CN107784645A

CN107784645A - Measurement for Digital Image Definition and system, auto focusing method

Info

Publication number: CN107784645A
Application number: CN201610737073.8A
Authority: CN
Inventors: 盛司潼; 冀高
Original assignee: Guangzhou Kangxinrui Gene Health Technology Co Ltd
Current assignee: Guangzhou Kangxinrui Gene Health Technology Co Ltd
Priority date: 2016-08-26
Filing date: 2016-08-26
Publication date: 2018-03-09

Abstract

The present invention relates to image processing field, there is provided a kind of Measurement for Digital Image Definition and system, auto focusing method.It the described method comprises the following steps：Images match step, utilize images match method, all area arrays to be matched in array of templates and image predeterminable area to be evaluated are subjected to similarity mode respectively, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively, obtain Similarity value image；First filtration step, identify that Similarity value in Similarity value image is more than or pixel more than or equal to similarity threshold using similarity threshold；Definition values calculation procedure, the Similarity value of all pixels point to being identified in the first filtration step are averaged, and obtain image clarity values.The method and system of the present invention is without reference to image, you can realizes the evaluation to image definition, can apply to various practical application scenes, strong applicability；Auto focusing method of the present invention, it can fast and accurately realize the automatic focusing to reference object.

Description

Measurement for Digital Image Definition and system, auto focusing method

Technical field

The present invention relates to image processing field, more specifically to Measurement for Digital Image Definition and system, and certainly Dynamic focus method.

Background technology

Image definition evaluation is an important research direction of image processing field, available for all kinds of imaging systems into As quality testing, the control of imaging system is and guided, system is worked all the time in optimum state, it can also be used to all kinds of image procossings The assessment of algorithm, parameter optimization etc., are optimal the synthesis output result of algorithm, it may also be used for image network quality monitoring Deng.

Current Measurement for Digital Image Definition, human eye subjective judgement is generally required, or carried out using reference picture Compare.And human eye subjective judgement efficiency is low, and often there is difference between different people, it is difficult to have unified standard；In addition, in many In practical application scene, reference picture can not obtain；Therefore, the application of existing image quality evaluating method by Limit.

Therefore a kind of new Measurement for Digital Image Definition and system without reference to image is needed.

The content of the invention

It is an object of the invention to provide a kind of Measurement for Digital Image Definition and system without reference to image, it is intended to solves The problem of certainly prior art application is limited.

In order to realize goal of the invention, a kind of Measurement for Digital Image Definition, comprise the following steps：

Images match step, using images match method, by array of templates with it is all to be matched in image predeterminable area to be evaluated Area array carries out similarity mode respectively, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively Point, obtain Similarity value image；

First filtration step, identify that Similarity value is more than or more than or equal to similar in Similarity value image using similarity threshold Spend the pixel of threshold value；

Definition values calculation procedure, the Similarity value of all pixels point to being identified in the first filtration step are averaged, obtained Image clarity values.

Wherein, methods described also includes array of templates acquisition step, is calculated according to Gauss nuclear operator and obtains array of templates；Or Processing acquisition array of templates is carried out to the numerical matrix of subject matter region in real image.

Wherein, described image matching step comprises the following steps：

Normalization step, all area arrays to be matched treated according to array of templates in evaluation image predeterminable area carry out normalizing Change, the area array to be matched after must normalizing；

First matching step, using images match method, array of templates and the area array to be matched after normalization are carried out respectively Similarity mode, and each Similarity value is invested to the pixel corresponded in area array to be matched respectively, obtain Similarity value image.

Wherein, described image matching method is normalized crosscorrelation matching algorithm.

Wherein, methods described also includes the second filtration step, is treated using signal threshold value each in evaluation image predeterminable area Pixel carries out the second filtering, obtains the second filtering image；

Described image matching step is using images match method, by all areas to be matched in array of templates and the second filtering image Domain array carries out similarity mode respectively, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively, Obtain Similarity value image.

Wherein, the image to be evaluated is the gray level image of high flux gene sequencing image.

Wherein, the subject matter is sphere.

Wherein, the image predeterminable area to be evaluated is the rectangular area of image to be evaluated center.

Wherein, methods described also includes predeterminable area acquisition step, and the predeterminable area obtains step and comprised the following steps：

First takes middle step, treats during evaluation image taken, obtains the first intermediate image；

Amplification procedure, the first intermediate image is amplified using linear interpolation method, obtains enlarged drawing；

Second takes middle step, in being taken to enlarged drawing, obtains image predeterminable area to be evaluated.

In order to which goal of the invention is better achieved, present invention also offers a kind of image definition evaluation system, including image Matching module, the first filtering module and definition values computing module；

Described image matching module, for utilizing images match method, by the institute in array of templates and image predeterminable area to be evaluated Need matching area array and carry out similarity mode respectively, and each Similarity value is invested in corresponding area array to be matched respectively Pixel, obtain Similarity value image；

First filtering module, for identifying that Similarity value is more than or is more than in Similarity value image using similarity threshold Equal to the pixel of similarity threshold；

The definition values computing module, the Similarity value for all pixels point to being identified in the first filtration step are made even Average, obtain image clarity values.

Wherein, the system also includes array of templates acquisition module, and template battle array is obtained for being calculated according to Gauss nuclear operator Row；Or obtain array of templates for carrying out processing to the numerical matrix of subject matter region in real image.

Wherein, described image matching module includes normalization unit and the first matching unit；

The normalization unit, for treating all area arrays to be matched in evaluation image predeterminable area according to array of templates It is normalized, the area array to be matched after must normalizing；

First matching unit, for utilizing images match method, by array of templates and the area array to be matched after normalization Similarity mode is carried out respectively, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively, is obtained similar Angle value image.

