CN108364274A - The lossless clear reconstructing method of optical imagery under micro-nano-scale - Google Patents
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Abstract
The present invention provides a kind of lossless clear reconstructing method of optical imagery under micro-nano-scale, is related to digital image processing techniques field.This method obtains two images respectively as source images and target image by changing the distance between video camera and object first, then calculate again the clear image corresponding to source images and target image to target image the optical energy propagation time, and then obtain clear image, finally calculate separately target image and the average gradient and image entropy of clear image again, come measure reconstruct clear image readability.The lossless clear reconstructing method of optical imagery under micro-nano-scale provided by the invention, clear image is reconstructed with optical energy propagation equation dynamic lossless, avoid calculating process of the tradition using complexity when solving Deconvolution Method reconstruct clear image, the accurate surveying to target signature under micro-nano vision is realized, the research restored for image in micro-nano vision provides theoretical research foundation.
Description
Technical field
The present invention relates under digital image processing techniques field more particularly to a kind of micro-nano-scale optical imagery it is lossless
Clear reconstructing method.
Background technology
Optical observation have it is real-time, lossless to sample, therefore the environment adaptation advantages such as epistasis are widely used in micro-
The fields such as electronics, semiconductor, new material, biological medicine, precision manufactureing.But in micro-nano-scale vision, high power light is micro-
The depth of field of mirror is very short, it is easy to the case where image blur occurs.And the fuzzy of image to be observed is largely affected micro-
To the accurate extraction of target signature under nanoscopic, therefore, the lossless, clear of the blur optical image under micro-nano-scale is studied
Change restoration methods, for promoting the development of micro-nano observation technology and related field science and technology to have very important significance.
Image deblurring is an important research content in the fields such as image procossing and computer vision.Carry out figure at present
Main method used by restoring as sharpening is non-blindness deblurring, also referred to as non-Blind deconvolution.Common non-blindness is anti-
Convolution algorithm includes：Wiener filtering Deconvolution Algorithm Based on Frequency, Lucy-Richardson Deconvolution Algorithm Based on Frequency, least square Deconvolution Algorithm Based on Frequency
Deng.The basic principle of these restoration methods is：In the case of the known specifically fuzzy origin cause of formation, obtain what scenery obscured by estimation
Unified point spread function, then the process to the processing of blurred picture deblurring.But non-Blind deconvolution is by fuzzy in practical application
And influence of noise, existence information lose the problem of, i.e., these clarification methods damage, it is difficult to make in High Accuracy Observation
With.Therefore, how to be estimated for optical imagery blurring process under micro-nano-scale, and modeling analysis just becomes micro-nano meter ruler
The lower lossless key clearly reconstructed of optical imagery of degree.
Invention content
In view of the drawbacks of the prior art, the present invention provides a kind of lossless clear reconstruct side of optical imagery under micro-nano-scale
Method, to improve the accuracy observed target signature under micro-nano vision.
