CN103345756B - Microscopical Atomatic focusing method, device and electronic equipment in a kind of urine sediments analyzer - Google Patents

Abstract

The invention discloses microscopical Atomatic focusing method, device and electronic equipment in a kind of urine sediments analyzer, described method is: obtains in different focusings respectively and takes the photograph image in advance accordingly；It is loaded into these source images；Respectively these images are carried out NSCT decomposition, and produces sub-band coefficients (image)；Calculate this image low frequency, the energy of high frequency coefficient and ratio；Ratio is utilized to obtain focus estimated value as reference data；Focus estimated value is utilized constantly to adjust focusing position；Repeat said process, determine the optimal focusing position of present image.The present invention proposes a kind of microscopical Atomatic focusing method decomposed based on NSCT, can be efficiently applied to microscopical auto-focusing in urine sediments analyzer.Present invention can ensure that the microscope of urine sediments analyzer carries out auto-focusing and makes display image the most clearly, substantially increase the reliability and sensitivity of focusing system.

Description

Microscopical Atomatic focusing method, device and electronics in a kind of urine sediments analyzer Equipment

Technical field

The present invention relates to a kind of microscopical Atomatic focusing method, particularly to a kind of based on urine sediments analyzer high-precision Spend microscopical Atomatic focusing method, device and electronic equipment.

Background technology

Along with deepening continuously that urine sediments analyzer and computer technology combine, the microscope as its core technology is automatic Focus algorithm has become as an important research direction in computer vision.The urine sediment image pair of clear profile can be obtained In medical analysis afterwards, diagnosis etc. is particularly significant, also has influence on the degree of accuracy of instrument.

Check the visible component in urine all to use under microscope clinically and be manually analyzed differentiating.Auto-focusing one side Face can alleviate the labor intensity of operator, operator is reduced or avoided because of the subjective error caused of repeatedly focusing.On the other hand, It eliminates the focusing action of complexity, greatly facilitates operator.Comparing common imaging system, the depth of focus of microscope objective is Extremely limited, and along with the increase of amplification, its depth of focus can constantly reduce.Especially under high x Microscope Objective, Only those structures near focussing plane or its are only clearly, can relatively obscure away from the structure of focal plane and even may not be used Seeing, the phenomenon that system imaging quality is limited by the depth of focus of high power objective and declines also can be extremely serious.Therefore, Urine sediments analyzer is shown For the acquisition of micro-image, controlling microscopical auto-focusing just becomes urine Urine sediments analyzer divide to obtain micro-image the most clearly The premise of analysis system normal assay.

The focusing mode being applied to microscope autofocus system at present mostly is passive mode.This mode is to use image Treatment technology determines whether sample image focuses.This image processing techniques is to analyze the quality of image according to image, from And obtain current image formation state, and the evaluation function value of the image of diverse location is calculated by focusing evaluation function, look for Go out the image space that evaluation function value is maximum, complete focus operation.

The various image evaluation methods having pointed out, refer to shown in Fig. 1.One class is the evaluation methodology of time domain, directly with sharp Change operator image is processed, then take the data after process as judgment basis, there is feature succinct, quick, but right Noise is more sensitive, common are Gradient algorithm, laplacian evaluation algorithms etc., can obtain relation as shown in Figure 2 bent Line；Another kind of is the evaluation methodology of frequency domain, mainly uses the method such as Fourier transformation, wavelet transformation, by analyzing the frequency of image Rate composition carrys out the definition of evaluation image, can obtain relation curve as shown in Figure 3.

Preferably sharpness evaluation function should meet unimodality and unbiasedness, in actual image acquisition, owing to making an uproar The impact of the factors such as the ambient interferences of sound, the dust of sample surface and sample, causes evaluation function multiple local maximums occur Value, and maximum peak slip chart picture position the most clearly, have influence on pattern detection result accuracy.Have been presented for various side at present Method eliminates the limitation extreme value of focusing curve, but major part is not of universal significance, and in some cases, no matter which kind of uses Focusing evaluation function, all may cause the failure of auto-focusing.Thus eliminate multimodal and ambient interferences, build one reliably, soon Fast and high-precision microscope autofocus system has great importance.

Summary of the invention

Present invention aims to urine sediments analyzer and a kind of image definition evaluation under microscopic field is provided Algorithm, be can ensure that microscope focus operation completes after, the image on display screen be correct the most clearly.

