CN109658372A - A kind of image conformity appraisal procedure and device - Google Patents
A kind of image conformity appraisal procedure and device Download PDFInfo
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- CN109658372A CN109658372A CN201710933092.2A CN201710933092A CN109658372A CN 109658372 A CN109658372 A CN 109658372A CN 201710933092 A CN201710933092 A CN 201710933092A CN 109658372 A CN109658372 A CN 109658372A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10052—Images from lightfield camera
Abstract
This application involves technical field of image detection more particularly to a kind of image conformity appraisal procedure and devices.The described method includes: obtaining the ensemble average pixel value I of image0, the imaging circumstances of each pixel of described image are identical；Described image is divided into M × N number of area equation rectangular area, wherein M is the number of every row rectangular area in described image, and N is the number of each column rectangular area in described image；Calculate the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij, wherein i=1,2 ..., M；J=1,2 ..., N；According to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average pixel value I0, calculate the uniformity coefficient U of described image；The uniformity of described image is assessed according to the uniformity coefficient U.The method has fully considered the fluctuation situation of the pixel value in each region in image, is conducive to the accuracy for improving image conformity assessment.
Description
Technical field
This application involves technical field of image detection more particularly to a kind of image conformity appraisal procedure and devices.
Background technique
For electronic image during imaging, the light that imaging object issues is under the action of camera optics element, with two dimension
The form of image is presented on the imaging plane of camera, and a large amount of imaging unit is typically provided on imaging plane, the imaging unit
Two dimensional image signal can be converted into electric signal, which with after display, that is, shows electronic image by amplification.
Under normal conditions, when each imaging unit in camera imaging plane to the response of optical signal is consistent when,
For camera in identical object (such as pure white paper) of shooting optical signal, the pixel value of each pixel is phase on the image of shooting
With, which is the uniform image of pixel value, while also illustrating that the camera has preferable imaging effect.But in fact, by
In reasons such as manufacturing process, each imaging unit is inevitably had a certain difference, and causes each imaging unit to light
The response of signal is different, and the pixel value for the image that the identical object of shooting optical signal obtains is uneven.As one can imagine passing through this
The image of camera shooting is it is possible that phenomena such as image fault.At this point, it is single to calibrate imaging to generally use image rectification algorithm
The optical signal response curve of member makes it keep identical response to identical optical signal.Pass through identical optical signal subject image
Pixel value uniformity, be able to reflect the validity of correcting algorithm, calibrate each imaging unit pair will pass through correcting algorithm
The response of optical signal eliminates influence of the hardware facility to image quality.
Currently, in the uniformity of assessment electronics image pixel value, usually with the pixel of all pixels point in electronic image
The mean square deviation of the average pixel value of value and whole image measures the fluctuation situation of electronic image whole pixel value.But high picture
Plain image form is too big, and the value differences of different zones are also bigger in image, is difficult to standard using the mean square deviation of entire image
Really measure the uniformity of image.
Summary of the invention
The application provides a kind of image conformity appraisal procedure and device, is assessed with solving the prior art to image conformity
The problem of inaccuracy.
The application's in a first aspect, provide a kind of image conformity appraisal procedure, comprising:
Obtain the ensemble average pixel value I of image0, the imaging circumstances of each pixel of described image are identical；
Described image is divided into M × N number of area equation rectangular area, wherein M is every row rectangle region in described image
The number in domain, N are the number of each column rectangular area in described image；
Calculate the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij, wherein i=1,
2,......,M；J=1,2 ..., N；
According to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average pixel value I0, meter
Calculate the uniformity coefficient U of described image；
The uniformity of described image is assessed according to the uniformity coefficient U.
Optionally, described according to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average
Pixel value I0, calculate the uniformity coefficient U of described image, comprising:
According to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate on the pixel value in each region
Limit Iij+SijWith the pixel value lower limit I in each regionij-Sij；
Obtain all pixel value upper limits and greatest member max and least member min in the pixel value lower limit；
According to uniformity coefficient formulaCalculate the uniformity coefficient U.