The lossless clear reconstructing method of optical imagery, includes the following steps under micro-nano-scale：
Step 1：Using same video camera piece image is acquired when focal length, image distance, numerical aperture are fixed；Upper
State condition it is constant in the case of, then change the distance between video camera and object, the size of distance change is Δ s, acquisition second
Width target image；
Step 2：Using piece image as source images E1(x, y), wherein x, y respectively represent the horizontal direction of imaging plane
And vertical direction, the second width image are target image E2(x, y), piece image E1(x, y) and the second width image E2(x, y) is right
The clear image answered is E0(x, y), calculates the optical energy propagation time from clear image to target image, and specific method is：
Step 2.1：The optical energy propagation equation group for establishing each pixel in each image, is shown below：
In formula, t ∈ (0, ∞) are indicated from E0The optical energy propagation time that (x, y) starts, t1It indicates from E0(x, y) arrives E1
The optical energy propagation time of (x, y), t2It indicates from E0(x, y) arrives E2The optical energy propagation time of (x, y), ε (x, y) are indicated
The optical energy propagation coefficient of pixel (x, y), u (x, y, 0), u (x, y, t1) and u (x, y, t2) it is respectively clear image E0(x,
Y), piece image E1(x, y) and the second width target image E2Reconstruct corresponding to (x, y) is fitted image,
Gradient operator is represented, It is differential operator；
Step 2.2：Calculate the optical energy propagation time Δ t=t from piece image to the second width image2-t1, calculate
Formula is as follows：
In formula, Δ σ2Indicate that optical energy propagates caused image fog-level variation；If Δ σ2＞ 0, then it represents that from
The optical energy propagation of piece image to the second width image is light energy diffusion process, and propagation coefficient is positive number；If Δ σ2＜
0, then it represents that it is that light energy converges process to be propagated from piece image to the optical energy of the second width image, and propagation coefficient is negative
Number；
Step 2.3：Setting time change step τ, the later energy propagation timings t=t of update iteration n times1+ n τ, according to
Step 2.2 calculates image fog-level changing value when energy propagation timings are tFormula is：
Step 2.4：According to step 2.3Blurred picture E when the calculating propagation time is tt(x, y), formula are：
In formula, x ', y ' indicate the transverse and longitudinal coordinate of any point in the first width source images respectively；
Step 2.5：Calculate blurred picture E when the second width image and propagation time are ttThe global energy of (x, y) is poor, if
Energy difference is more than energy thresholdThe propagation time that each pixel is updated with step-length τ is then returned to step 2.3 and continues iteration；
If energy is less than or equal to threshold value, iteration stopping, when obtaining propagating to the optical energy of the second width target image from clear image
Between t2；
Blurred picture E when the second width image and propagation time are ttThe calculating of the global energy difference F (t) of (x, y)
Formula is as follows：
In formula, α is normalization parameter, and k is Optimal Parameters；
Step 3：According to the optical energy propagation equation group in step 2, clear image E is obtained0(x, y), following formula institute
Show：
In formula, ω, v indicate the transverse and longitudinal coordinate of any point in the second width target image ,-t respectively2Indicate the second width target
Image E2(x, y) arrives clear image E0The reverse optical energy propagation timings of (x, y)；
Step 4：The second width target image and the average gradient and image entropy of clear image are calculated separately, to measure reconstruct
The readability of clear image, average gradient is bigger, and reflection image is stronger to the ability to express of marginal information and texture information, figure
As the average information of entropy characterization image, Image entropy is bigger, and the clarity and precision of image are higher；
Departure degree of the average gradient of described image by the boundary pixel of image with surrounding pixel in certain direction carries out
It calculates, calculation formula is as follows：
In formula,For the average gradient of image E (i, j), M and N indicate the width and height of image E (i, j) respectively, and i, j are
Intensity value ranges [0,255], i are certain center pixel gray value in image, and j is certain center pixel surrounding neighbors pixel ash in image
Spend average value；
The calculation formula of described image entropy is shown below：
In formula, H is image entropy, and what f (i, j) indicated the feature group that the gray value i and gray value j of image are formed goes out occurrence
Number.
As shown from the above technical solution, the beneficial effects of the present invention are：Optics under micro-nano-scale provided by the invention
The lossless clear reconstructing method of image reconstructs clear image with optical energy propagation equation dynamic lossless, avoids tradition
Using the calculating process for solving complexity when Deconvolution Method reconstructs clear image, realize under micro-nano vision to target signature
Accurate surveying.Meanwhile this method image blur Analysis on Mechanism from micro-nano vision is started with, and is that image is extensive in micro-nano vision
Multiple research provides theoretical research foundation.
Description of the drawings
Fig. 1 is the flow of the lossless clear reconstructing method of optical imagery under micro-nano-scale provided in an embodiment of the present invention
Figure；
Fig. 2 is the two images that video camera provided in an embodiment of the present invention takes, wherein (a) is video camera shooting
First width coloured image extracts the image after gray scale, (b) after for the second width coloured image extraction gray scale of video camera shooting
Image；
Fig. 3 is the design sketch after the progress lossless recovery of sharpening provided in an embodiment of the present invention to the second width target image.
