CN1877438A - Self-adaptive automatic focusing method used in digital camera - Google Patents

Abstract

Disclosed is a self-adapting self-focusing method in digital camera. The method comprises steps of: a. collecting original colorful image with digital camera; b. taking the central area in the original colorful image as sub image and cutting out with self-adapting window according to the resolution of the original image; c. converting the colorful sub image into gray-scale image; d. performing two dimensional DCT transformation on the gray-scale sub image and obtaining two dimensional DCT coefficients; e. performing self-adapting weight on the two dimensional DCT coefficients according to its frequency and calculating image clearness evaluation function; f. employing a global searching strategy to control the movement of the stepper motor according to the image clearness evaluation function and searching out clear focused-image.

Description

Self-adapting automatic focus method in the digital camera

Technical field

The present invention is the automatic focus technology in a kind of digital camera, belongs to the technical field of the Flame Image Process of digital camera.

Background technology

On ultimate principle, auto focusing method can be divided into two big classes: a class is an active method; Another kind of is passive method.Active method is based on the distance-finding method of range observation between camera lens and the subject, situation according to subject is adjusted optical system, the feature of active method is to come the distance and bearing of Measuring Object by the electromagnetic wave that receives initiatively emission or the reflection wave of sound wave, and according to optical imaging concept calculating optimum focal position, control motor to realize automatic focus by message handler then, therefore this method is called active method.Owing to need additional distance-measuring equipment, therefore adopt the general volume of instrument of this method bigger, carry inconvenience, price is higher, and not too suitable for in-plant situation.

Passive method refers to that the information of utilizing image that optical system is obtained itself to be had by oneself realizes automatic focus, and the adjusting of process lens location is to obtain focusedimage the most clearly, and this method is also referred to as the auto focusing method based on Digital Image Processing usually.This method can realize automatic focusing by software, promptly by fixing algorithm the information that the digital picture inherence comprises is carried out respective handling, obtains the control corresponding amount, and drive stepping motor drives camera lens and moves forward and backward, up to obtaining to focus on clearly image.Because passive method do not need extra distance-measuring equipment, therefore adopt the general volume of instrument of this method less, easy to carry, use flexibly, can be applicable in the optical system such as digital camera.Adopt passive method to realize that a self-focusing key issue is: how to design effective Image Definition and judge whether image is clear.A desirable Image Definition should have unbiasedness, and resulting best focus position should be corresponding with the maximal value of Image Definition, also should have noise resisting ability and less computational complexity preferably simultaneously.

According to optical imaging concept,, satisfy following relation between object distance u and the image distance v in focal distance f:

$\frac{1}{f}=\frac{1}{u}+\frac{1}{v}---\left(1\right)$

The ideal focusing situation is the light that each point on the object plane is sent, through still meeting at a bit after the lens refraction.It is all corresponding picture point of each object point.When the object plane of an object when the distance of lens is u, viewing plane is when the distance of lens is v, resulting image is focusedimage the most clearly, this moment, viewing plane was positioned on the focussing plane.If viewing plane has departed from focussing plane, the light that every bit sent on the object plane then can form a circle of confusion on viewing plane, just produced out-of-focus image, and image at this moment will thicken.If viewing plane is far away more apart from focussing plane, the image that is produced on viewing plane is also just fuzzy more so.If when having the object that a plurality of object distance u vary in size, and the object distance u of these a plurality of objects is much larger than the focal distance f of lens itself, the light launched of this a plurality of object can be approximately directional light when arriving lens so, and their image distance v can be approximately the focal distance f of lens, that is:

$v=\frac{\mathrm{uf}}{u-f}\≈f---\left(2\right)$

At this moment, if when viewing plane is positioned at the focal plane of lens, these a plurality of object imagings are the most clear, therefore can obtain these a plurality of objects focusedimage clearly simultaneously.Present focus method is the research of carrying out at this situation mostly.If but the object distance u that has an object in a plurality of objects at least compares can not be considered as infinity the time with focal distance f, after the light that a plurality of object sent different with lens distance was through the lens refraction, each object was also inequality through the image distance v behind the lens so.At this moment, no matter which position viewing plane is in, the picture rich in detail that all can not obtain all these objects simultaneously and generated, and present technology is less at the research of this situation.In addition, traditional Image Definition requires to satisfy unimodality, and in this case, well behaved Image Definition often unimodal situation can not occur, this is the different cause of image distance because of a plurality of objects, and Image Definition tends to a plurality of peak values occur in the image distance position of different objects.

