pre-stored basic pixel point
Point spread function information, wherein the basic pixel point includes that each of multiple predefined visual fields of the camera are predetermined
Pixel corresponding to adopted visual field；First determining module is configured as the point spread function information according to the basic pixel point,
Determine the point spread function information of the residual pixel point of the camera；Second determining module is configured as according to the basis
The point spread function information of pixel and the point spread function information of residual pixel point, obtain the point spread function information
Matrix.
Optionally, the point spread function information of the basic pixel point is stored in advance in the following manner：It obtains respectively
The line spread function information of each basic pixel point in the first direction and a second direction, wherein the first direction and
The second direction is orthogonal；For each basic pixel point, the line of the basic pixel point in said first direction is expanded
Dissipate function information and in this second direction line spread function information progress multiplying, obtain the point of the basic pixel point
Spread function information；Store the point spread function information of each basic pixel point.
Optionally, first determining module is configured as：According to the point spread function information of the basic pixel point, lead to
Cross the point spread function information that bilinear interpolation algorithm determines the residual pixel point.
Optionally, the processing module is configured as：In the channel Y in the domain YUV, the brightness of the original image is carried out
Using the point spread function information matrix as the inverse convolutional calculation of convolution kernel.
According to the third aspect of an embodiment of the present disclosure, a kind of image processing apparatus is provided, including：Processor；For storing
The memory of processor-executable instruction；Wherein, the processor is configured to：Obtain the original image captured by camera；
Image procossing is carried out to the original image, generates target image, wherein described image processing includes at least：It is taken the photograph based on described
As corresponding point spread function information matrix, the brightness of the original image is adjusted, the point spread function information
Matrix is to be formed by matrix by the corresponding point spread function information of each pixel of the camera.
According to a fourth aspect of embodiments of the present disclosure, a kind of electronic equipment is provided, including：Camera；At above-mentioned image
Manage device.
According to a fifth aspect of the embodiments of the present disclosure, a kind of computer readable storage medium is provided, calculating is stored thereon with
Machine program instruction realizes the step of image processing method provided by the disclosure first aspect when program instruction is executed by processor
Suddenly.
The technical scheme provided by this disclosed embodiment can include the following benefits：
In the image processing process that the disclosure provides, pass through the corresponding point spread function of each pixel of application camera
Number information is formed by matrix, is adjusted to the brightness of original image, so as to corresponding according to each pixel of camera
Point spread function information and original image, adjustment obtain the brightness of more accurate target image so that target image is bright
Degree is more nearly the brightness of object to be shot reflection light, to obtain the image being more clear.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.
Fig. 1 is the flow chart of image processing method shown according to an exemplary embodiment；
Fig. 2 is the pixel schematic diagram for a spot lamp-house in subject in original image；
Fig. 3 is the schematic diagram of the corresponding basic pixel point of predefined visual field in camera；
Fig. 4 A and Fig. 4 B are the image processing method image comparison schematic diagram before and after the processing provided using the disclosure respectively；
Fig. 5 is the flow chart of the image processing method shown according to another exemplary embodiment；
Fig. 6 is the point spread function of basic pixel point in the image processing method shown according to another exemplary embodiment
A kind of flow chart for implementation that information is stored in advance；
Fig. 7 is the block diagram of image processing apparatus shown according to an exemplary embodiment；
Fig. 8 is the block diagram of the image processing apparatus shown according to another exemplary embodiment；
Fig. 9 is the block diagram of image processing apparatus shown according to an exemplary embodiment；
Figure 10 is the block diagram of the image processing apparatus shown according to another exemplary embodiment.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
Fig. 1 is a kind of flow chart of image processing method shown according to an exemplary embodiment, as shown in Figure 1, the party
Method includes the following steps.
In S11, the original image captured by camera is obtained.
In S12, image procossing is carried out to the original image, generates target image, wherein described image processing is at least
Including：Based on the corresponding point spread function information matrix of the camera, the brightness of the original image is adjusted, it is described
Point spread function information matrix is to be formed by matrix by the corresponding point spread function information of each pixel of the camera.