Optionally, described according to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate each area
The pixel value upper limit I in domainij+SijWith the pixel value lower limit I in each regionij-Sij, comprising:
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel of described image
Value matrix I and area pixel value mean square deviation S, wherein
According to the mean pixel value matrix I and the mean square deviation matrix S, pixel value upper limit Matrix C and pixel value are calculated
Lower limit matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
Optionally, described to obtain all pixel value upper limits and maximum value max and minimum in the pixel value lower limit
Value min, comprising:
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E, E=[C, D]；
The greatest member max (E) in matrix E is obtained, max (E) is used as the greatest member max, is obtained in matrix E
Min (E) is used as the least member min by least member min (E).
Optionally, described according to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate each area
The pixel value upper limit I in domainij+SijWith the pixel value lower limit I in each regionij-Sij, further includes:
Judge the Iij+SijIn the numerical value of any one element whether be greater than 2bit- 1, if it is, with 2bit- 1 replacement
It is all described greater than 2bit- 1 element, wherein bit is the bit wide of described image pixel value；
Judge the Iij-SijIn any one element whether less than 0, if it is, all described less than 0 with 0 replacement
Element.
The second aspect of the embodiment of the present application provides a kind of image conformity assessment device characterized by comprising
First computing unit, for obtaining the ensemble average pixel value I of image0, each pixel of described image
Imaging circumstances are identical；
Image division unit, for described image to be divided into M × N number of area equation rectangular area, wherein M is institute
The number of every row rectangular area in image is stated, N is the number of each column rectangular area in described image；
Second computing unit calculates the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation
Sij, wherein i=1,2 ..., M；J=1,2 ..., N；
Third computing unit, according to the region average pixel value Iij, area pixel value mean square deviation SijIt is flat with the entirety
Equal pixel value I0, calculate the uniformity coefficient U of described image；
Uniformity assessment unit, for assessing the uniformity of described image according to the uniformity coefficient U.
Optionally, the third computing unit, is also used to:
According to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate on the pixel value in each region
Limit Iij+SijWith the pixel value lower limit I in each regionij-Sij；
Obtain all pixel value upper limits and greatest member max and least member min in the pixel value lower limit；
According to uniformity coefficient formulaCalculate the uniformity coefficient U.
Optionally, the third computing unit, is also used to:
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel of described image
Value matrix I area pixel value mean square deviation S, wherein
According to the mean pixel value matrix I and the mean square deviation matrix S, pixel value upper limit Matrix C and pixel value are calculated
Lower limit matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
Optionally, the third computing unit, is also used to:
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E, E=[C, D]；
The greatest member max (E) in matrix E is obtained, max (E) is used as the greatest member max, is obtained in matrix E
Min (E) is used as the least member min by least member min (E).
Optionally, the third computing unit, is also used to:
Judge the Iij+SijIn the numerical value of any one element whether be greater than 2bit- 1, if it is, with 2bit- 1 replacement
It is described to be greater than 2bit- 1 element, wherein bit is the bit wide of described image pixel value；
Judge the Iij-SijIn any one element whether less than 0, if it is, with the 0 replacement member less than 0
Element.
The technical scheme provided by the application includes following advantageous effects:
The application calculates the ensemble average pixel value I of image0, and divide an image into M × N number of area equation rectangle
Region calculates the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij；Pass through ensemble average
Pixel value I0, region average pixel value IijWith area pixel value mean square deviation SijUniformity coefficient U is calculated, uniformity coefficient is passed through
U assesses the uniformity coefficient of image.The method has fully considered the fluctuation situation of the pixel value in each region in image,
Be conducive to improve the accuracy of image conformity assessment.
Detailed description of the invention
In order to illustrate more clearly of the technical solution of the application, letter will be made to attached drawing needed in the embodiment below
Singly introduce, it should be apparent that, for those of ordinary skills, without any creative labor,
It is also possible to obtain other drawings based on these drawings.