Wherein, the system also includes the second filtering module, for treating evaluation image predeterminable area using signal threshold value In each pixel carry out the second filtering, obtain the second filtering image；

Described image matching module, for utilizing images match method, array of templates is filtered in image with second and needed Similarity mode is carried out respectively with area array, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively Point, obtain Similarity value image.

Wherein, the subject matter is sphere.

Wherein, the system also includes predeterminable area acquisition module, during the predeterminable area acquisition module takes including first Unit, amplifying unit and second take middle unit；

Described first takes middle unit, for treating during evaluation image taken, obtains the first intermediate image；

The amplifying unit, for being amplified using linear interpolation method to the first intermediate image, obtain enlarged drawing；

Described second takes middle unit, in being taken for enlarged drawing, obtains image predeterminable area to be evaluated.

In order to which goal of the invention is better achieved, present invention also offers a kind of auto focusing method, comprise the following steps：

Figure step is clapped, control filming apparatus is taken pictures in different focal positions to reference object, obtains multiple images；

Calculation procedure, the definition values of each image are calculated using any of the above-described kind of Measurement for Digital Image Definition, obtain multiple figures The definition values of picture；

Identification step, the maximum in the definition values of the multiple image is identified, define value of maximum articulation correspondence image Focal position is best focus position；

Focus steps, control filming apparatus are moved to best focus position.

In order to preferably realize goal of the invention, present invention also offers another auto focusing method, comprise the following steps：

Initial step, control module control filming apparatus are taken pictures to reference object, obtain the first image；

Calculation procedure, the definition values of the first image are calculated using any of the above-described kind of Measurement for Digital Image Definition, obtain the first figure Image sharpness value；

Judgment step, if the first image clarity values are more than or equal to clarity threshold, terminate to focus on automatically；If the first image Definition values are less than clarity threshold, then enter focusing step；

Focusing step, control module control reference object that relative displacement occurs with respect to filming apparatus, and filming apparatus is taken pictures, adjusted Burnt image；It is the first image to make the focusing image, and enters calculation procedure.

From the foregoing, it will be observed that the Measurement for Digital Image Definition and system of the present invention, by by array of templates and region to be matched Array is matched, and then the Similarity value of acquisition is filtered, and then the Similarity value to filtering out is averaged, you can Image clarity values are obtained, Measurement for Digital Image Definition of the invention and system are without reference to image, you can realize to image The evaluation of definition, it can apply to various practical application scenes, strong applicability；In addition, the present invention is based on above-mentioned image clearly Evaluation method is spent, two kinds of auto focusing methods is additionally provided, can fast and accurately realize the automatic focusing to reference object.

Brief description of the drawings

Fig. 1 is the method flow diagram of first embodiment of the invention.

Fig. 2 is the Method And Principle schematic diagram of first embodiment of the invention.

Fig. 3 is several examples of the array of templates of the present invention.

Fig. 4 is curve map corresponding to the Gauss nuclear operator of the present invention.

Fig. 5 is the gray level image of the high flux gene sequencing image in the specific embodiment of the present invention.

Fig. 6 is the numerical matrix calculated based on Gauss nuclear operator obtained by Fig. 5 adjustment.

Fig. 7 is the array of values in several regions to be matched in one embodiment of the invention in the front and rear comparison diagram of normalization.

Fig. 8 is the method flow diagram of the second embodiment of the present invention.

Fig. 9 is the method flow diagram of the predeterminable area acquisition step in the third embodiment of the present invention.

Figure 10 is that the principle of two steps of S92, S93 in the predeterminable area acquisition step in one embodiment of the present of invention is shown It is intended to.

Figure 11 is the principle schematic of the predeterminable area acquisition step in the specific embodiment of the present invention.

The schematic diagram of image definition evaluation system in Figure 12 fourth embodiment of the present invention.

Figure 13 is the schematic diagram of the image definition evaluation system in the fifth embodiment of the present invention.

Figure 14 is the schematic diagram of the predeterminable area acquisition module in the sixth embodiment of the present invention.

Figure 15 is the auto focusing method flow chart in one embodiment of the present of invention.

Figure 16 is the auto focusing method flow chart in an alternative embodiment of the invention.

Embodiment

In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples The present invention is further elaborated.

As shown in Figure 1 and Figure 2, the present invention proposes first embodiment, a kind of Measurement for Digital Image Definition, methods described bag Include following steps：

S11, images match step, using images match method, by array of templates with being needed in image predeterminable area to be evaluated Matching area array carries out similarity mode respectively, and each Similarity value is invested to the picture in corresponding area array to be matched respectively Vegetarian refreshments, obtain Similarity value image；

S12, the first filtration step, identify that Similarity value is more than or is more than or equal in Similarity value image using similarity threshold The pixel of similarity threshold；

S13, definition values calculation procedure, the Similarity value of all pixels point to being identified in the first filtration step are averaged Value, obtains image clarity values.

It should be noted that in the present embodiment, the array of templates is that have definite shape by what series of values was formed With the array of values of size；The actual Similarity value image is Similarity value array.The image predeterminable area to be evaluated is The rectangular area of image center to be evaluated.As shown in Fig. 2 area array 1 to be matched is defined as in image predeterminable area to be evaluated Any one array of values formed with each pixel numerical value in array of templates size, shape identical region, it is each to be matched There may be lap between area array.

The image to be evaluated can be common photo, or professional equipment is taken pictures gained photo, such as utilize high flux High flux gene sequencing image obtained by gene sequencer shooting.