Generally speaking, focus on image more accurately, its high fdrequency component is also just many more, and the edge details part is also just sharp keen more; And the image of out of focus, its high fdrequency component incurs loss, and it is level and smooth relatively that the marginal portion just seems, the tangible more image of out of focus degree, its high fdrequency component loss is also just many more, and the image border part is also just level and smooth more, and image is also just fuzzy more.Therefore, can carry out two-dimensional dct transform to image, with image by spatial transform to frequency domain, obtain two dimensional DCT coefficients, two dimensional DCT coefficients has embodied the frequency information of image preferably, wherein high-frequency information has mainly reflected the edge of image detail section, then can get the interpretational criteria of the energy of the high fdrequency component in the two dimensional DCT coefficients as image definition, thus the construct image sharpness evaluation function.Yet with regard to two dimensional DCT coefficients, be difficult to strictly distinguish which two dimensional DCT coefficients and belong to radio-frequency component, usual way is a DC coefficient of removing two dimensional DCT coefficients, and with the energy of ac coefficient interpretational criteria as image definition, the low-frequency component and the radio-frequency component of two dimensional DCT coefficients will be treated comparably like this, this just causes this method often can not satisfy the requirement of Image Definition, and then causes the inaccurate situation that focuses on easily.

Summary of the invention

Technical matters: the purpose of this invention is to provide self-adapting automatic focus method in a kind of digital camera, this method has defined an interested window area, the size of this window can be adjusted adaptively according to the resolution of image, to adapt to different photographing requests, when the distance of different objects and lens is inequality, can be with interested locking objects at this window area, thus interested object is realized automatic focus.

Technical scheme: because the object different apart from lens, also inequality through the distance of lens refraction pairing picture plane, back and lens, when the object distance u that has an object at least compares can not be considered as infinity the time with focal distance f, will occur focusing on when clear other object imagings with situation about thickening when one of them object imaging.And present auto focusing method is less at this Study on Problems.

In fact lens system can equivalence be a low-pass filtering system.Image when being in focus state, its radio-frequency component is abundant relatively, and the edge of image detail section is clear; And the image when being in out-of-focus appearance, its radio-frequency component incurs loss, and it is fuzzy that the edge of image detail section also just seems, and the out of focus degree is big more, and this phenomenon shows also just obviously more.From this angle, can choose the evaluation criterion of the energy of image medium-high frequency composition as sharpness, the construct image sharpness evaluation function, and after image carried out two-dimensional dct transform, the two dimensional DCT coefficients that obtains had just embodied the frequecy characteristic of image.Present method is normally removed the flip-flop of two dimensional DCT coefficients, with the energy of alternating component interpretational criteria as image definition, yet both comprised radio-frequency component in the alternating component, also comprise a large amount of low-frequency components simultaneously, this method is handled radio-frequency component and low-frequency component comparably, there is theoretic deficiency, and in practical operation, often makes focusing inaccurate.

For this reason, a kind of two dimensional DCT coefficients method of weighting is provided, this method is at first removed the DC coefficient of two-dimensional dct, then the low-frequency component and the radio-frequency component of two dimensional DCT coefficients are treated with a certain discrimination, give different weights with different frequency contents, give bigger weight with radio-frequency component, and give less weight low-frequency component.The frequency of DCT coefficient is high more, and the weight of being given is also just big more.Radio-frequency component can be highlighted significantly like this, and also have certain inhibiting effect for low-frequency component.Therefore, this method is better than traditional two-dimensional dct method.