Microscope Atomatic focusing method based on NSCT in a kind of urine sediments analyzer, this focusing process includes following step Rapid:

A1 takes the photograph image X in advance X different object distances acquisition the most continuously and opens, and taking the photograph image Px in advance for each all has accordingly X object distance position；

A2 is loaded into described source images；

A3 continuous print X is opened take the photograph in advance image carry out N level NSCT decompose, every image obtainsIndividual high-frequency sub-band coefficient With 1 low frequency sub-band coefficient；

A4 utilizes sub-band coefficients structure based on the Laplce's energy improved and function, low frequency sub-band coefficient Laplce's energy The ratio of amount and functional value and high-frequency sub-band coefficient Laplce's energy and functional value is sharpness evaluation function value；

Ratio described in A5 utilization obtains focus estimated value as reference data；

A6 utilizes focus estimated value constantly to adjust focusing position；

A7 repeats said process, determines the optimal focusing position of present image.

Described method, described step A3, method particularly includes: initially with the tower bank of filters of non-lower sampling to input Image F carries out multi-resolution decomposition, obtains low frequency sub-band coefficient and high-frequency sub-band coefficient；Then the pyramidal structure obtained is entered The multi-direction decomposition of row non-lower sampling directional filter banks, obtains the sub-band coefficients of different scale, different directions:

$\{C_N^L(i,j),C_{n,k}^H(i,j)\},1\≤n\≤N,k=\mathrm{1,2},\·\·\·,2^{k_n}$

Wherein, N is Decomposition order,Represent low frequency (L) sub-band coefficients,Represent on n yardstick k direction Position is at (i, each high frequency (H) directional subband coefficient j), k_nFor the Directional Decomposition progression under yardstick n,Number for directional subband Mesh.

Described method, described step A4-A6, method particularly includes: at NSCT transform domain, the La Pula of described improvement This (ML) and SML function definition are as follows:

ML_{N, k}(i, j)=| 2C_{N, k}(i, j)-C_{N, k}(i-1, j)+

C_{N, k}(i+1, j) |+| 2C_{N, k}(i, j)-

C_{N, k}(i, j-1)+C_{N, k}(i, j+1) |

${\mathrm{SML}}_{n,k}=\underset{i}{\mathrm{\Σ}}\underset{j}{\mathrm{\Σ}}{\left[{\mathrm{ML}}_{n,k}(i,j)\right]}^2$

Wherein, C_{N, k}(i j) is image sub-band coefficients after NSCT decomposes；

Low frequency sub-band coefficient and Laplce's energy of high-frequency sub-band coefficient and function (SML) is obtained at NSCT transform domain:

$\left\{\begin{array}{c}{E}^L={\mathrm{SML}}_N\\ E_{n,k}^H=[{\mathrm{SML}}_{\mathrm{1,1}},{\mathrm{SML}}_{\mathrm{2,1}},\·\·\·,{\mathrm{SML}}_{n,k}]\end{array}\right.$

High-frequency sub-band coefficient energy according to different directions, obtains every grade of high-frequency sub-band coefficient energy:

$E_n=\frac{1}{2^n}\mathrm{\Σ}{E}_{n,k}$

The gross energy of high-frequency sub-band coefficient is obtained by following formula:

$E^H=\mathrm{\α}{E_1}^H+(1-\mathrm{\α})\frac{\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{E}_n^H}{N}$

In conjunction with the Variation Features of both high and low frequency sub-band coefficients (image) energy, calculate sharpness evaluation function value:

$h=\frac{E^L}{E^H}$

It is principle to the maximum with the sharpness evaluation function value of image, contrasts the clear of previous width or a few width image focusing position Degree evaluation function value, estimating the optimal focusing position of present image, then doing small adjustment near estimation position, until obtaining Take focus image the most clearly.

The present invention also provides for a kind of microscope automatic focusing mechanism, and this automatic focusing mechanism includes:

Image capture device based on CMOS, takes the photograph image in order to shoot the pre-of microscope different focus point；

USB interface, is used for connecting image capture device and computer, is the passage of image transmitting；

Computer, is used for analyzing, storing source images, produces focus estimated value to determine camera lens according to object selection value Focusing position for sample；

Single-chip microcomputer, receives the instruction from computer, and drive stepping motor adjusts；

Stepper motor driver, by Single-chip Controlling, is used for driving microscope camera lens, so that focus lens to move to prediction Focus lens position；

Wherein, this computer utilizes the sharpness evaluation function value of image to estimate the optimal of present image with corresponding object distance Focusing object distance.