In specific procedure, the size and shape of array of templates can carry out accommodation as needed, such as Size and shape of the subject matter in image to be evaluated.The subject matter is depending on needing identification or main pass in specific image to be evaluated Depending on the object of note, lived thing or the effigurate object of tool in image including but not limited to be evaluated.The mark Thing be preferably the object with special construction or shape, the requirement of special construction or shape for images match method is relatively low, needs The factor to be considered is less, and Similarity value differs greatly, and it is more accurate to enter line definition evaluation by this method.When to be evaluated When image is high flux gene sequencing image, the subject matter is preferably sphere or like ball thing, such as magnetic bead or microballon.This hair The bright quantity without concrete restriction for treating the subject matter in evaluation image.

The method of the present embodiment is by by all region battle arrays to be matched in array of templates and image predeterminable area to be evaluated Row are matched, and then the Similarity value of acquisition are filtered, and then the Similarity value to filtering out is averaged, you can To image clarity values；That is, the method for the present embodiment is without reference to image, you can realizes the evaluation to image definition, can answer For various practical application scenes, strong applicability, and the use of array of templates so that image clarity values being capable of more accurately generation The definition situation of object for needing to identify in table image to be evaluated or being primarily upon.

In the specific embodiment of the present invention, the Similarity value is invested in corresponding area array to be matched respectively Imago vegetarian refreshments., also can be by these phases in the alternate embodiment that the central pixel point of area array to be matched is invested in Similarity value Invested respectively like angle value adjacent above pixel, such as central pixel point corresponding to the other positions in area array to be matched Adjacent pixel below pixel or central pixel point.

In another specific embodiment, image predeterminable area size to be evaluated is M × N, and array of templates size is P × Q, institute State area array to be matched for any one in image predeterminable area to be evaluated with array of templates size, shape identical region Each pixel numerical value composition array of values, then area array size to be matched is also P × Q, then pre- in image to be evaluated If shared in region（M-P+1）×（N-Q+1）Individual area array to be matched.Now, the array of templates and image to be evaluated are pre- If the similarity mode that all area arrays to be matched in region are carried out respectively, carried out successively with the movement of individual element point 's.It is preferred that since wantonly 1 corner in 4 corners of image predeterminable area to be evaluated, and from wantonly 1 in remaining 3 corner Individual corner is terminated, and the motion track in whole matching process is snakelike route or several parallel lines.The present embodiment can be real Existing Rapid matching, and ensure the accuracy rate of matching.

In the alternate embodiment of above-mentioned specific embodiment, the array of templates and the institute in image predeterminable area to be evaluated Need similarity mode that matching area array carries out respectively or with mobile 2,3,5 or more pictures every time Vegetarian refreshments movement is carried out successively.Accordingly, in this alternate embodiment, the area array to be matched is image preset areas to be evaluated Any one in domain and the array of values of each pixel numerical value composition in array of templates size, shape identical region, and respectively Spacing between the central point of the central point area array to be matched adjacent thereto of area array to be matched for 2,3,5 or More pixels.This alternate embodiment can significantly improve matching efficiency.

For similarity threshold it should be noted that the similarity threshold can be set as needed.Treated for example, working as Evaluation image is high flux gene sequencing image, and when the subject matter is magnetic bead or microballon, the similarity threshold is preferably 0.3 Any value into 0.8.In the present embodiment, because high flux gene sequencing image more rule, it is substantially not present in image Other articles in addition to subject matter, so similarity threshold is located to any value in 0.3 to 0.8, the equal energy of acquired results Effectively distinguish the definition of image to be evaluated.

In one embodiment, the similarity threshold is preferably 0.5.This specific embodiment can preferably avoid treating That partly overlapping subject matter corresponds to Similarity value and is identified in evaluation image between each other be present, treat evaluation image Discrimination it is more preferable.Because partly overlapping subject matter in image to be evaluated between each other be present, in high flux gene sequencing figure It can be interfered with each other in the subsequent processes of picture, reduce the accuracy of result, so this programme can improve whole high pass Measure the accuracy of gene sequencing processing result image.

For array of templates, it is necessary to illustrate, the shapes and sizes of the array of templates preferably with image to be evaluated Subject matter shapes and sizes it is consistent or almost consistent.The array of templates that part can use in the present invention is shown in Fig. 3. The array of templates can be set to array of values or numerical matrix with definite shape and size as needed.The template Numerical value in array can be light signal strength, and the light signal strength can be to be represented by rgb value, i.e. colour picture signal value； Or represented by gray value, i.e. black-and-white image signal value.The corresponding image to be evaluated can be alternatively for coloured image Black white image.

Preferably, each numerical value in the array of templates corresponds to the artwork master of one or more pixels of the position The gray value of picture.This programme can substantially reduce array of templates and all area arrays to be matched in image predeterminable area to be evaluated Operand during similarity mode is carried out, improves efficiency.

On the basis of any of the above-described embodiment, the present invention proposes one embodiment, also includes mould before the step S11 Plate array obtains step S10：Processing acquisition array of templates is carried out to the numerical matrix of subject matter region in real image.

The present embodiment obtains array of templates based on actually detected obtained numerical matrix after processing, and method is simple, right The relatively regular or smooth object of subject matter is especially suitable in image.It should be noted that the processing in the present embodiment can have A variety of implementations, it will be specifically described below by numerous embodiments.

In one embodiment of the invention, the array of templates is method manually or automatically, to having schemed Subject matter as in is detected, and then obtains its corresponding array of values, and the numerical matrix can be directly as array of templates.

In another embodiment of the present invention, the acquisition of the array of templates is similar with a upper embodiment, Bu Guoqi By being detected to the subject matter in existing image, and then multiple array of values are obtained, then pass through the multiple numerical value battle array After row carry out average value processing, the array of values after average value processing is obtained as array of templates.The average value processing is by more numbers The numerical value of same position is added and averaged in value array, so as to obtain the array of values of multiple average value compositions.