Fig. 1 provides a kind of flow chart of image conformity appraisal procedure for the embodiment of the present application.
Fig. 2 is a kind of image-region partition structure schematic diagram of the application.
Fig. 3 is the flow chart of another image conformity appraisal procedure provided by the embodiments of the present application.
Fig. 4 is the flow chart of another image conformity appraisal procedure provided by the embodiments of the present application.
Fig. 5 is the connection block diagram that a kind of image conformity provided by the embodiments of the present application assesses device.
Specific embodiment
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the application
Example, and together with specification it is used to explain the principle of the application.
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, for those of ordinary skill in the art
Speech, without creative efforts, is also possible to obtain other drawings based on these drawings.
Embodiment 1
Referring to Figure 1, the embodiment of the present application provides a kind of flow chart of image conformity appraisal procedure, and the method passes through
101~step 105 of following steps is realized.
Step S101 obtains the ensemble average pixel value I of image0, the imaging circumstances of each pixel of described image
It is identical.
The ensemble average pixel value I of described image0For the average value of the pixel value of all pixels point in described image.According to
The ensemble average pixel value I of formula (1) calculating described image0:
Wherein, A is the number of the every a line pixel of described image, and B is the number of each column pixel of described image；P is
The abscissa of each pixel in described image, p=1,2 ... A；Q is the vertical seat of each pixel in described image
Q=1,2 is marked ... B；I (p, q) is the pixel value of each pixel of described image.
It should be noted that in this application, the imaging circumstances of each pixel are identical to be referred to, described image it is each
A pixel is all that the optical signal for acquiring same uniform object (such as pure white paper) using the image-forming component of same model is formed.
The pixel value of each point can be RGB (RedGreenBlue, RGB) value, rgb color in the present embodiment
Mode is a kind of color standard of industry, be by variation to three Color Channels of red, green, blue and they between each other
Superposition to obtain miscellaneous color.Certainly, the pixel value may be the other forms for indicating image pixel
Numerical value, the application are not limited this.
Described image is divided into M × N number of area equation rectangular area by step S102, wherein M is in described image
The number of every row rectangular area, N are the number of each column rectangular area in described image.
Refer to Fig. 2, a kind of image-region partition structure schematic diagram provided by the embodiments of the present application.In this application, M and
N is non-negative integer, and the specific value of M and N can determine as the case may be.For example, when pixel in image to be assessed
Quantity it is more when, can suitably increase the numerical value of M and N.And when the negligible amounts of pixel in image to be assessed, it can be appropriate
Reduce the numerical value of M and N.In the present embodiment, M=4, N=3.
Step S103 calculates the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij,
In, i=1,2 ..., M；J=1,2 ..., N.
The region average pixel value I of described imageijIt is averaged for the pixel value of all pixels point in each rectangular area
Value.The region average pixel value I is calculated according to formula (2)ij。
Wherein, a is the number of the every a line pixel in each rectangular area；B is each column pixel in each rectangular area
The number of point；(p, q) is the coordinate value of each pixel in image；I (p, q) is the pixel of each pixel in image
Value.
It should be noted that in the present embodiment, for the rectangular area for being located at the i-th row, jth arranges, the rectangular area
Abscissa p=a (i-1)+1, a (i-1)+2 of interior pixel (p, q) ..., ai；Pixel in the region it is vertical
Coordinate q=b (j-1)+1, b (j-1)+2 ..., bj.
Illustratively, in the present embodiment, for i=1 (the first row in described image) and j=2 (second in described image
Column) rectangular area average pixel value
The area pixel value mean square deviation S of each rectangular areaijIt is calculated by formula (3):
Wherein, a is the number of the every a line pixel in each rectangular area；B is each column pixel in each rectangular area
The number of point；(p, q) is the coordinate value of each pixel in image；I (p, q) is the pixel of each pixel in image
Value, IijFor the region average pixel value of the i-th row jth column rectangular area.