Under normal conditions, people's notice all can concentrate on the zone line of image, and specifically, the people always gets used to and will be received within the zone line of image in own interested when taking pictures.When actual photographed scenery, if there is the different object of a plurality of object distances, and the object distance that has an object at least is compared can not be considered as infinity the time with focal length, so at this moment, the object of different object distances will have different image distances, therefore can not clearly demonstrate the object imaging of different object distances simultaneously at viewing plane.Must accept or reject to some extent this, provide the zone line of image has been solved this problem as the method for " emphasis " of entire image, specifically, with the focussing plane of the pairing focussing plane of zone line as entire image, wherein zone line is big or small most important, if window is excessive, might cause the shared zone of the interior interested object of window less than the shared zone of background around it, like this possibility of result of Ju Jiaoing can with around background focus on, and this moment interested object may be in out-of-focus appearance; If window is too small, zone that then may the lost part attention object.Therefore, need be to the window size consideration of compromising.Consider the requirement of required different resolution image in addition, provide a kind of for this reason and can regulate the window area of size adaptively according to required resolution.Specifically, the row and column of two-dimentional original image is carried out trisection respectively, the intersecting area of 1/3 center section of getting row and column then respectively is as interested window, so the area of window accounts for 1/9 of entire image area, at this moment the size of window can be done adjustment adaptively along with the resolution of image as can be seen, when photographic images, can so just can utilize follow-up Image Definition and search strategy only interested target to be carried out automatic focus with interested target lock-on at middle window.

A kind of new Image Definition is provided then.To the subimage of image middle window, utilize Image Definition to judge its sharpness.After subimage carried out two-dimensional dct transform, obtain two dimensional DCT coefficients,, for this reason, provide a kind of weighting two dimensional DCT coefficients method because the low-frequency component of two dimensional DCT coefficients is different to the influence of image definition with radio-frequency component.

Self-adapting automatic focus method in the digital camera of the present invention the steps include:

A, gather original colorful image with digital camera;

B, according to the resolution sizes of original image, adopt the method for self-adapting window that the colored zone line of original image is sheared out as subimage;

C, the subimage of colour is converted to gray scale image;

D, grayscale sub-image is carried out two-dimensional dct transform, obtain two dimensional DCT coefficients;

E, two dimensional DCT coefficients is carried out according to the size of its frequency adaptive weighted, the computed image sharpness evaluation function;

F, according to Image Definition, adopt a kind of the moving of search strategy control step motor of whole process, search out focusedimage clearly.

Wherein the concrete steps of the method for self-adapting window are: the resolution sizes of at first calculating original image, according to the resolution of original image the row and column of two-dimentional original image is carried out trisection respectively, get zone that the center section of row and column intersects then respectively as interested window, so the area of window accounts for 1/9th sizes of entire image area, at last the image in this window is sheared from original image as subimage.

Wherein weighting two dimensional DCT coefficients method in the Image Definition in the optics automatic focus the steps include:

1.) establish I (x, y) expression resolution be M * N gray level image pixel (then the two-dimensional dct transform of gray level image is defined as for x, gray-scale value y):

$F(u,v)=C\left(u\right)C\left(v\right)\underset{m=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}I(x,y)\cos \frac{\mathrm{\π}(2m+1)u}{2M}\cos \frac{\mathrm{\π}(2n+1)v}{2N}$

Wherein u and v represent line frequency and the row frequency in the frequency domain respectively, F (u, v) be called image I (x, two dimensional DCT coefficients y), wherein C (u) and C (v) define by following formula respectively:

$C\left(u\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{M}}& u=0\\ \sqrt{\frac{2}{M}}& 1\≤u\≤M-1\end{array}\right.,C\left(v\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{N}}& v=0\\ \sqrt{\frac{2}{N}}& 1\≤v\≤N-1\end{array}\right.$

2.) remove the DC coefficient of two dimensional DCT coefficients, remaining other coefficients then are ac coefficient, according to the size of two dimensional DCT coefficients frequency, ac coefficient are carried out the adaptive weighted computed image sharpness evaluation function that comes, and computing formula is as follows:

$E_1=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)F{(u,v)}^2\right]$

$E_2=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)\right|F(u,v)\left|\right]$

Wherein, E ₁And E ₂Square energy and the absolute value energy in the presentation video sharpness evaluation function respectively, M and N represent line number and the columns in the two dimensional DCT coefficients respectively, u and v represent line frequency and the row frequency in the frequency domain respectively, and u and v are not zero simultaneously.