In the present embodiment, by average value processing, it can make that array of templates is more representative, and matching result is more accurate.

In addition, the array of templates can according to subject matter represented characteristic under light illumination, by corresponding algorithm and .For example, when the image to be evaluated be high flux gene sequencing image gray level image, when subject matter is magnetic bead or microballon, The intensity of reflected light distribution of magnetic bead is similar with the curve distribution of Gauss nuclear operator in image to be evaluated.The number of the Gauss nuclear operator Learning expression formula is：

The figure of above-mentioned mathematic(al) representation is as shown in Figure 4.Wherein a represents the height of curve, and b refers to curve in the center of x-axis, c Refer to the width of curve.

As shown in figure 4, function of region value is maximum centered on the characteristics of above-mentioned Gauss nuclear operator, the equidistant function with central point It is worth identical, and functional value is relative to the specific exponentially type downward trend of central point and the point.With magnetic bead in image to be evaluated Intensity of reflected light distribution is very much like.According to the size of magnetic bead in image to be evaluated, the gray-value variation of each pixel of magnetic bead becomes Gesture, adjust a, b, c value in above-mentioned mathematic(al) representation, you can obtain the Gauss highly similar to magnetic bead in image to be evaluated and adjust Son.The method of the present embodiment is particularly suitable for use in the gray level image that image to be evaluated is high flux gene sequencing image, and subject matter is The situation of magnetic bead or microballon, it being capable of the effectively image to be evaluated for distinguishing different definition.

In one particular embodiment of the present invention, Fig. 5 is the gray level image of high flux gene sequencing image, and Fig. 6 is base In the numerical matrix that Gauss nuclear operator obtained by Fig. 5 adjustment calculates, the numerical matrix can be used as array of templates, for similarity Matching, image to be evaluated be with Fig. 5 the same terms shooting obtained by high flux gene sequencing image gray level image.It is corresponding , a=35100, b=0, c=4/3 in the expression formula of the Gauss nuclear operator.

Because during the similarity mode of the step S11, what Similarity value considered is array of templates with treating Subfield value to be matched and numerical value change trend in evaluation image predeterminable area, and influenceed by illumination variation, it is same to be evaluated The numerical value of the subject matter of diverse location in image predeterminable area may differ greatly, but numerical value change trend is identical； Subject matter in different image predeterminable areas to be evaluated obtained by the same terms shooting equally exists above mentioned problem.

For influence of the numerical value difference to Similarity value caused by solving illumination variation, the present invention is in any of the above-described embodiment On the basis of propose an embodiment, methods described, which is additionally included in the step S11, specific carries out similarity mode meter each time Before calculation, in addition to the step of the area array to be matched treated in evaluation image predeterminable area is normalized.This programme can drop Influence of the low illumination variation to Similarity value, accuracy rate of the definition evaluation method of the present invention in similarity mode is improved, And then more accurately distinguish the definition of image to be evaluated.

On the basis of above-described embodiment, the present invention proposes another embodiment, and the step S11 comprises the following steps：

S111, normalization step：All area arrays to be matched treated in evaluation image predeterminable area are normalized, and must return Area array to be matched after one change；

S112, the first matching step：Using images match method, array of templates and the area array to be matched after normalization are distinguished Similarity mode is carried out, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively, obtains Similarity value Image.

It should be noted that the normalization step there are a variety of implementations, will be carried out below by multiple embodiments It is expanded on further.

In one embodiment of the invention, the normalization step is using array of templates as normalization array of templates, institute The each numerical value needed in matching area array is multiplied by z；The z is coefficient of variation, for example, the center of normalization array of templates The ratio of point value and the centerpoint value in region to be matched.In one particular embodiment of the present invention, z=a/b；The a is normalizing Change the centerpoint value of array of templates, the b is the centerpoint value in region to be matched.

Fig. 7 shows in one embodiment of the invention that the array of values in several regions to be matched is in front and rear pair of normalization Than.Wherein, for masterplate array as normalization array of templates, A, B, C are the array of values before region normalization to be matched respectively, A ', B ', C ' are the array of values after region A, B, C normalization to be matched respectively.

For normalization array of templates it should be noted that it is not limited to array of templates, in another implementation of the present invention In example, the normalization array of templates is the array of values separately built, different from array of templates.In normalization, by template The array of values in array and region to be matched is normalized by the normalization array of templates.

For the coefficient of variation, it is not limited to central point of the centerpoint value with region to be matched for normalizing array of templates The ratio of value, as long as this ratio is the ratio for normalizing the numerical value of same position in array of templates and region to be matched. Such as normalize the ratio of point value adjacent above the array of templates central point point value adjacent with above regional center point to be matched.

It is high flux gene sequencing image for image to be evaluated, when subject matter is magnetic bead, because subject matter and template battle array It is that central point is most bright place in row；That is numerical value highest place；Using centerpoint value ratio as coefficient of variation, phase can be improved Like the accuracy of degree matching.

It is high flux gene sequencing image for image to be evaluated, subject matter is the concrete condition of magnetic bead, any of the above-described On the basis of embodiment, the present invention proposes a specific embodiment, and described image matching method is to carry out matching meter based on Euclidean distance Calculate.

In the another specific embodiment of the present invention, described image matching method is normalized crosscorrelation matching algorithm.

In one particular embodiment of the present invention, the normalized crosscorrelation matching algorithm is：

Wherein, NCC is Similarity value, and w (x, y) is array of templates, and g (x, y) is area array to be matched, is that array of templates is equal Value, it is regional average value to be matched, m is the length of template area, and n is the width of template area.