For example, the area of the rectangular area for i=1 (the first row in described image) and j=2 (secondary series in described image)
Domain pixel value mean square deviation
Step S104, according to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average picture
Plain value I0, calculate the uniformity coefficient U of described image.
In the present embodiment, Fig. 3 is referred to, step S104 is realized by step S301-S303.
Step S301, according to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate each region
Pixel value upper limit Iij+SijWith the pixel value lower limit I in each regionij-Sij。
Optionally, in the present embodiment, step S301 is realized by following mode.
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel of described image
Value matrix I and area pixel value mean square deviation matrix S.
The mean pixel value matrixWherein, Iij(i=1,2 ... M；J=1,
2 ... N) position in mean pixel value matrix I and IijThe position of corresponding pixel in the picture is identical.
The mean square deviation matrixWherein, Sij(i=1,2 ... M；J=1,
2 ... N) position in the mean square deviation matrix S and SijThe position of corresponding pixel in the picture is identical.
Step S302 obtains all pixel value upper limits and greatest member max and minimum in the pixel value lower limit
Element min.
In the present embodiment, Fig. 4 is referred to, S401-S403 is realized step S302 as follows.
Step S401 calculates pixel value upper limit Matrix C according to the mean pixel value matrix I and the mean square deviation matrix S
With pixel value lower limit matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
In formula (4), Iij+SijIndicate the pixel value upper limit in each rectangular area.In formula (4), Iij-Sij
Indicate the pixel value lower limit in each rectangular area.That is, on pixel value of the pixel value upper limit Matrix C by each region
Limit is constituted.Pixel value lower limit matrix D is made of the pixel value lower limit in each region.
Optionally, step S401 further includes following constraint condition: judging whether any one element is greater than in the Matrix C
2bit- 1, if it is, with 2bitIt is all in -1 replacement Matrix C to be greater than 2bit- 1 element, wherein bit is described image pixel value
Bit wide.For example, as the bit wide bit=8 of pixel value, 2bit- 1=28- 1=255.Any one element is in judgment matrix D
It is no less than 0, if it is, with 0 replacement matrix D in all elements less than 0.By above-mentioned constraint condition, square can be prevented
Element in battle array C and matrix D exceeds the pixel value range [0,2 of imagebit- 1], abnormal data is avoided the occurrence of.
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E by step S402, E=[C,
D]。
Step S403 obtains the greatest member max (E) in matrix E, and max (E) is used as the greatest member max, is obtained
Min (E) is used as the least member min by the least member min (E) in matrix E.
Step S303, according to uniformity coefficient formulaCalculate the uniformity coefficient U.
In the present embodiment,Wherein, max (E) is the greatest member in matrix E, min
It (E) is the least member in matrix E, I0For the ensemble average pixel value of image.Max (E)-min (E) indicates each in described image
The maximum of pixel value is averaged undulating value between a rectangular area.Indicate each rectangle region in described image
The maximum of the pixel value undulating value that is averaged accounts for the ratio of image ensemble average pixel value between domain.
For example, the pixel value of each pixel of described image is identical in the state of a kind of ideal, at this point,
The pixel value of each region of described image does not fluctuate, Sij=0, at this point, max (E)=Iij=I0, min (E)=Iij=I0,
So uniformity coefficientIndicate image substantially uniformity.
Step S105 assesses the uniformity of described image according to the uniformity coefficient U.
In this application, the range of uniformity coefficient U is [0,1], if the uniformity coefficient U more levels off to numerical value 1,
Then think that the uniformity of described image is better.If the uniformity coefficient U more levels off to numerical value 0, then it is assumed that described image
Uniformity is poorer.
Embodiment 2:
The embodiment of the present application provides a kind of image conformity assessment device, refers to Fig. 5, described device includes:
First computing unit 1, for obtaining the ensemble average pixel value I of image0, each pixel of described image
Imaging circumstances are identical；
Image division unit 2, for described image to be divided into M × N number of area equation rectangular area, wherein M is institute
The number of every row rectangular area in image is stated, N is the number of each column rectangular area in described image；
Second computing unit 3 calculates the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation
Sij, wherein i=1,2 ..., M；J=1,2 ..., N；
Third computing unit 4, according to the region average pixel value Iij, area pixel value mean square deviation SijWith the entirety
Average pixel value I0, calculate the uniformity coefficient U of described image；
Uniformity assessment unit 5, for assessing the uniformity of described image according to the uniformity coefficient U.