Wherein Quan Cheng search strategy is to search for focusedimage the most clearly according to Image Definition.Because the situation of multimodal may appear in Image Definition, if so adopt traditional search strategy may converge to local peaking, and the global search strategy can address this problem, its method is: at first adopt bigger step-length to carry out global search, and write down the evaluation function value in each when search step, obtain the situation of change of evaluation function curve, by stepper motor camera lens is moved to peaked last step-length position then, carry out the long precise search of small step at peaked front and back position, till searching clearly focusedimage.This searching method is not only applicable to the situation of multimodal, simultaneously unimodal situation is suitable for too.

Beneficial effect: the invention has the beneficial effects as follows, if when photographic images, there are a plurality of objects different apart from camera lens, so only with interested locking objects at middle window, occupy big zone at middle window, to carry out automatic focus to it, obtain the picture rich in detail of attention object.Adopt the middle window method also to reduce computation complexity effectively simultaneously, shortened the required time that focuses on.

Another beneficial effect of the present invention is, two kinds of methods calculating weighting DCT coefficient energy are provided, and better met the requirement of Image Definition, make focus on judge more accurate.

Description of drawings

Fig. 1 is the schematic diagram of a plurality of object optical imageries.

Fig. 2 is that the present invention realizes self-focusing control flow synoptic diagram.

Wherein have: the picture A ' of the first object A, the second object B, first object, the picture B ' of second object, focal distance f.

Embodiment

Self-adapting automatic focus method the steps include: in the digital camera

A, gather original colorful image with digital camera;

B, according to the resolution sizes of original image, adopt the method for self-adapting window that the colored zone line of original image is sheared out as subimage;

C, the subimage of colour is converted to gray scale image;

D, grayscale sub-image is carried out two-dimensional dct transform, obtain two dimensional DCT coefficients;

E, two dimensional DCT coefficients is carried out according to the size of its frequency adaptive weighted, the computed image sharpness evaluation function;

F, according to Image Definition, adopt a kind of the moving of search strategy control step motor of whole process, search out focusedimage clearly.

Wherein the concrete steps of the method for self-adapting window are: the resolution sizes of at first calculating original image, according to the resolution of original image the row and column of two-dimentional original image is carried out trisection respectively, get zone that the center section of row and column intersects then respectively as interested window, so the area of window accounts for 1/9th sizes of entire image area, at last the image in this window is sheared from original image as subimage.

If I (x, y) expression resolution be M * N subimage pixel (then the two-dimensional discrete dct transform of subimage is defined as for x, gray-scale value y):

$F(u,v)=C\left(u\right)C\left(v\right)\underset{m=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}I(x,y)\cos \frac{\mathrm{\π}(2m+1)u}{2M}\cos \frac{\mathrm{\π}(2n+1)v}{2N}---\left(3\right)$

Wherein C (u) and C (v) define by following formula respectively:

$C\left(u\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{M}}& u=0\\ \sqrt{\frac{2}{M}}& 1\≤u\≤M-1\end{array}\right.,C\left(v\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{N}}& v=0\\ \sqrt{\frac{2}{N}}& 1\≤v\≤N-1\end{array}\right.$

F (u, (x, two dimensional DCT coefficients y) are removed the DC coefficient of two dimensional DCT coefficients then v) to be called image I, remaining other coefficients then are ac coefficient, in ac coefficient, existing radio-frequency component also has low-frequency component simultaneously, and different frequency contents is different to the sharpness influence of image, for this reason, provide a kind of and given the method for different weights with different frequency contents, the weight that the DCT coefficient that frequency is high is more given is also just big more, that is:

$E_1=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)F{(u,v)}^2\right]---\left(4\right)$

Wherein, frequency component u and v are not zero simultaneously.From formula (4) as can be seen, when frequency was high more, the weight of the high-frequency energy of being given was also just big more, this more meets the requirement of Image Definition, and what consider formula (4) employing is a square energy, and required operand is higher, a kind of method of absolute value energy also is provided for this reason:

$E_2=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)\right|F(u,v)\left|\right]---\left(5\right)$

Wherein, frequency component u and v are not zero simultaneously.From formula (5), as can be seen, behind the employing absolute calculation energy, replace square operation, under the prerequisite that guarantees the sharpness evaluation function performance, can reduce operand.

Realize self-focusing key step as shown in Figure 2, at first gather original image, size according to original image resolution, the row and column of the original image of two dimension is carried out trisection respectively, get the part that intersects in the middle of the row and column, and the regional shear of row and column intersection come out as middle window, subsequent operation will only be handled the subimage of middle window.