Specific implementation mode
With reference to the accompanying drawings and examples, the specific implementation mode of the present invention is described in further detail.Implement below
Example is not limited to the scope of the present invention for illustrating the present invention.
The lossless clear reconstructing method of optical imagery receives standard under present embodiment micro-nano-scale using the present invention
Rice grid is tested, and experiment uses the high 500nm of standard grid, and wide 1500nm, error is within 3%.It is adopted in present embodiment
It uses HIROX-7700 types microscope as video camera, standard nanometer grid can be amplified 7000 times.
The lossless clear reconstructing method of optical imagery under micro-nano-scale, as shown in Figure 1, including the following steps：
Step 1：Same video camera is fixed in focal length f=0.357mm, image distance R=0.399mm, numerical aperture D=2
When, acquire piece image E1(x, y)；In the case where above-mentioned condition is constant, then change the distance between video camera and object,
Distance change is dimensioned to s=5 μm of Δ, the second width image E of acquisition in present embodiment2(x, y).
If it is coloured image to collect image, needs to convert two images, be converted into gray level image.
8 gray level images are used in present embodiment, i.e. the brightness value of pixel is 0-255, and the first width coloured image is transformed
Shown in gray level image such as Fig. 2 (a)；Shown in transformed gray level image such as Fig. 2 (b) of second width coloured image.The present embodiment
Target is that the gray level image for obscuring the second width carries out lossless sharpening recovery.
Step 2：Using the piece image of Fig. 2 (a) as source images E1(x, y), wherein x, y respectively represent imaging plane
Horizontally and vertically, the second width image of Fig. 2 (b) is target image E2(x, y), piece image E1(x, y) and second
Width image E2(x, y) corresponding clear image is E0(x, y), when calculating the optical energy propagation from clear image to target image
Between, specific method is：
The optical energy propagation equation group of each pixel in image is established, formula is：
In formula, t is indicated from E0The optical energy propagation time that (x, y) starts；t1It indicates from E0(x, y) arrives E1The light of (x, y)
Learn energy propagation timings；t2It indicates from E0(x, y) arrives E2The optical energy propagation time of (x, y)；ε (x, y) expressions pixel (x,
Y) optical energy propagation coefficient, wherein x, y respectively represent horizontally and vertically u (x, y, 0), the u of imaging plane
(x, y, t1) and u (x, y, t2) it is respectively clear image E0(x, y), piece image E1(x, y) and the second width target image E2(x,
Y) reconstruct corresponding to is fitted image, Gradient operator is represented,It is differential operator.
Step 2.2：Calculate the optical energy propagation time Δ t=t from piece image to the second width image2-t1, calculate
Formula is as follows：
In formula, Δ σ2Indicate that optical energy propagates caused image fog-level variation.If Δ σ2＞ 0, then it represents that from
The optical energy propagation of piece image to the second width image is light energy diffusion process, and propagation coefficient is positive number；If Δ σ2＜
0, then it represents that it is that light energy converges process to be propagated from piece image to the optical energy of the second width image, and propagation coefficient is negative
Number.
Step 2.3：Use the energy of length and wide the second width of identical initialization of two-dimensional array image with the second width image
In the propagation time, simple in order to calculate, the present embodiment defines t2(x, y) each propagation time initial value be ideal object away from
3.4mm；Setting current time no longer changes, i.e., energy threshold when depth no longer changes Size with calculate tie
The precision of fruit is inversely proportional；The order of magnitude of iteration step length τ, τ is set according to video camera ideal object away from determination, with iterations at anti-
Than τ=50nm in the present embodiment.Update the later energy propagation timings t=t of iteration n times1+ n τ calculate energy according to step 2.2
Image fog-level changing value when the amount propagation time is tCalculation formula is as follows：
Step 2.4：According to step 2.3Blurred picture E when the calculating propagation time is tt(x, y), formula are：
In formula, x ', y ' indicate the transverse and longitudinal coordinate of any point in the first width source images respectively；
Step 2.5：Calculate blurred picture E when the second width image and propagation time are ttThe global energy of (x, y) is poor, if
Energy difference is more than energy thresholdThe propagation time that each pixel is updated with step-length τ is then returned to step 2.3 and continues iteration；
If energy is less than or equal to threshold value, iteration stopping, when obtaining propagating to the optical energy of the second width target image from clear image
Between t2；
Blurred picture E when second width image and propagation time are ttThe calculation formula of the global energy difference F (t) of (x, y)
As follows：
In formula, α is normalization parameter, and k is Optimal Parameters, in the present embodiment, α=0.6, k=2.