It should be noted that image processing process is other than carrying out above-mentioned brightness adjustment to original image, it further include it
His image processing step, to finally obtain target image.Wherein, to other image processing steps and the relevant technologies of original image
In it is consistent, the disclosure repeats no more.
By taking digital camera as an example, image-forming principle is：Light enters camera, image-forming component CCD (Charge- from camera lens
Coupled Device, charge coupled cell) colour filter, photosensitive (photoelectric conversion) are carried out, it will be shot according to certain arrangement mode
At pixel one by one, these pixels are turned in the form of analog picture signal by A/D the image " decomposition " of object
Electric signal in each pixel is converted into digital signal and generates original image, and sent it on image processor by parallel operation,
It is processed into target image through image processor, later by target image compression storage into storage medium.
Wherein, as shown in Fig. 2, being the signal of pixel of the spot lamp-house in original image in subject
Figure.It, should when point spread function information can indicate that a point light source passes through camera imaging in original image in subject
The diffusion of pixel.The brightness of pixel is spread from the center of the pixel to surrounding, clear so as to cause the pixel
Degree reduces.
In addition, as shown in figure 3, the point diffusion of each pixel of camera and its away from camera central pixel point it
Between distance dependent, the distance between the pixel and camera central pixel point are bigger, and the point diffusion of the pixel is got over
By force, clarity is lower.The brightness value of each pixel in original image captured by camera is the anti-of subject
The brightness value that light is mapped in after the diffusion in original image on corresponding pixel is penetrated, therefore to the clarity of target image
There is larger impact.
As a result, in the image processing process that the disclosure provides, pass through the corresponding point of each pixel of application camera
Spread function information is formed by matrix, is adjusted to the brightness of original image, so as to according to each pixel of camera
The corresponding point spread function information of point and original image, adjustment obtains the brightness of more accurate target image, so that target figure
The brightness of picture is more nearly the brightness of object to be shot reflection light, to obtain the image being more clear.Such as Fig. 4 A and Fig. 4 B
It is shown, wherein image shown in Fig. 4 A is the image shot by the prior art, and image shown in Fig. 4 B is the image using the disclosure
The image of processing method shooting, it is apparent that more clear using the image that the image processing method that the disclosure provides is shot
It is clear.
Fig. 5 is a kind of flow chart of the image processing method shown according to another exemplary embodiment.As shown in figure 5,
On the basis of Fig. 1, before the step 11 of the original image for obtaining and being captured by camera, this method can also include：
In S51, the point spread function information of pre-stored basic pixel point is obtained, wherein the basic pixel point
Pixel corresponding to the predefined visual field of each of multiple predefined visual fields including the camera.
Illustratively, as shown in figure 3, the visual field of camera is divided into 0 visual field (corresponding basic pixel point is), 0.4 at 0 point
Visual field (corresponding basic pixel point is 4A point, 4B point, 4C point and 4D point), 0.6 visual field (corresponding basic pixel point be 6A point,
6B point, 6C point and 6D point) and 0.8 visual field (corresponding basic pixel point is 8A point, 8B point, 8C point and 8D point).Wherein, 0 visual field
Corresponding basic pixel point is the central pixel point of camera, remaining each visual field has respectively corresponded 4 basic pixel points, this 4
A basic pixel point being equidistant to camera central pixel point, and the length and width of the rectangle formed with 4 basic pixel points
Ratio is 4:3.In addition, the corresponding pixel of 1 visual field is four vertex pixels of the camera.0.4 visual field, 0.6 visual field and
The central point of 0.8 visual field and 1 visual field coincides with central pixel point, and between corresponding basic pixel point and central pixel point
Distance ratio be 2:3:4:5.
In S52, according to the point spread function information of basic pixel point, the point diffusion of the residual pixel point of camera is determined
Function information.
Optionally, according to the point spread function information of the basic pixel point, by described in bilinear interpolation algorithm determination
The point spread function information of residual pixel point.