Described microscope automatic focusing mechanism, also includes that auto exposure parameter determines and control unit, and it is arranged at institute State in computer, in order to according to the environment captured by this image capture device, to determine time of exposure when subject shoots, light Circle size and at least one person of ISO value.

The present invention also provides for a kind of electronic imaging device using any of the above-described described method.

The invention have the characteristics that:

1. the present invention proposes a kind of microscopical Atomatic focusing method decomposed based on NSCT, can be efficiently applied to urine heavy Microscopical auto-focusing in slag analyser.

2. present invention can ensure that the microscope of urine sediments analyzer carries out auto-focusing and makes display image the most clearly, greatly Improve greatly the reliability and sensitivity of focusing system.

3. the algorithm in the present invention realizes simple, and kernel software algorithm part only needs a PC just can be automatically performed.

Accompanying drawing explanation

Fig. 1 prior art utilizes 2 images to be evaluated the schematic diagram of focusing；

The relation schematic diagram of the evaluation result that Fig. 2 prior art is calculated in time domain and object distance；

The relation schematic diagram of the evaluation result that Fig. 3 prior art is calculated at frequency domain and object distance；

The principle schematic of Fig. 4 present invention；

The evaluation result of Fig. 5 present invention and the relation schematic diagram of object distance；

The auto-focusing of Fig. 6 embodiment of the present invention controls the block diagram representation of circuitry configuration；

Wherein, reference:

300 microscope automatic focusing control apparatus, 310 auto-focusing microscopes, 320 image capture devices, 330USB connects Mouthful, 340 computers, 350 single-chip microcomputers, 360 stepper motor drivers；

Detailed description of the invention

Embodiment 1

For the basic operation workflow of the present invention can be clearly described, refer to shown in Fig. 4, different at X continuously first respectively Object distance acquisition is taken the photograph image X in advance and is opened, and taking the photograph image Px in advance for each all has corresponding X object distance position；X=3 in the diagram.It is loaded into pre- Take the photograph image；Continuous print X is opened take the photograph in advance image carry out N level NSCT decompose, every image obtainsIndividual high-frequency sub-band coefficient (figure Picture) and 1 low frequency sub-band coefficient (image)；N=3 in the diagram.After this decomposing program, sub-band coefficients (image) contains source The marginal information that image is abundant, utilizes sub-band coefficients (image) structure based on the Laplce's energy improved and function, low frequency Band coefficient Laplce's energy and functional value are with the ratio of high-frequency sub-band coefficient (image) Laplce's energy and functional value Sharpness evaluation function value, the success rate of auto-focusing will be substantially improved.

In the diagram, as a example by X=3, obtain respectively and first take the photograph image P1 in advance, second image P2 in advance, the 3rd image P3 in advance. Subsequently, these images (P is calculated₁～P₃) low frequency, Laplce's energy of high-frequency signal and the ratio of functional value；So just can obtain To the object distance relation corresponding thereto of source images as shown in Figure 5.Compared to the relation curve obtained by prior art, Fig. 5 has There is more specific focusing position, and show more preferable noise immunity and unimodality.The success rate of auto-focusing will be substantially improved. Last further according to these images (P₁～P₃) sharpness evaluation function value object distance relation corresponding thereto, with result maximum For principle, determine the focusing object distance that the maximum of sharpness evaluation function value is corresponding.

In actual applications, refer to shown in Fig. 6, its be the embodiment of the present invention auto-focusing control equipment circuit join The block diagram put.The microscope automatic focusing control apparatus 300 of the present invention includes: auto-focusing microscope 310, image acquisition set Standby (based on CMOS) 320, USB interface 330, computer 340, single-chip microcomputer 350 and stepper motor driver 360.,