This specific embodiment while matching primitives are carried out, realizes normalizing by normalized crosscorrelation matching algorithm Change, both reduced influence of the illumination variation to Similarity value, improve the Measurement for Digital Image Definition of the present invention in similarity mode When accuracy rate, and then more accurately distinguish the definition of image to be evaluated, in turn simplify calculating process, improve efficiency.

In order to avoid noise in image to be evaluated is to obtaining the influence of image definition accuracy to be evaluated, the present invention is the Second embodiment, a kind of Measurement for Digital Image Definition, as shown in figure 8, comprising the following steps are proposed on the basis of one embodiment：

S81, the second filtration step, treat each pixel in evaluation image predeterminable area using signal threshold value and carry out the second filtering, Obtain the second filtering image；

S82, images match step, using images match method, by all areas to be matched in array of templates and the second filtering image Domain array carries out similarity mode respectively, and each Similarity value is invested to the pixel in corresponding area array to be matched respectively, Obtain Similarity value image；

S83, the first filtration step, identify that Similarity value is more than or is more than or equal in Similarity value image using similarity threshold The pixel of similarity threshold；

S84, definition values calculation procedure, the Similarity value of all pixels point to being identified in the first filtration step are averaged Value, obtains image clarity values.

It should be noted that second filtering is according to signal threshold value, identifies and believe in image predeterminable area to be evaluated Number value more than or equal to signal threshold value pixel.The second filtering image, is defined as after the second filtration step, figure to be evaluated It is identified as in, signal value is more than or equal to the image that the pixel of signal threshold value forms.The signal value, signal threshold value with Numerical value in the array of templates is same type, can be light signal strength, and the light signal strength can be to pass through rgb value table Show, i.e. colour picture signal value；Or represented by gray value, i.e. black-and-white image signal value.

In the present embodiment, define area array to be matched for any one in the second filtering image with array of templates size, The array of values of each pixel numerical value composition in shape identical region.Other necessity define identical with first embodiment.

Handled in the present embodiment by treating evaluation image predeterminable area in advance, both avoided and made an uproar in image to be evaluated Influence of the sound to the definition values of acquisition image to be evaluated, reduces the operand in S82 steps, improves to figure to be evaluated again The discrimination and evaluation efficiency of image sharpness.

In the present embodiment, the signal threshold value can be set as needed.For example, when image to be evaluated is gray scale During image, the signal threshold value can be 100,300,500,1000 or higher.

When image to be evaluated is high flux gene sequencing image, and subject matter is luminous magnetic bead, because image to be evaluated The false signal of magnetic bead and the weak signal of random distribution cannot can not be remained luminously in background, these noises are in images match step In, it is also possible to larger matching factor is calculated, and is identified in the first follow-up filtration step, it is follow-up so as to influence Definition values calculation procedure.And often signal value is relatively low for above-mentioned noise, therefore increase the second above-mentioned filtration step, and to image Matching step carries out adaptation, can effectively remove the influence of above-mentioned noise, improves the definition for treating evaluation image Discrimination and evaluation efficiency.

In one particular embodiment of the present invention, when the gray level image that image to be evaluated is high flux gene sequencing image When, when subject matter is luminous magnetic bead, the signal threshold value is preferably between 300 to 1000.In this section, it can preferably remove and treat Noise in evaluation image.

For image predeterminable area to be evaluated, it is necessary to illustrate, it can be any one region in image to be evaluated Or whole image to be evaluated, the present invention have no particular/special requirement, will be further elaborated below by embodiment.

In most cases, need to identify in image to be evaluated or the object that is primarily upon is in the center of image to be evaluated. Therefore, in the preferred embodiment of the present invention, the image predeterminable area to be evaluated is image to be evaluated center Rectangular area.In the present embodiment, it can cause the image clarity values of acquisition are more accurately represented in image to be evaluated to need to know Not or the definition situation of object that is primarily upon, and can effectively reduce amount of calculation, improve efficiency.

In another preferred embodiment of the present invention, the image to be evaluated is rectangular image, the image to be evaluated The rectangular area that predeterminable area is hit exactly by image to be evaluated, and it is distributed in four rectangular areas in four corners of image to be evaluated Composition.The relatively upper specific embodiment of the present embodiment, gained definition values have preferably representative.

On the basis of any of the above-described embodiment, the present invention proposes 3rd embodiment, and the definition evaluation method is also wrapped Include predeterminable area and obtain step, the predeterminable area obtains step as shown in figure 9, comprising the following steps：

S91, first take middle step, treat during evaluation image taken, obtain the first intermediate image；

S92, amplification procedure, the first intermediate image is amplified using linear interpolation method, obtains enlarged drawing；

S93, second take middle step, in being taken to enlarged drawing, obtain image predeterminable area to be evaluated.

The present embodiment by taking, linear interpolation method send out it is big, take middle step again, can either accurately represent image to be evaluated The definition situation of the middle object for needing to identify or be primarily upon, effectively reduces the amount of calculation of successive image matching step, carries High efficiency, the quantity for the pixel being identified in follow-up first filtration step in unit area can be improved again, is further carried Height treats the discrimination of evaluation image definition.

It should be noted that can be optionally configured in taking in the step S91 and S93, the scope in taking can phase It is same or different.The present invention a preferred embodiment in, it is above-mentioned take middle gained image be original image area half extremely 60 a quarters.The more preferably a quarter of original image area.Amplification in the step S92 also can optionally be set Put.In another preferred embodiment of the present invention, the first intermediate image is amplified to originally by being enlarged into the step S92 1.5 times to 64 times of area.More preferably 4 times of original image area.