Illustratively, as shown in figure 3, to calculate the point spread function information of pixel M, then can based on pixel 8A, as
The point spread function information of vegetarian refreshments 8D, pixel 6A and pixel 6D, are calculated by bilinear interpolation algorithm.Wherein, double
Linear interpolation algorithm is known algorithm, and details are not described herein.
In addition, it is necessary to which explanation is：
1) the point diffusion information of residual pixel point is the basis based on the minimum quadrangle vertex position comprising the pixel
What the point spread function information of pixel was calculated.Such as the pixel in Fig. 3 in dotted line frame region S, in 1. region
The point spread function information of pixel is the point spread function based on pixel 8A, pixel 8D, pixel 6A and pixel 6D
Information is calculated by bilinear interpolation algorithm；The point spread function information of pixel in 2. region is based on pixel
The point spread function information of 8C, pixel 8D, pixel 6C and pixel 6D, are calculated by bilinear interpolation algorithm.Other phases
Identical like region calculation, details are not described herein.
2) if the point spread function information of the pixel in Fig. 3 in dotted line frame region T is based on pixel 4A, pixel
The point spread function information of 4B, pixel 4C and pixel 4D, are calculated by bilinear interpolation algorithm.
In S53, according to the point spread function information of the point spread function information of basic pixel point and residual pixel point, obtain
Point spread function information matrix out.
According to the point spread function information of the point spread function information of basic pixel point and residual pixel point, the camera shooting is obtained
The point spread function information of each pixel is based on each location of pixels relationship, obtains the corresponding point spread function of the camera
Number information matrix.For example, using the point spread function information of the pixel of the i-th row jth column in camera as point spread function
Information matrix AijIn aijValue, wherein i ∈ [0, N], j ∈ [0, M], N+1 be camera pixel total line number, M+
1 is total columns of the pixel of camera.
In the above-mentioned technical solutions, according to the point spread function information of the basic pixel point of camera storage, camera shooting is determined
The point spread function information of head residual pixel point, so that it is determined that the corresponding point spread function information matrix of the camera.Due to taking the photograph
As head dummy number and the difference of performance, corresponding point spread function information matrix may be different, even the camera shooting of same model
Head, corresponding point spread function information matrix may also be different.Therefore, through the above technical solutions, to basic pixel
The point spread function information of point is fitted to simulate the point spread function information of entire picture other parts, it is ensured that different
The correction intensity of visual field is different, and changes with the performance change of camera.Meanwhile it can determine that each camera is corresponding
Point spread function information matrix guarantees the accuracy of the point spread function information matrix, to be subsequent image processing process
Accurate data are provided to support.
It, can MTF (Modulation Transfer to camera in the test process before camera factory
Function, modulation transfer function) value tested.Line spread function information can be calculated during testing mtf value.Cause
This, can use the line spread function information calculated during this and determine the corresponding point spread function information of basic pixel point.
Optionally, the point spread function information of basic pixel point is stored in advance in the following manner, flow chart such as Fig. 6
It is shown, including：
In S61, the line spread function information of each basic pixel point in the first direction and a second direction is obtained respectively,
Wherein, the first direction and the second direction are orthogonal.
In s 62, for each basic pixel point, to the line spread function information of basic pixel point in a first direction
Line spread function information in a second direction carries out multiplying, obtains the point spread function information of the basic pixel point.
Illustratively, as shown in figure 3, for pixel 6B, during the test, line L1 can be calculated and line L2 is corresponding
Line spread function information.Based on the corresponding line spread function information of line L1 and line L2, multiplying is carried out, it can be deduced that line L1
The point spread function information of pixel 6B corresponding with line L2 orthogonal crossover point.The point spread function information of other basic pixel points
Calculation be identical with this, repeat no more.
In S63, the point spread function information of each basic pixel point is stored.
In the above-mentioned technical solutions, when making full use of camera factory test, for the line of each camera itself calculating
Spread function information, so that it is determined that the point spread function information of each basic pixel point out, and stored.By above-mentioned
Technical solution, can be during image procossing, it is ensured that each camera can be based on itself point spread function information
The brightness of original image is adjusted, to obtain the brightness of more accurate target image, so as to effectively improve target
The clarity of image.