The image capture device 320 of this device is connected with computer 340, in order to shooting environmental and sample by USB interface 330 This imaging obtains pre-image of taking the photograph, and will take the photograph image transmitting in advance to computer 340.When reality performs, auto exposure parameter meeting Automatically suitably adjustment is made according to shooting environmental.Computer 340 receives the pre-of image capture device 320 transmission and takes the photograph image, should Take the photograph image in advance preserve and be converted into digital signal；Utilize this digital signal that this pre-image of taking the photograph is carried out NSCT conversion, obtain source figure 1 low frequency sub-band coefficient of picture and multiple high-frequency sub-band coefficient, calculate every image low frequency sub-band coefficient, high-frequency sub-band coefficient Laplce's energy of (image) and the ratio of functional value are worth to sharpness evaluation function value, clear with a width or a few width image Degree evaluation function value compares, and obtains homologue away from relation curve, for search by hill climbing；Simultaneously according to each image definition Evaluation function value output control command with instrumentality away from, this control command is exported to single-chip microcomputer 350 by serial ports.Single-chip microcomputer 350 It is connected with computer 340 serial ports, rotates to control stepper motor driver in order to receive the above-mentioned control command of computer 340. Motor often rotates once, and microscope 310 adjusts object distance towards the direction that sharpness evaluation function value is big；Again by image acquisition Equipment 320 shoots new image, and is transferred to computer 340 and repeats above-mentioned analysis.

Repeating the step described in epimere, according to previous width or a few width Image Definition value, using climbs the mountain searches Rope algorithm, calculates the sharpness evaluation function value of current position image, until the sharpness evaluation function value of new image is more than The functional value of the most all images, makes this microscope camera lens 310 stop in this place, the focusing position of this i.e. this microscope 310, by This just completes auto-focusing.Because the autofocus system of the present embodiment is according to the image gained of display on computer 340 Result carry out focus operation, it is thus ensured that after focus operation completes, the image being projeced on computer 340 screen is correct Clearly.

Embodiment 2

The present embodiment describes Laplce's energy and the function of above-mentioned improvement in detail.

Image capture device by the image transmitting that photographed to computer, being given subsequent algorithm by computer and carry out frame by frame Process.Need exist for explanation is original each two field picture to have carried out 1/4th samplings (such as: original graph in the present invention As size is 800 × 600, it is 200 × 150 after sampling), so can improve follow-up calculation on the premise of not affecting Detection results The arithmetic speed of method.

Initially with the tower bank of filters of non-lower sampling (NSP), input picture F is carried out multi-resolution decomposition, obtain low frequency Band coefficient (image) and high-frequency sub-band coefficient (image)；Then the pyramidal structure obtained is carried out non-lower sampling trend pass filtering Device group (NSDFB) multi-direction decomposition, obtains the sub-band coefficients of different scale, different directions:

$\{C_N^L(i,j),C_{n,k}^H(i,j)\},1\≤n\≤N,k=\mathrm{1,2},\·\·\·,2^{k_n}$

Wherein, N is Decomposition order,Represent low frequency (L) sub-band coefficients,Represent on n yardstick k direction Position is at (i, each high frequency (H) directional subband coefficient j), k_nFor the Directional Decomposition progression under yardstick n,Number for directional subband Mesh.Coefficient magnitude keeps consistent with original image, therefore can regard the sub-band coefficients of NSCT transform domain as image.

Then the Laplce's energy and the function (Sum-modified laplacian, SML) that define improvement carry out phenogram The energy value of picture.At NSCT transform domain, the Laplce (ML) of improvement and SML function definition are as follows:

ML_{N, k}(i, j)=| 2C_{N, k}(i, j)-C_{N, k}(i-1, j)+

C_{N, k}(i+1, j) |+| 2C_{N, k}(i, j)-

C_{N, k}(i, j-1)+C_{N, k}(i, j+1) |

${\mathrm{SML}}_{n,k}=\underset{i}{\mathrm{\Σ}}\underset{j}{\mathrm{\Σ}}{\left[{\mathrm{ML}}_{n,k}(i,j)\right]}^2$

Wherein, C_{N, k}(i j) is image sub-band coefficients (image) after NSCT decomposes.