In one embodiment of the invention, as shown in Figure 10, it illustrates S92, S93 two that predeterminable area obtains module Individual step；Wherein, the first intermediate image is 3 × 3 array of values, after its amplified step after 2 times of amplification gained image be 6 × 6 array of values, then takes middle step through second, and gained image predeterminable area to be evaluated is 4 × 4 array of values.Need Bright is that Figure 10 is only schematic diagram.

In one particular embodiment of the present invention, the image to be evaluated is the gray-scale map of high flux gene sequencing image Picture, as shown in figure 11, step in being taken first, selected is the figure of a quarter surface area of image center to be evaluated Picture, i.e. the first intermediate image are the image that image to be evaluated hits exactly a quarter area；Then in amplification procedure, using linear First intermediate image area is amplified 4 times by interpolation method, obtains enlarged drawing；In finally being taken second in step, selected is to put The image of a quarter surface area of big image center, i.e., image predeterminable area to be evaluated be enlarged drawing center four/ The image of one area.It should be noted that Figure 11 is only to illustrate, in actual processing procedure, these images are all with numerical value battle array What the form of row represented.

Present invention also offers fourth embodiment, a kind of image definition evaluation system, as shown in figure 12, the system 100 include images match module 110, the first filtering module 120 and definition values computing module 130；

Described image matching module 110, for utilizing images match method, by array of templates and image predeterminable area to be evaluated All area arrays to be matched carry out similarity mode respectively, and each Similarity value is invested to corresponding area array to be matched respectively In pixel, obtain Similarity value image；

First filtering module 120, for using similarity threshold identify in Similarity value image Similarity value be more than or More than or equal to the pixel of similarity threshold；

The definition values computing module 130, the Similarity value for all pixels point to being identified in the first filtration step Average, obtain image clarity values.

It should be noted that in the present embodiment, the module or system can perform the integrated circuit of specific function, It can be stored in storage device and the software program of corresponding function is completed by computing device.

The array of templates is the array of values with definite shape and size being made up of series of values；It is described similar Actual angle value image is Similarity value array.The image predeterminable area to be evaluated is the rectangular area of image to be evaluated center. Area array to be matched is defined as any one in image predeterminable area to be evaluated and array of templates size, shape identical region In each pixel numerical value composition array of values, may have lap between each area array to be matched.

In specific system work process, the size and shape of the array of templates can carry out adaptability tune as needed It is whole, such as size and shape of the subject matter in image to be evaluated.The subject matter in specific image to be evaluated depending on needing to identify Or depending on the object being primarily upon, lived thing or the effigurate thing of tool in image including but not limited to be evaluated Body.The subject matter is preferably the object with special construction or shape, and special construction or shape are for images match module 110 Requirement it is relatively low, it is necessary to which the factor considered is less, and Similarity value differs greatly, line definition evaluation is entered more by the system Accurately.When image to be evaluated is high flux gene sequencing image, the subject matter is preferably sphere or like ball thing, such as magnetic Pearl or microballon.The present invention treats the quantity without concrete restriction of the subject matter in evaluation image.

The system 100 of the present embodiment is by by all regions to be matched in array of templates and image predeterminable area to be evaluated Array is matched, and then the Similarity value of acquisition is filtered, and then the Similarity value to filtering out is averaged, you can Obtain image clarity values；That is, the system 100 of the present embodiment passes through images match module 110, the first filtering module 120 and clear The mutual cooperation of clear angle value computing module 130, without reference to image, you can realize the evaluation to image definition, can apply to Various practical application scenes, strong applicability, and the use of array of templates so that image clarity values can more accurately be represented and treated The definition situation of object for identifying or being primarily upon is needed in evaluation image.

On the basis of any of the above-described embodiment, the present invention proposes one embodiment, described image definition evaluation system Also include array of templates and obtain module, mould is obtained for carrying out processing to the numerical matrix of subject matter region in real image Plate array.

The present embodiment obtains array of templates based on actually detected obtained numerical matrix after processing, simple, efficient, right The relatively regular or smooth object of subject matter is especially suitable in image.It should be noted that the processing in the present embodiment can have A variety of implementations, it will be specifically described below by numerous embodiments.

In one embodiment of the invention, the array of templates obtains module, for the target in existing image Thing is detected, and then obtains its corresponding array of values, and the numerical matrix can be directly as array of templates.

In another embodiment of the present invention, the array of templates acquisition module is similar with a upper embodiment, but It is specially：For being detected to the subject matter in existing image, and then multiple array of values are obtained, then by described more After individual array of values carries out average value processing, the array of values after average value processing is obtained as array of templates.The average value processing is The numerical value of same position in multiple array of values is added and averaged, so as to obtain the array of values of multiple average value compositions.

For above-described embodiment, the present invention proposes another alternate embodiment, and described image definition evaluation system also includes Array of templates obtains module：For according to subject matter represented characteristic under light illumination, passing through corresponding algorithm and obtaining template Array.For example, when the gray level image that the image to be evaluated is high flux gene sequencing image, subject matter is magnetic bead or microballon When, the intensity of reflected light distribution of magnetic bead is similar with the curve distribution of Gauss nuclear operator in image to be evaluated.The Gauss nuclear operator Mathematic(al) representation be：

As shown in figure 4, function of region value is maximum centered on the characteristics of above-mentioned Gauss nuclear operator, the equidistant function with central point It is worth identical, and functional value is relative to the specific exponentially type downward trend of central point and the point.With magnetic bead in image to be evaluated Intensity of reflected light distribution is very much like.According to the size of magnetic bead in image to be evaluated, the gray-value variation of each pixel of magnetic bead becomes Gesture, adjust a, b, c value in above-mentioned mathematic(al) representation, you can obtain the Gauss highly similar to magnetic bead in image to be evaluated and adjust Son.The system of the present embodiment is particularly suitable for use in the gray level image that image to be evaluated is high flux gene sequencing image, and subject matter is The situation of magnetic bead or microballon, it being capable of the effectively image to be evaluated for distinguishing different definition.