Optionally, described to be based on the corresponding point spread function information matrix of the camera, to the bright of the original image
Degree is adjusted, including：In the channel Y in the domain YUV, the brightness of the original image is carried out with the point spread function information
Matrix is the inverse convolutional calculation of convolution kernel.
Illustratively, the calculating of inverse convolution can be carried out by following formula：
F (x, y)=fft-1[G (u, v)/H (u, v)]=fft-1[fft[g(u,v)]/fft[h(u,v)]]
Wherein, f (x, y) indicates image adjusted；
fft-1[] indicates inverse Fourier transform；
Fft [] is Fourier transformation；
G (u, v) indicates original image in the spatial domain, i.e., original image described above；
H (u, v) indicates convolution kernel in the spatial domain, i.e., convolution kernel described above；
G (u, v) is the expression being transformed into the original image in frequency domain；
H (u, v) is the expression being transformed into the convolution kernel in frequency domain.
Since the light that the brightness value of pixel each in original image is subject reflection is mapped to corresponding picture
Brightness value after vegetarian refreshments diffusion, therefore, the brightness progress to the original image is with the point spread function information matrix
The inverse convolutional calculation of convolution kernel can effectively adjust the brightness value of each pixel in original image, to obtain clearly mesh
Logo image.In addition, the adjustment process can also continue on the basis of having focused clearly, target figure is further promoted
The clarity of picture.
Fig. 7 is the block diagram of image processing apparatus shown according to an exemplary embodiment.As shown in fig. 7, the device 10 wraps
It includes：
First obtains module 100, is configured as obtaining the original image captured by camera；
Processing module 200 is configured as carrying out image procossing to the original image, generates target image, wherein described
Image procossing includes at least：Brightness based on the corresponding point spread function information matrix of the camera, to the original image
It is adjusted, the point spread function information matrix is the corresponding point spread function information of each pixel by the camera
It is formed by matrix.
Fig. 8 is the block diagram of the image processing apparatus shown according to another exemplary embodiment.As shown in figure 8, in the base of Fig. 7
On plinth, which can also include：
Second obtains module 300, is configured as obtaining the point spread function information of pre-stored basic pixel point,
In, the basic pixel point includes pixel corresponding to the predefined visual field of each of multiple predefined visual fields of the camera
Point；
First determining module 400 is configured as the point spread function information according to the basic pixel point, takes the photograph described in determination
As the point spread function information of the residual pixel point of head；
Second determining module 500 is configured as point spread function information and the residue according to the basic pixel point
The point spread function information of pixel obtains the point spread function information matrix.
Optionally, the point spread function information of basic pixel point is stored in advance in the following manner：
The line spread function information of each basic pixel point in the first direction and a second direction is obtained respectively,
In, the first direction and the second direction are orthogonal；
For each basic pixel point, to the line spread function information of basic pixel point in said first direction
Line spread function information in this second direction carries out orthogonal operations, obtains the point spread function letter of the basic pixel point
Breath；
Store the point spread function information of each basic pixel point.
Optionally, the first determining module 400 is configured as：
According to the point spread function information of the basic pixel point, the residual pixel is determined by bilinear interpolation algorithm
The point spread function information of point.
Optionally, processing module 200 is configured as：
In the channel Y in the domain YUV, the brightness of the original image is carried out with the point spread function information matrix being volume
The inverse convolutional calculation of product core.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
The disclosure also provides a kind of computer readable storage medium, is stored thereon with computer program instructions, which refers to
The step of enabling the image processing method that disclosure offer is provided when being executed by processor.
Fig. 9 is the block diagram of image processing apparatus 900 shown according to an exemplary embodiment.For example, device 900 can be
Mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, Medical Devices, body-building are set
It is standby, personal digital assistant etc..
Referring to Fig. 9, device 900 may include following one or more components：Processing component 902, memory 904, electric power
Component 906, multimedia component 908, audio component 910, the interface 912 of input/output (I/O), sensor module 914, and
Communication component 916.