Low frequency sub-band coefficient and Laplce's energy of high-frequency sub-band coefficient (image) and function is obtained at NSCT transform domain (SML):

$\left\{\begin{array}{c}{E}^L={\mathrm{SML}}_N\\ E_{n,k}^H=[{\mathrm{SML}}_{\mathrm{1,1}},{\mathrm{SML}}_{\mathrm{2,1}},\·\·\·,{\mathrm{SML}}_{n,k}]\end{array}\right.$

High-frequency sub-band coefficient (image) energy according to different directions, obtains every grade of high-frequency sub-band coefficient (image) energy:

$E_n=\frac{1}{2^n}\mathrm{\Σ}{E}_{n,k}$

The gross energy of high-frequency sub-band coefficient (image) is obtained by following formula:

$E^H=\mathrm{\α}{E_1}^H+(1-\mathrm{\α})\frac{\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{E}_n^H}{N}$

In conjunction with the Variation Features of both high and low frequency sub-band coefficients (image) energy, calculate sharpness evaluation function Value:

$h=\frac{E^L}{E^H}$

It is principle to the maximum with the sharpness evaluation function value of image, contrasts the clear of previous width or a few width image focusing position Degree evaluation function value, estimating the optimal focusing position of present image, then doing small adjustment near estimation position, until obtaining Take focus image the most clearly.

The tower wave filter of the non-lower sampling (NSP) that described NSCT uses is one group of two passage non-lower sampling wave filter.Often The bank of filters that one-level is used is that the wave filter being used upper level is by sampling matrix $D=2I=\left[\begin{array}{cc}2& 0\\ 0& 2\end{array}\right]$ Carry out sampling Arrive.Image, after N level non-lower sampling QMF compression, can obtain N+1 the subband system with source images with same size size Number (image).

The non-lower sampling anisotropic filter (NSDFB) that described NSCT is used is a class frequency response characteristic for fan-shaped shape The two non-lower employing bank of filters of passage of shape.In order to obtain more Directional Decomposition, NSCT is also by employing two-way repeatedly Road directional filter banks travel direction filtering realizes.The wave filter that every one-level uses is the wave filter by using upper level By sampling matrix $D=\left[\begin{array}{cc}1& 1\\ 1& -1\end{array}\right]$ Sampling obtains.Can get 2 after sub-band coefficients (image) carries out k level decomposition under certain yardstick^kIndividual The sub-band coefficients (image) identical with original input picture size.Image obtains 1 low frequency sub-band after N level NSCT is decomposed Coefficient (image) andIndividual high-frequency sub-band coefficient (image).

Except above-described embodiment, it is to utilize this microscope mobile equally that the Atomatic focusing method of the present invention can also be used for other 310, and obtain image in each lens location and calculate the sharpness evaluation function value of this image, then compare to take Obtain maximum image sharpness evaluation function value, and make this microscope 310 camera lens be positioned at the mode of opposite position.The most existing Universe searches (Global Search) method, Fei Shi searches the focusing modes such as (Fibonacci Search) method.

It should be appreciated that for those of ordinary skills, can be improved according to the above description or be converted, And all these modifications and variations all should belong to the protection domain of claims of the present invention.

Claims (6)

1. microscope Atomatic focusing method based on NSCT in a urine sediments analyzer, it is characterised in that this focusing process bag Include the following step:

A1 takes the photograph image X in advance X different object distances acquisition the most continuously and opens, and takes the photograph image P in advance for each_XAll there is corresponding X thing Away from position；

Continuous print X described in A2 loading A1 opens and takes the photograph image in advance；

A3 continuous print X is opened take the photograph in advance image carry out N level NSCT decompose, every image obtainsIndividual high-frequency sub-band coefficient and 1 Low frequency sub-band coefficient；

A4 utilizes Laplce's energy and the function SML of sub-band coefficients structure improvement_{N, k}, wherein subscript k represents the side that NSCT decomposes To number, the low frequency sub-band coefficient obtained at NSCT transform domain and Laplce's energy of the improvement of high-frequency sub-band coefficient and function SML is respectively E^LWithWherein subscript k represents the direction number that NSCT decomposes, according to the high-frequency sub-band coefficient energy of different directions Amount, obtains every grade of high-frequency sub-band coefficient ENERGY E_n, by first order high-frequency sub-band coefficient ENERGY E₁ ^HWeights be α, other is at different levels high Frequently the weights of the average of sub-band coefficients energy are that the mode of 1-α is weighted gross energy E^H, the improvement of low frequency sub-band coefficient Laplce's energy and functional value E^LLaplce's energy of the improvement with high-frequency sub-band coefficient and functional value E^HRatio be Sharpness evaluation function value；

Ratio described in A5 utilization obtains focus estimated value as reference data；

A6 utilizes focus estimated value constantly to adjust focusing position；

A7 repeats said process, determines the optimal focusing position of present image.