Optionally, the third computing unit 4, is also used to:
According to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate on the pixel value in each region
Limit Iij+SijWith the pixel value lower limit I in each regionij-Sij；
Obtain all pixel value upper limits and greatest member max and least member min in the pixel value lower limit；
According to uniformity coefficient formulaCalculate the uniformity coefficient U.
Optionally, the third computing unit 4, is also used to:
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel of described image
Value matrix I area pixel value mean square deviation matrix S, wherein
According to the mean pixel value matrix I and the mean square deviation matrix S, pixel value upper limit Matrix C and pixel value are calculated
Lower limit matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
Optionally, the third computing unit 4, is also used to:
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E, E=[C, D]；
The greatest member max (E) in matrix E is obtained, max (E) is used as the greatest member max, is obtained in matrix E
Min (E) is used as the least member min by least member min (E).
Optionally, the third computing unit 4, is also used to:
Judge the Iij+SijIn the numerical value of any one element whether be greater than 2bit- 1, if it is, with 2bit- 1 replacement
It is described to be greater than 2bit- 1 element, wherein bit is the bit wide of described image pixel value；
Judge the Iij-SijIn any one element whether less than 0, if it is, with the 0 replacement member less than 0
Element.
In conclusion method and apparatus provided by the present application have fully considered the wave of the pixel value in each region in image
Emotionally condition is conducive to the accuracy for improving image conformity assessment.
It should be noted that the relational terms of such as " first " and " second " or the like be used merely to an entity or
Operation is distinguished with another entity or operation, and without necessarily requiring or implying between these entities or operation, there are any
This actual relationship or sequence.Moreover, the terms "include", "comprise" or its any other variant be intended to it is non-exclusive
Property include so that including the article of a series of elements or equipment not only includes those elements, but also including not having
The other element being expressly recited, or further include for elements inherent to such a process, method, article, or device.Do not having
There is the element limited in the case where more limiting by sentence "including a ...", it is not excluded that in the mistake including the element
There is also other identical elements in journey, method, article or equipment.
The above is only the specific embodiment of the application, is made skilled artisans appreciate that or realizing this Shen
Please.Various modifications to these embodiments will be apparent to one skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the application.Therefore, the application
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
It should be understood that the application is not limited to the content for being described above and being shown in the accompanying drawings, and can
To carry out various modifications and change without departing from the scope.Scope of the present application is only limited by the accompanying claims.
Claims (10)
1. a kind of image conformity appraisal procedure, which is characterized in that the described method includes:
Obtain the ensemble average pixel value I of image0, the imaging circumstances of each pixel of described image are identical；
Described image is divided into M × N number of area equation rectangular area, wherein M is every row rectangular area in described image
Number, N are the number of each column rectangular area in described image；
Calculate the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij, wherein i=1,
2,......,M；J=1,2 ..., N；
According to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average pixel value I0, calculate institute
State the uniformity coefficient U of image；
The uniformity of described image is assessed according to the uniformity coefficient U.
2. image conformity appraisal procedure according to claim 1, which is characterized in that described to be averaged picture according to the region
Plain value Iij, area pixel value mean square deviation SijWith the ensemble average pixel value I0, the uniformity coefficient U of described image is calculated, is wrapped
It includes:
According to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate the pixel value upper limit I in each regionij
+SijWith the pixel value lower limit I in each regionij-Sij；
Obtain all pixel value upper limits and greatest member max and least member min in the pixel value lower limit；
According to uniformity coefficient formulaCalculate the uniformity coefficient U.