The integrated operation of the usual control device 900 of processing component 902, such as with display, telephone call, data communication, phase
Machine operation and record operate associated operation.Processing component 902 may include that one or more processors 920 refer to execute
It enables, to complete all or part of the steps of above-mentioned image processing method.In addition, processing component 902 may include one or more
Module, convenient for the interaction between processing component 902 and other assemblies.For example, processing component 902 may include multi-media module,
To facilitate the interaction between multimedia component 908 and processing component 902.
Memory 904 is configured as storing various types of data to support the operation in device 900.These data are shown
Example includes the instruction of any application or method for operating on device 900, contact data, and telephone book data disappears
Breath, picture, video etc..Memory 904 can be by any kind of volatibility or non-volatile memory device or their group
It closes and realizes, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM) is erasable to compile
Journey read-only memory (EPROM), programmable read only memory (PROM), read-only memory (ROM), magnetic memory, flash
Device, disk or CD.
Electric power assembly 906 provides electric power for the various assemblies of device 900.Electric power assembly 906 may include power management system
System, one or more power supplys and other with for device 900 generate, manage, and distribute the associated component of electric power.
Multimedia component 908 includes the screen of one output interface of offer between described device 900 and user.One
In a little embodiments, screen may include liquid crystal display (LCD) and touch panel (TP).If screen includes touch panel, screen
Curtain may be implemented as touch screen, to receive input signal from the user.Touch panel includes one or more touch sensings
Device is to sense the gesture on touch, slide, and touch panel.The touch sensor can not only sense touch or sliding action
Boundary, but also detect duration and pressure associated with the touch or slide operation.In some embodiments, more matchmakers
Body component 908 includes a front camera and/or rear camera.When device 900 is in operation mode, such as screening-mode or
When video mode, front camera and/or rear camera can receive external multi-medium data.Each front camera and
Rear camera can be a fixed optical lens system or have focusing and optical zoom capabilities.
Audio component 910 is configured as output and/or input audio signal.For example, audio component 910 includes a Mike
Wind (MIC), when device 900 is in operation mode, when such as call mode, recording mode, and voice recognition mode, microphone is matched
It is set to reception external audio signal.The received audio signal can be further stored in memory 904 or via communication set
Part 916 is sent.In some embodiments, audio component 910 further includes a loudspeaker, is used for output audio signal.
I/O interface 912 provides interface between processing component 902 and peripheral interface module, and above-mentioned peripheral interface module can
To be keyboard, click wheel, button etc..These buttons may include, but are not limited to：Home button, volume button, start button and lock
Determine button.
Sensor module 914 includes one or more sensors, and the state for providing various aspects for device 900 is commented
Estimate.For example, sensor module 914 can detecte the state that opens/closes of device 900, and the relative positioning of component, for example, it is described
Component is the display and keypad of device 900, and sensor module 914 can be with 900 1 components of detection device 900 or device
Position change, the existence or non-existence that user contacts with device 900,900 orientation of device or acceleration/deceleration and device 900
Temperature change.Sensor module 914 may include proximity sensor, be configured to detect without any physical contact
Presence of nearby objects.Sensor module 914 can also include optical sensor, such as CMOS or ccd image sensor, at
As being used in application.In some embodiments, which can also include acceleration transducer, gyro sensors
Device, Magnetic Sensor, pressure sensor or temperature sensor.
Communication component 916 is configured to facilitate the communication of wired or wireless way between device 900 and other equipment.Device
900 can access the wireless network based on communication standard, such as WiFi, 2G or 3G or their combination.In an exemplary implementation
In example, communication component 916 receives broadcast singal or broadcast related information from external broadcasting management system via broadcast channel.
In one exemplary embodiment, the communication component 916 further includes near-field communication (NFC) module, to promote short range communication.Example
Such as, NFC module can be based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra wide band (UWB) technology,
Bluetooth (BT) technology and other technologies are realized.
In the exemplary embodiment, device 900 can be believed by one or more application specific integrated circuit (ASIC), number
Number processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD), field programmable gate array
(FPGA), controller, microcontroller, microprocessor or other electronic components are realized, for executing above-mentioned image processing method.