Method the most according to claim 1, it is characterised in that described step A3, method particularly includes: under non- Tower bank of filters of sampling carries out multi-resolution decomposition to input picture F, obtains low frequency sub-band coefficient and high-frequency sub-band coefficient；Then The pyramidal structure obtained is carried out the multi-direction decomposition of non-lower sampling directional filter banks, obtains different scale, different directions Sub-band coefficients:

$\begin{array}{cc}\{C_N^L(i,j),C_{n,k}^H(i,j)\}& 1\≤n\≤N,k=1,2,...,2^{k_n}\end{array}$

Wherein, N is Decomposition order,Represent low frequency sub-band coefficient,Represent on n yardstick k direction position (i, J) each high frequency direction sub-band coefficients, k_nFor the Directional Decomposition progression under yardstick n,Number for directional subband.

Method the most according to claim 1, it is characterised in that described step A4-A6, method particularly includes: become at NSCT Changing territory, the Laplce ML of improvement and Laplce's energy of improvement and function SML definition are as follows:

ML_{N, k}(i, j)=| 2C_{N, k}(i, j)-C_{N, k}(i-1, j)+

C_{N, k}(i+1, j) |+| 2C_{N, k}(i, j)-

C_{N, k}(i, j-1)+C_{N, k}(i, j+1) |

${\mathrm{SML}}_{n,k}=\underset{i}{\Σ}\underset{j}{\Σ}{\[{\mathrm{ML}}_{n,k}(i,j)\]}^2$

Wherein, C_{N, k}(i j) is image sub-band coefficients after NSCT decomposes；

Laplce's energy and the function SML of the improvement of low frequency sub-band coefficient and high-frequency sub-band coefficient is obtained at NSCT transform domain:

$\left\{\begin{array}{c}{E}^L=SM{L}_N\\ E_{n,k}^H=\[{\mathrm{SML}}_{1,1},{\mathrm{SML}}_{2,1},...,{\mathrm{SML}}_{n,k}\]\end{array}\right.$

High-frequency sub-band coefficient energy according to different directions, obtains every grade of high-frequency sub-band coefficient energy:

$E_n=\frac{1}{2^n}{\mathrm{\ΣE}}_{n,k}$

The gross energy of high-frequency sub-band coefficient is obtained by following formula:

$E^H={\mathrm{\αE}}_1^H+(1-\mathrm{\α})\frac{\underset{n=1}{\overset{N}{\Σ}}{E}_n^H}{N}$

α in above formula is the weight coefficient of first order high-frequency sub-band coefficient and other high-frequency sub-band Coefficient Means at different levels, in conjunction with two The Variation Features of person's high and low frequency sub-band coefficients energy, calculates sharpness evaluation function value:

$h=\frac{E^L}{E^H}$

Being principle to the maximum with the sharpness evaluation function value of image, the definition contrasting previous width or a few width image focusing position is commented Valency functional value, estimates the optimal focusing position of present image, then does small adjustment near estimation position, until obtaining Focus image clearly.

4. according to the microscope automatic focusing mechanism of the arbitrary described method of claim 1-3, it is characterised in that this auto-focusing Device includes:

Image capture device based on CMOS, takes the photograph image in order to shoot the pre-of microscope different focus point；

USB interface, is used for connecting image capture device and computer, is the passage of image transmitting；

Computer, is used for analyzing, storing source images, according to object selection value produce focus estimated value with determine camera lens for The focusing position of sample；

Single-chip microcomputer, receives the instruction from computer, and drive stepping motor adjusts；

Stepper motor driver, by Single-chip Controlling, is used for driving microscope camera lens, so that focus lens to move to prediction focusing Lens location；

Wherein, this computer utilizes the sharpness evaluation function value of image to estimate the optimal focusing of present image with corresponding object distance Object distance.

Microscope automatic focusing mechanism the most according to claim 4, it is characterised in that also include that auto exposure parameter determines With control unit, it is arranged in described computer, in order to according to the environment captured by this image capture device, to determine to be taken At least one person of time of exposure, aperture size and ISO value during thing shooting.

6. the electronic imaging device using the arbitrary described method of claim 1-3.