Now, the array of templates obtains module, and array of templates is obtained for being calculated according to Gauss nuclear operator.

Because described image matching module is in the course of the work, what Similarity value considered is array of templates with it is to be evaluated Subfield value to be matched and numerical value change trend in image predeterminable area, and influenceed by illumination variation, same image to be evaluated The numerical value of the subject matter of diverse location in predeterminable area may differ greatly, but numerical value change trend is identical；It is identical Subject matter in different image predeterminable areas to be evaluated obtained by condition shooting equally exists above mentioned problem.

For influence of the numerical value difference to Similarity value caused by solving illumination variation, the present invention is in any of the above-described embodiment On the basis of propose an embodiment, described image matching module, be additionally operable to carry out before similarity mode calculates each time specific, The area array to be matched treated in evaluation image predeterminable area is normalized.This programme can reduce illumination variation to similarity The influence of value, improve accuracy rate of the image definition evaluation system of the present invention in similarity mode, and then more accurately area Divide the definition of image to be evaluated.

On the basis of above-described embodiment, the present invention proposes another embodiment, wherein, described image matching module includes returning One changes unit and the first matching unit；

In one embodiment of the invention, the normalization unit is using array of templates as normalization array of templates, institute The each numerical value needed in matching area array is multiplied by z；The z is coefficient of variation, for example, the center of normalization array of templates The ratio of point value and the centerpoint value in region to be matched.In one particular embodiment of the present invention, z=a/b；The a is normalizing Change the centerpoint value of array of templates, the b is the centerpoint value in region to be matched.

This specific embodiment while matching primitives are carried out, realizes normalizing by normalized crosscorrelation matching algorithm Change, both reduced influence of the illumination variation to Similarity value, improve the image definition evaluation system of the present invention in similarity mode When accuracy rate, and then more accurately distinguish the definition of image to be evaluated, in turn simplify calculating process, improve efficiency.

In order to avoid noise in image to be evaluated is to obtaining the influence of image definition accuracy to be evaluated, the present invention is the The 5th embodiment of proposition on the basis of four embodiments, a kind of image definition evaluation system, as shown in figure 13, the system 200 Including images match module 210, the first filtering module 220, the filtering module 240 of definition values computing module 230 and second；

Second filtering module, the second mistake is carried out for treating each pixel in evaluation image predeterminable area using signal threshold value Filter, obtains the second filtering image；

Described image matching module 210, for utilizing images match method, by array of templates with being needed in the second filtering image Matching area array carries out similarity mode respectively, and each Similarity value is invested to the picture in corresponding area array to be matched respectively Vegetarian refreshments, obtain Similarity value image.

First filtering module 220, for identifying that Similarity value is big in Similarity value image using similarity threshold In or more than or equal to similarity threshold pixel；

The definition values computing module 230, the Similarity value for all pixels point to being identified in the first filtration step Average, obtain image clarity values.

It should be noted that second filtering is according to signal threshold value, identifies and believe in image predeterminable area to be evaluated Number value more than or equal to signal threshold value pixel.The second filtering image, is defined as after the second filtration step, figure to be evaluated It is identified as in, signal value is more than or equal to the image that the pixel of signal threshold value forms.The signal value and the template Numerical value in array is same type, can be light signal strength, the light signal strength can be to be represented by rgb value, i.e., colored Image signal value；Or represented by gray value, i.e. black-and-white image signal value.

In the present embodiment, define area array to be matched for any one in the second filtering image with array of templates size, The array of values of each pixel numerical value composition in shape identical region.Other necessity define identical with fourth embodiment.

Handled in the present embodiment by treating evaluation image predeterminable area in advance, both avoided and made an uproar in image to be evaluated Influence of the sound to the definition values of acquisition image to be evaluated, reduces the operand of images match module, improves to be evaluated again The discrimination and evaluation efficiency of valency image definition.

When image to be evaluated is high flux gene sequencing image, and subject matter is luminous magnetic bead, because image to be evaluated The false signal of magnetic bead and the weak signal of random distribution cannot can not be remained luminously in background, these noises are in images match module work During work, it is also possible to calculate larger matching factor, and be identified in the first follow-up filtering module, so as to influence Follow-up definition values calculation procedure.And often signal value is relatively low for above-mentioned noise, therefore increase the second above-mentioned filtering module, and Adaptation is carried out to images match module, can effectively remove the influence of above-mentioned noise, evaluation image is treated in raising The discrimination and evaluation efficiency of definition.

On the basis of any of the above-described embodiment, the present invention proposes sixth embodiment, and the system also includes predeterminable area Module is obtained, as shown in figure 14, the predeterminable area obtains module 250 and takes middle unit 2510, amplifying unit 2520 including first Middle unit 2530 is taken with second；

Described first takes middle unit 2510, for treating during evaluation image taken, obtains the first intermediate image；

The amplifying unit 2520, for being amplified using linear interpolation method to the first intermediate image, obtain enlarged drawing；

Described second takes middle unit 2530, in being taken for enlarged drawing, obtains image predeterminable area to be evaluated.

It should be noted that the predeterminable area obtains the operation principle schematic diagram of module referring to Figure 10；Described first takes Middle unit 2510 and second takes in taking in middle unit 2530 and can be optionally configured.In the preferred embodiment of the present invention In, it is above-mentioned to take half that middle gained image is original image area to 60 a quarters.More preferably original image area A quarter.Amplification in the amplifying unit 2520 also can be optionally configured.Another in the present invention is preferably implemented In example, the first intermediate image is amplified to 1.5 times to 64 times of original area by being enlarged into the amplifying unit 2520.It is more excellent Elect original image area as 4 times.