In the exemplary embodiment, a kind of non-transitorycomputer readable storage medium including instruction, example are additionally provided
It such as include the memory 904 of instruction, above-metioned instruction can be executed by the processor 920 of device 900 to complete above-mentioned image processing method
Method.For example, the non-transitorycomputer readable storage medium can be ROM, random access memory (RAM), CD-ROM, magnetic
Band, floppy disk and optical data storage devices etc..
Figure 10 is the block diagram of the image processing apparatus 1000 shown according to another exemplary embodiment.Referring to Fig.1 0, device
1000 include processing component 1022, further comprises one or more processors, and deposit as representated by memory 1032
Memory resource, can be by the instruction of the execution of processing component 1022, such as application program for storing.It is stored in memory 1032
Application program may include it is one or more each correspond to one group of instruction module.In addition, processing component 1022
It is configured as executing instruction, to execute above-mentioned image processing method.
Device 1000 can also include that a power supply module 1026 be configured as the power management of executive device 1000, and one
Wired or wireless network interface 1050 is configured as device 1000 being connected to network and input and output (I/O) interface
1058。
The disclosure also provides a kind of electronic equipment, including：Camera；The image processing apparatus 10 that the disclosure provides, or
The image processing apparatus 1000 that the disclosure provides.
Those skilled in the art will readily occur to other embodiment party of the disclosure after considering specification and practicing the disclosure
Case.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or adaptability
Variation follows the general principles of this disclosure and including the undocumented common knowledge or usual skill in the art of the disclosure
Art means.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following claim
It points out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the accompanying claims.
Claims (13)
1. a kind of image processing method, which is characterized in that including：
Obtain the original image captured by camera；
Image procossing is carried out to the original image, generates target image, wherein described image processing includes at least：Based on institute
The corresponding point spread function information matrix of camera is stated, the brightness of the original image is adjusted, the point spread function
Information matrix is to be formed by matrix by the corresponding point spread function information of each pixel of the camera.
2. the method according to claim 1, wherein in the step of the original image for obtaining and being captured by camera
Before rapid, the method also includes：
Obtain the point spread function information of pre-stored basic pixel point, wherein the basic pixel point includes the camera shooting
Pixel corresponding to the predefined visual field of each of multiple predefined visual fields of head；
According to the point spread function information of the basic pixel point, the point spread function of the residual pixel point of the camera is determined
Information；
According to the point spread function information of the point spread function information of the basic pixel point and residual pixel point, institute is obtained
State point spread function information matrix.
3. according to the method described in claim 2, it is characterized in that, the point spread function information of basic pixel point by with
Under type is stored in advance：
The line spread function information of each basic pixel point in the first direction and a second direction is obtained respectively, wherein institute
It states first direction and the second direction is orthogonal；
For each basic pixel point, to basic pixel point line spread function information in said first direction and
Line spread function information in the second direction carries out multiplying, obtains the point spread function information of the basic pixel point；
Store the point spread function information of each basic pixel point.
4. according to the method described in claim 2, it is characterized in that, described believe according to the point spread function of the basic pixel point
Breath, determines the point spread function information of the residual pixel point of the camera, including：
According to the point spread function information of the basic pixel point, the residual pixel point is determined by bilinear interpolation algorithm
Point spread function information.
5. method according to any of claims 1-4, which is characterized in that described to be based on the corresponding point of the camera
Spread function information matrix is adjusted the brightness of the original image, including：
In the channel Y in the domain YUV, the brightness of the original image is carried out using the point spread function information matrix as convolution kernel
Inverse convolutional calculation.
6. a kind of image processing apparatus, which is characterized in that including：
First obtains module, is configured as obtaining the original image captured by camera；
Processing module is configured as carrying out image procossing to the original image, generates target image, wherein at described image
Reason includes at least：Based on the corresponding point spread function information matrix of the camera, the brightness of the original image is adjusted
Whole, the point spread function information matrix is formed by the corresponding point spread function information of each pixel of the camera
Matrix.