In the present embodiment, iterations are set as 200 times, if having reached iterations, iteration is jumped out automatically, terminates to follow
Ring process.
Step 3：According to the optical energy propagation equation group in step 2, clear image E is obtained0(x, y), calculation formula is such as
It is lower no：
In formula, ω, v indicate the transverse and longitudinal coordinate of any point in the second width target image ,-t respectively2Indicate the second width target
Image E2(x, y) arrives clear image E0The reverse optical energy propagation timings of (x, y)；
Step 4：Average gradient and the image entropy of the second width target image and clear image are calculated separately to measure reconstruct
The readability of clear image, average gradient is bigger, and reflection image is stronger to the ability to express of marginal information and texture information, figure
As the average information of entropy characterization image, Image entropy is bigger, and the clarity and precision of image are higher；
Departure degree of the average gradient of image by the boundary pixel of image with surrounding pixel in certain direction is calculated,
Calculation formula is as follows：
In formula,For the average gradient of image E (i, j), M and N indicate the width and height of image E (i, j), i, j respectively
For intensity value ranges [0,255], i is certain center pixel gray value in image, and j is certain center pixel surrounding neighbors pixel in image
Average gray；
The calculation formula of image entropy is shown below：
In formula, H is the entropy of image E (i, j), and f (i, j) indicates the appearance for the feature group that gray value i and gray value j is formed
Number.
In the present embodiment, the fuzzy clear image restored is removed as shown in figure 3, compared with original target image Fig. 2 (b),
Clear image has preferably restored the Texture eigenvalue of grating image；In step 4, the second width target image of calculating and clear figure
The image averaging gradient and image entropy of picture be respectively：The average gradient of second width target image only has 0.000217, and passes through extensive
The average gradient of clear image after multiple is 0.072893, improves two orders of magnitude.The image entropy of second width target image is only
Have 5.54, and the image entropy of the clear image after over recovery reaches 6.1.Image definition evaluation value average gradient after recovery
It is greatly improved with image entropy, so, for micro-nano-scale blurred picture, can be effectively removed using the method for the present invention
It is fuzzy to obtain lossless clear image, effectively increase the observation effect to target signature under micro-nano vision.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, it will be understood by those of ordinary skill in the art that：It still may be used
To modify to the technical solution recorded in previous embodiment, either which part or all technical features are equal
It replaces；And these modifications or replacements, model defined by the claims in the present invention that it does not separate the essence of the corresponding technical solution
It encloses.