As shown in figure 15, present invention also offers a kind of auto focusing method, comprise the following steps：

S151, figure step is clapped, control filming apparatus is taken pictures in different focal positions to reference object, obtains multiple figures Picture；

S152, calculation procedure, the definition values of each image are calculated using any of the above-described kind of Measurement for Digital Image Definition, much The definition values of individual image；

S153, identification step, the maximum in the definition values of the multiple image is identified, define value of maximum articulation corresponding diagram The focal position of picture is best focus position；

S154, focus steps, control filming apparatus are moved to best focus position.

The auto focusing method of the present embodiment utilizes above-mentioned any image definition evaluation after multiple images are obtained Method, definition highest image can be fast and effectively compared, and then determine best focus position, so as to focus to automatically Best focus position.

As shown in figure 16, present invention also offers another auto focusing method, comprise the following steps：

S161, initial step, control module control filming apparatus are taken pictures to reference object, obtain the first image；

S162, calculation procedure, the definition values of the first image are calculated using any of the above-described kind of Measurement for Digital Image Definition, obtain the One image clarity values；

S163, judgment step, if the first image clarity values are more than or equal to clarity threshold, terminate to focus on automatically；If the One image clarity values are less than clarity threshold, then enter focusing step；

S164, focusing step, control module control reference object that relative displacement occurs with respect to filming apparatus, and filming apparatus is taken pictures, Obtain focusing image；It is the first image to make the focusing image, and enters calculation procedure.

It should be noted that the clarity threshold, can be set as needed.If the first image clarity values are more than Or equal to clarity threshold, then it is assumed that the first image reaches definition requirement, terminates automatic focus on；If the first image clearly Angle value is less than clarity threshold, then it is assumed that not up to definition requirement, into focusing step, by controlling reference object is relative to clap Take the photograph device and relative displacement, i.e. follow shot object, or follow shot device occurs, or follow shot object and shooting fill simultaneously Put, change focal length.The method of the present embodiment, available for the clearer and more definite situation of reference object, especially repeat to identical or class As reference object situation about being focused on automatically, method is simple, quick, efficiency high.

In the preferred embodiment of the present invention, the reference object is high flux gene sequencing image, in image Principal concern is microballon or magnetic bead, and the clarity threshold is 0.62.

The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention All any modification, equivalent and improvement made within refreshing and principle etc., should be included in the scope of the protection.

Claims

1. a kind of Measurement for Digital Image Definition, it is characterised in that the described method comprises the following steps：

2. Measurement for Digital Image Definition according to claim 1, it is characterised in that methods described also includes array of templates Step is obtained, is calculated according to Gauss nuclear operator and obtains array of templates；Or the numerical value square to subject matter region in real image Battle array carries out processing and obtains array of templates.

3. Measurement for Digital Image Definition according to claim 1, it is characterised in that described image matching step include with Lower step：

4. Measurement for Digital Image Definition according to claim 1, it is characterised in that described image matching method is normalization Cross Correlation Matching algorithm.

5. Measurement for Digital Image Definition according to claim 1, it is characterised in that methods described also includes the second filtering Step, treat each pixel in evaluation image predeterminable area using signal threshold value and carry out the second filtering, obtain the second filtering image；

6. Measurement for Digital Image Definition according to claim 2, it is characterised in that the image to be evaluated is high flux The gray level image of gene sequencing image, the subject matter are sphere.

7. Measurement for Digital Image Definition according to claim 1, it is characterised in that the image predeterminable area to be evaluated For the rectangular area of image to be evaluated center.

8. Measurement for Digital Image Definition according to claim 1, it is characterised in that methods described also includes predeterminable area Step is obtained, the predeterminable area obtains step and comprised the following steps：

9. a kind of image definition evaluation system, it is characterised in that the system includes images match module, the first filtering module With definition values computing module；

10. image definition evaluation system according to claim 9, it is characterised in that the system also includes template battle array Row obtain module, and array of templates is obtained for being calculated according to Gauss nuclear operator；Or for subject matter location in real image The numerical matrix in domain carries out processing and obtains array of templates.

11. image definition evaluation system according to claim 9, it is characterised in that described image matching module includes Normalization unit and the first matching unit；

12. image definition evaluation system according to claim 9, it is characterised in that described image matching method is normalizing Change Cross Correlation Matching algorithm.

13. image definition evaluation system according to claim 9, it is characterised in that the system also includes the second mistake Module is filtered, the second filtering is carried out for treating each pixel in evaluation image predeterminable area using signal threshold value, obtains the second filtering Image；

14. image definition evaluation system according to claim 10, it is characterised in that the image to be evaluated is high pass The gray level image of gene sequencing image is measured, the subject matter is sphere.

15. image definition evaluation system according to claim 9, it is characterised in that the image preset areas to be evaluated Domain is the rectangular area of image to be evaluated center.

16. image definition evaluation system according to claim 9, it is characterised in that the system also includes preset areas Domain obtains module, and the predeterminable area obtains module and takes middle unit, amplifying unit and second to take middle unit including first；

17. a kind of auto focusing method, it is characterised in that comprise the following steps：

Calculation procedure, the definition of each image is calculated using any one of claim 1 to 8 Measurement for Digital Image Definition Value, obtain the definition values of multiple images；

Focus steps, control filming apparatus are moved to best focus position.

18. a kind of auto focusing method, it is characterised in that comprise the following steps：

Calculation procedure, the clear of the first image is calculated using Measurement for Digital Image Definition any one of claim 1 to 8 Angle value, obtain the first image clarity values；