7. device according to claim 6, which is characterized in that described device further includes：
Second obtains module, is configured as obtaining the point spread function information of pre-stored basic pixel point, wherein the base
Plinth pixel includes pixel corresponding to the predefined visual field of each of multiple predefined visual fields of the camera；
First determining module is configured as determining the camera according to the point spread function information of the basic pixel point
The point spread function information of residual pixel point；
Second determining module is configured as according to the point spread function information of the basic pixel point and residual pixel point
Point spread function information obtains the point spread function information matrix.
8. device according to claim 7, which is characterized in that the point spread function information of the basic pixel point by with
Under type is stored in advance：
The line spread function information of each basic pixel point in the first direction and a second direction is obtained respectively, wherein institute
It states first direction and the second direction is orthogonal；
For each basic pixel point, to basic pixel point line spread function information in said first direction and
Line spread function information in the second direction carries out multiplying, obtains the point spread function information of the basic pixel point；
Store the point spread function information of each basic pixel point.
9. device according to claim 7, which is characterized in that first determining module is configured as：
According to the point spread function information of the basic pixel point, the residual pixel point is determined by bilinear interpolation algorithm
Point spread function information.
10. the device according to any one of claim 6-9, which is characterized in that the processing module is configured as：
In the channel Y in the domain YUV, the brightness of the original image is carried out using the point spread function information matrix as convolution kernel
Inverse convolutional calculation.
11. a kind of image processing apparatus, which is characterized in that including：
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to：
Obtain the original image captured by camera；
Image procossing is carried out to the original image, generates target image, wherein described image processing includes at least：Based on institute
The corresponding point spread function information matrix of camera is stated, the brightness of the original image is adjusted, the point spread function
Information matrix is to be formed by matrix by the corresponding point spread function information of each pixel of the camera.
12. a kind of electronic equipment, which is characterized in that the electronic equipment includes：
Camera；
According to image processing apparatus described in any one of claim 6-11 claim.
13. a kind of computer readable storage medium, is stored thereon with computer program instructions, which is characterized in that the program instruction
The step of any one of claim 1-5 the method is realized when being executed by processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810517005.XA CN108830805A (en) | 2018-05-25 | 2018-05-25 | Image processing method, device and readable storage medium storing program for executing, electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810517005.XA CN108830805A (en) | 2018-05-25 | 2018-05-25 | Image processing method, device and readable storage medium storing program for executing, electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108830805A true CN108830805A (en) | 2018-11-16 |
Family
ID=64146105
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810517005.XA Pending CN108830805A (en) | 2018-05-25 | 2018-05-25 | Image processing method, device and readable storage medium storing program for executing, electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108830805A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410152A (en) * | 2018-11-26 | 2019-03-01 | Oppo广东移动通信有限公司 | Imaging method and device, electronic equipment, computer readable storage medium |
| CN110475068A (en) * | 2019-08-30 | 2019-11-19 | 北京迈格威科技有限公司 | Image processing method and device |
| CN110533617A (en) * | 2019-08-30 | 2019-12-03 | Oppo广东移动通信有限公司 | Image processing method and device, storage medium |
| WO2020224423A1 (en) * | 2019-05-07 | 2020-11-12 | 京东方科技集团股份有限公司 | Terminal device and zooming processing method and apparatus for image thereof |