If the resolution of image is higher, can carry out suitable sampling to image according to the size of resolution, guaranteeing can to reduce data volume under the self-focusing prerequisite of realization, convert coloured image to gray level image then, conversion formula is as follows:

$I=\frac{1}{3}(R+G+B)---\left(6\right)$

Wherein, R, G and B represent redness, green and the blue component of coloured image respectively, and I is the gray level image after changing, and each gray-scale value is represented by 8bits.Then gray level image is carried out two-dimensional dct transform, obtain two dimensional DCT coefficients.

According to formula (4) or (5), computed image sharpness evaluation function value because Image Definition tends to occur the situation of multimodal, can adopt a kind of search strategy method of whole process for this reason then.This searching method at first adopts bigger step-length global search one time, and document image sharpness evaluation function curve, then camera lens is moved to the peaked last position of function and near maximal value, carry out little step length searching, till searching image definition criterion function extreme point, can solve the peaked problem of search under the situation that a plurality of peak values occur like this.This moment, pairing image was focusedimage clearly.

Claims (3)

1. self-adapting automatic focus method in the digital camera is characterized in that the steps include:

A, gather original colorful image with digital camera;

B, according to the resolution sizes of original image, adopt the method for self-adapting window that the colored zone line of original image is sheared out as subimage;

C, the subimage of colour is converted to gray scale image;

D, grayscale sub-image is carried out two-dimensional dct transform, obtain two dimensional DCT coefficients;

E, two dimensional DCT coefficients is carried out according to the size of its frequency adaptive weighted, the computed image sharpness evaluation function;

F, according to Image Definition, adopt a kind of the moving of search strategy control step motor of whole process, search out focusedimage clearly.

2. self-adapting automatic focus method in the digital camera according to claim 1, it is characterized in that wherein the concrete steps of the method for self-adapting window are: the resolution sizes of at first calculating original image, according to the resolution of original image the row and column of two-dimentional original image is carried out trisection respectively, get zone that the center section of row and column intersects then respectively as interested window, so the area of window accounts for 1/9th sizes of entire image area, at last the image in this window is sheared from original image as subimage.

3. self-adapting automatic focus method in the digital camera according to claim 1 is characterized in that in the wherein optics automatic focus weighting two dimensional DCT coefficients method in the Image Definition, the steps include:

1.) establish I (x, y) expression resolution be M * N gray level image pixel (then the two-dimensional discrete dct transform of gray level image is defined as for x, gray-scale value y):

$F(u,v)=C\left(u\right)C\left(v\right)\underset{m=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{n=0}{\overset{N-1}{\mathrm{\Σ}}}I(x,y)\cos \frac{\mathrm{\π}(2m+1)u}{2M}\cos \frac{\mathrm{\π}(2n+1)v}{2N}$

Wherein u and v represent line frequency and the row frequency in the frequency domain respectively, F (u, v) be called image I (x, two dimensional DCT coefficients y), wherein C (u) and C (v) define by following formula respectively:

$C\left(u\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{M}}& u=0\\ \sqrt{\frac{2}{M}}& 1\≤u\≤M-1\end{array}\right.,C\left(v\right)=\left\{\begin{array}{cc}\frac{1}{\sqrt{N}}& v=0\\ \sqrt{\frac{2}{N}}& 1\≤v\≤N-1\end{array}\right.$

2.) remove the DC coefficient of two dimensional DCT coefficients, remaining other coefficients then are ac coefficient, according to the size of two dimensional DCT coefficients frequency, ac coefficient are carried out the adaptive weighted computed image sharpness evaluation function that comes, and computing formula is as follows:

$E_1=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)F{(u,v)}^2\right]$

$E_2=\underset{u=0}{\overset{M-1}{\mathrm{\Σ}}}\underset{v=0}{\overset{N-1}{\mathrm{\Σ}}}\left[(u+v)\right|F(u,v)\left|\right]$

Wherein, E ₁And E ₂Square energy and the absolute value energy in the presentation video sharpness evaluation function respectively, M and N represent line number and the columns in the two dimensional DCT coefficients respectively, u and v represent line frequency and the row frequency in the frequency domain respectively, and u and v are not zero simultaneously.