3. image conformity appraisal procedure according to claim 2, which is characterized in that described to be averaged picture according to the region
Plain value Iij, area pixel value mean square deviation Sij, calculate the pixel value upper limit I in each regionij+SijWith the pixel in each region
It is worth lower limit Iij-Sij, comprising:
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel value matrix of described image
I area pixel value mean square deviation S, wherein
According to the mean pixel value matrix I and the mean square deviation matrix S, pixel value upper limit Matrix C and pixel value lower limit are calculated
Matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
4. image conformity appraisal procedure according to claim 3, which is characterized in that described to obtain all pixel values
The upper limit and maximum value max and minimum value min in the pixel value lower limit, comprising:
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E, E=[C, D]；
The greatest member max (E) in matrix E is obtained, max (E) is used as the greatest member max, obtains the minimum in matrix E
Min (E) is used as the least member min by element min (E).
5. according to the described in any item image conformity appraisal procedures of claim 2-4, which is characterized in that described according to the area
Domain average pixel value Iij, area pixel value mean square deviation Sij, calculate the pixel value upper limit I in each regionij+SijWith each area
The pixel value lower limit I in domainij-Sij, further includes:
Judge the Iij+SijIn the numerical value of any one element whether be greater than 2bit- 1, if it is, with 2bit- 1 all institutes of replacement
It states and is greater than 2bit- 1 element, wherein bit is the bit wide of described image pixel value；
Judge the Iij-SijIn any one element whether less than 0, if it is, with all elements less than 0 of 0 replacement.
6. a kind of image conformity assesses device characterized by comprising
First computing unit, for obtaining the ensemble average pixel value I of image0, the imaging ring of each pixel of described image
Border is identical；
Image division unit, for described image to be divided into M × N number of area equation rectangular area, wherein M is the figure
The number of every row rectangular area as in, N are the number of each column rectangular area in described image；
Second computing unit calculates the region average pixel value I of each rectangular areaijWith area pixel value mean square deviation Sij,
In, i=1,2 ..., M；J=1,2 ..., N；
Third computing unit, according to the region average pixel value Iij, area pixel value mean square deviation SijWith the ensemble average picture
Plain value I0, calculate the uniformity coefficient U of described image；
Uniformity assessment unit, for assessing the uniformity of described image according to the uniformity coefficient U.
7. image conformity according to claim 6 assesses device, which is characterized in that the third computing unit is also used
In:
According to the region average pixel value Iij, area pixel value mean square deviation Sij, calculate the pixel value upper limit I in each regionij
+SijWith the pixel value lower limit I in each regionij-Sij；
Obtain all pixel value upper limits and greatest member max and least member min in the pixel value lower limit；
According to uniformity coefficient formulaCalculate the uniformity coefficient U.
8. image conformity according to claim 7 assesses device, which is characterized in that the third computing unit is also used
In:
According to region average pixel value IijWith area pixel value mean square deviation Sij, form the region mean pixel value matrix of described image
I and area pixel value mean square deviation S, wherein
According to the mean pixel value matrix I and the mean square deviation matrix S, pixel value upper limit Matrix C and pixel value lower limit are calculated
Matrix D, the pixel value upper limit Matrix C=I+S, the pixel value lower limit matrix D=I-S.
9. image conformity according to claim 8 assesses device, which is characterized in that the third computing unit is also used
In:
The pixel value upper limit Matrix C and pixel value lower limit matrix D are merged into synthetical matrix E, E=[C, D]；
The greatest member max (E) in matrix E is obtained, max (E) is used as the greatest member max, obtains the minimum in matrix E
Min (E) is used as the least member min by element min (E).
10. assessing device according to the described in any item image conformities of claim 7-9, which is characterized in that the third calculates
Unit is also used to:
Judge the Iij+SijIn the numerical value of any one element whether be greater than 2bit- 1, if it is, with 2bit- 1 replacement is described big
In 2bit- 1 element, wherein bit is the bit wide of described image pixel value；
Judge the Iij-SijIn any one element whether less than 0, if it is, with the 0 replacement element less than 0.
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