| CN112215777A (en) * | 2020-10-19 | 2021-01-12 | 维沃移动通信有限公司 | Calibration system, calibration method, calibration device and electronic equipment of point spread function |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101291391A (en) * | 2007-04-20 | 2008-10-22 | 致伸科技股份有限公司 | Image processing method and related partial point spreading function estimating method |
| CN101441764A (en) * | 2008-12-31 | 2009-05-27 | 中国资源卫星应用中心 | MTFC remote sensing image restoration method |
| CN106651811A (en) * | 2017-01-03 | 2017-05-10 | 长沙全度影像科技有限公司 | Brightness channel guided simple lens imaging blurring removing method |
| US20170365046A1 (en) * | 2014-08-15 | 2017-12-21 | Nikon Corporation | Algorithm and device for image processing |
| CN107734294A (en) * | 2017-09-26 | 2018-02-23 | 中国科学院长春光学精密机械与物理研究所 | Monitoring image recovery system and method |
-
2018
- 2018-05-25 CN CN201810517005.XA patent/CN108830805A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101291391A (en) * | 2007-04-20 | 2008-10-22 | 致伸科技股份有限公司 | Image processing method and related partial point spreading function estimating method |
| CN101441764A (en) * | 2008-12-31 | 2009-05-27 | 中国资源卫星应用中心 | MTFC remote sensing image restoration method |
| US20170365046A1 (en) * | 2014-08-15 | 2017-12-21 | Nikon Corporation | Algorithm and device for image processing |
| CN106651811A (en) * | 2017-01-03 | 2017-05-10 | 长沙全度影像科技有限公司 | Brightness channel guided simple lens imaging blurring removing method |
| CN107734294A (en) * | 2017-09-26 | 2018-02-23 | 中国科学院长春光学精密机械与物理研究所 | Monitoring image recovery system and method |
Non-Patent Citations (2)
| Title |
|---|
| 于殿泓: "《图像检测与处理技术》", 31 December 2006 * |
| 郝建坤: "基于计算光学的简单透镜成像技术", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109410152A (en) * | 2018-11-26 | 2019-03-01 | Oppo广东移动通信有限公司 | Imaging method and device, electronic equipment, computer readable storage medium |
| WO2020224423A1 (en) * | 2019-05-07 | 2020-11-12 | 京东方科技集团股份有限公司 | Terminal device and zooming processing method and apparatus for image thereof |
| CN110475068A (en) * | 2019-08-30 | 2019-11-19 | 北京迈格威科技有限公司 | Image processing method and device |
| CN110533617A (en) * | 2019-08-30 | 2019-12-03 | Oppo广东移动通信有限公司 | Image processing method and device, storage medium |
| CN110533617B (en) * | 2019-08-30 | 2022-05-27 | Oppo广东移动通信有限公司 | Image processing method and device, and storage medium |
| CN112215777A (en) * | 2020-10-19 | 2021-01-12 | 维沃移动通信有限公司 | Calibration system, calibration method, calibration device and electronic equipment of point spread function |
| CN112215777B (en) * | 2020-10-19 | 2023-06-16 | 维沃移动通信有限公司 | Calibration system, calibration method, calibration device and electronic equipment of point spread function |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108830805A (en) | Image processing method, device and readable storage medium storing program for executing, electronic equipment | |
| CN105528606B (en) | Area recognizing method and device | |
| US10452890B2 (en) | Fingerprint template input method, device and medium | |
| US10963982B2 (en) | Video watermark generation method and device, and terminal | |
| CN105631797B (en) | Watermark adding method and device | |
| CN106778773B (en) | Method and device for positioning target object in picture | |
| CN105302615B (en) | Method for upgrading software and device | |
| JP2017526316A (en) | Method, apparatus, program and recording medium for processing moving picture file identifier | |
| CN104238890B (en) | Character displaying method and device | |
| CN106446946B (en) | Image recognition method and device | |
| CN107995500B (en) | Video watermark recognition methods, device and terminal | |
| CN105957037B (en) | Image enchancing method and device | |
| EP2975574B1 (en) | Method, apparatus and terminal for image retargeting | |
| JP6378453B2 (en) | Feature extraction method and apparatus | |
| CN107426489A (en) | Processing method, device and terminal during shooting image | |
| US11245886B2 (en) | Method and apparatus for synthesizing omni-directional parallax view, and storage medium | |
| CN105574834B (en) | Image processing method and device | |
| CN105825490A (en) | Gaussian blur method and device of image | |
| JP2018507495A (en) | Feature extraction method and apparatus | |
| CN105678296B (en) | Method and device for determining character inclination angle | |
| CN109542285A (en) | Image processing method and device | |
| CN110363702B (en) | Image processing method and related product | |
| CN105678685B (en) | Image processing method and device | |
| CN105100622B (en) | Zoom implementation method and device, electronic equipment | |
| CN107992894B (en) | Image recognition method, image recognition device and computer-readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20181116 |