Claims (7)
1. the lossless clear reconstructing method of optical imagery under a kind of micro-nano-scale, it is characterised in that：Include the following steps：
Step 1：Using same video camera piece image is acquired when focal length, image distance, numerical aperture are fixed；In above-mentioned item
In the case that part is constant, then change the distance between video camera and object, the size of distance change is Δ s, acquires the second width mesh
Logo image；
Step 2：Using piece image as source images E1(x, y), wherein x, y respectively represent the horizontal direction of imaging plane and vertical
Direction, the second width image are target image E2(x, y), piece image E1(x, y) and the second width image E2(x, y) is corresponding clear
Clear image is E0(x, y), calculates the optical energy propagation time from clear image to target image, and specific method is：
Step 2.1：The optical energy propagation equation group for establishing each pixel in each image, is shown below：
In formula, t ∈ (0, ∞) are indicated from E0The optical energy propagation time that (x, y) starts, t1It indicates from E0(x, y) arrives E1(x, y)
The optical energy propagation time, t2It indicates from E0(x, y) arrives E2The optical energy propagation time of (x, y), ε (x, y) indicate pixel
The optical energy propagation coefficient of (x, y), u (x, y, 0), u (x, y, t1) and u (x, y, t2) it is respectively clear image E0(x, y),
Piece image E1(x, y) and the second width target image E2Reconstruct corresponding to (x, y) is fitted image, Represent ladder
Operator is spent, It is differential operator；
Step 2.2：Calculate the optical energy propagation time Δ t=t from piece image to the second width image2-t1；
Step 2.3：Setting time change step τ, the later energy propagation timings t=t of update iteration n times1+ n τ, according to step
2.2 calculate image fog-level changing value Δ σ when energy propagation timings are tt 2；
Step 2.4：According to the Δ σ of step 2.3t 2, the blurred picture E when calculating propagation time is tt(x, y)；
Step 2.5：Calculate blurred picture E when the second width image and propagation time are ttThe global energy of (x, y) is poor, if energy
Difference is more than energy thresholdThe propagation time that each pixel is updated with step-length τ is then returned to step 2.3 and continues iteration；If energy
Amount is less than or equal to threshold value, then iteration stopping, obtains the optical energy propagation time t from clear image to the second width target image2；
Step 3：According to the optical energy propagation equation group in step 2, clear image E is obtained0(x, y)；
Step 4：Calculate separately the second width target image E2(x, y) and clear image E0The average gradient and image entropy of (x, y) come
The readability of the clear image of reconstruct is measured, average gradient is bigger, expression of the reflection image to marginal information and texture information
Ability is stronger, and image entropy characterizes the average information of image, and Image entropy is bigger, and the clarity and precision of image are higher.
2. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
The calculation formula of the rapid 2.2 optical energy propagation time Δ t is as follows：
In formula, Δ σ2Indicate that optical energy propagates caused image fog-level variation；If Δ σ2＞ 0, then it represents that from the first width
The optical energy propagation of image to the second width image is light energy diffusion process, and propagation coefficient is positive number；If Δ σ2＜ 0, then
Indicate that from piece image be that light energy converges process to the propagation of the optical energy of the second width image, propagation coefficient is negative.
3. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
Image fog-level changing value Δ σ when rapid 2.3 energy propagation timings are tt 2Calculation formula it is as follows：
4. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
Blurred picture E when rapid 2.4 propagation time is ttThe calculation formula of (x, y) is as follows：
In formula, x ', y ' indicate the transverse and longitudinal coordinate of any point in the first width source images respectively.
5. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
Blurred picture E when the rapid 2.5 second width image and propagation time are ttThe calculation formula of the global energy difference F (t) of (x, y)
As follows：
In formula, α is normalization parameter, and k is Optimal Parameters.
6. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
The rapid 3 clear image E0The calculation formula of (x, y) is as follows：
In formula, ω, υ indicate the transverse and longitudinal coordinate of any point in the second width target image ,-t respectively2Indicate the second width target image
E2(x, y) arrives clear image E0The reverse optical energy propagation timings of (x, y).
7. the lossless clear reconstructing method of optical imagery under micro-nano-scale according to claim 1, it is characterised in that：Step
Departure degree of the average gradient of rapid 4 described image by the boundary pixel of image with surrounding pixel in certain direction is counted
It calculates, calculation formula is as follows：
In formula,For the average gradient of image E (i, j), M and N indicate that the width and height of image E (i, j), i, j are gray scale respectively
It is worth range [0,255], i is certain center pixel gray value in image, and j is that certain center pixel surrounding neighbors pixel grey scale is flat in image
Mean value；
The calculation formula of described image entropy is shown below：
In formula, H is the entropy of image E (i, j), and the feature group that f (i, j) expressions gray value i and gray value j is formed goes out occurrence
Number.
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| CN113077395A (en) * | 2021-03-26 | 2021-07-06 | 东北大学 | Deblurring method for large-size sample image under high-power optical microscope |
| CN114627469A (en) * | 2022-05-16 | 2022-06-14 | 河北工业大学 | Fruit state nondestructive identification method |
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| CN114627469B (en) * | 2022-05-16 | 2022-08-12 | 河北工业大学 | Fruit state nondestructive identification method |
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