CN110211074A - Low-light (level) electronic speckle interference fringe pattern image intensifying method - Google Patents
Low-light (level) electronic speckle interference fringe pattern image intensifying method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 32
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- 238000002310 reflectometry Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 5
- 238000005286 illumination Methods 0.000 claims description 5
- 230000002093 peripheral effect Effects 0.000 claims description 3
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- 238000002474 experimental method Methods 0.000 abstract description 6
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- 238000012545 processing Methods 0.000 abstract description 3
- 239000000284 extract Substances 0.000 abstract description 2
- 238000005305 interferometry Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 210000001525 retina Anatomy 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 210000003710 cerebral cortex Anatomy 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/40—Image enhancement or restoration by the use of histogram techniques
Abstract
The invention belongs to optical detections and technical field of image processing, and to realize that the contrast to the electronic speckle interference image of low-light (level) enhances, the striped after image binaryzation can be kept as far as possible completely, so that extracts when subsequent extracted skeleton line is more accurate.The technical solution adopted by the present invention is that, low-light (level) electronic speckle interference fringe pattern image intensifying method, utilize Retinex theory, choose based on center ring around multi-Scale Retinex Algorithm (multi-scale retinex, MSR), the low quality low-light (level) electronic speckle interference fringe pattern picture obtained to experiment is handled, and adjusts scale parameter, optimal result is obtained, to realize image enhancement.Present invention is mainly applied to optical detections and image procossing occasion.
Description
Technical field
The invention belongs to optical detections and technical field of image processing, and it is scattered to be related to a kind of electronics based on Retinex theory
Spot interference fringe image Enhancement Method.
Background technique
Electronic speckle interference (Electronic Speckle Pattern Interferometry, abbreviation ESPI) measurement
Technology is a kind of contemporary optics measuring technique, it has many advantages, such as the non-contact whole audience, high-precision and high sensitivity, is not protected from light, extensively
General deformation measurement and non-destructive testing applied to optically roughness surface.When tested workpiece generates small displacement, in its table
Speckle figure is formed by face can also move, and be recorded speckle figure using photo-optical method, to deformation
Two width speckle images of front and back acquisition do the operation that absolute value subtracts each other, is added or is multiplied, and dissipating for corresponding deformation information can be obtained
Spot bar graph.It is the key that obtain object deformation displacement information that phase is accurately extracted from interference fringe image.
Although Electronic speckle pattern interferometry has many good characteristics, but in the electronic speckle stripe pattern that experiment obtains
It is often accompanied by very strong granularity noise, and will appear the very low phenomenon of illumination, this reduces the clarity of image, so that
The resolution ratio and contrast of striped are affected, and then will affect the result and final measurement essence of Electronic speckle pattern interferometry
Degree, the expansion of extraction and phase to stripe fixed position bring very big challenge.Therefore, find one kind can effectively enhance it is scattered
The method of the readability of spot stripe pattern is particularly important the subsequent processing of electronic speckle interference fringe pattern.
The image enhancement technique based on human vision became a kind of research tendency in recent years, wherein Retinex theory is being schemed
Image intensifying field plays a significant role.This word of Retinex is by retina (Retina) and cerebral cortex (Cortex)
Two word combinations are constituted, and theory is that Land and McCann is proposed, its basic thought be object color by object to length
What the albedo of wave, medium wave and shortwave light determined, it is not dependent on the absolute light that the point enters human eye, and object
Color is not illuminated by the light heteropical influence, with uniformity, i.e. Retinex is based on color constancy.Retinex
Two kinds of forms can be divided into: Retinex based on path and based on center ring around Retinex.Commonly Retinex algorithm is
Based on center ring around single scale Retinex algorithm (single-scale retinex, SSR) and multi-Scale Retinex Algorithm
(multi-scale retinex,MSR).Retinex algorithm basic principle is that given image is resolved into two different figures
Picture, reflected image and incident image, reflected image are exactly the original image not being interfered.This method is will be in given image
In, the influence of incident image is reduced, retains the reflecting attribute of object essence as far as possible, to obtain the most essential appearance of image.
Summary of the invention
In order to overcome the deficiencies of the prior art, the present invention is directed to realize the contrast to the electronic speckle interference image of low-light (level)
Enhance, the striped after image binaryzation can be kept as far as possible completely, so that extracts when subsequent extracted skeleton line is more accurate.This
Invention the technical solution adopted is that, low-light (level) electronic speckle interference fringe pattern image intensifying method utilizes Retinex theoretical, chooses
Based on center ring around multi-Scale Retinex Algorithm (multi-scale retinex, MSR), to experiment obtain low quality it is low
Illumination electronic speckle interference fringe pattern picture is handled, and is adjusted scale parameter, optimal result is obtained, to realize image enhancement.
Low-light (level) electronic speckle interference fringe pattern image intensifying method, specifically uses that the technical scheme comprises the following steps:
Step 1: obtaining low-light (level) electronic speckle interference fringe pattern as f；
Step 2: building Retinex theoretical model；
Step 3: each scale parameter of multi-Scale Retinex Algorithm MSR, the enhancing figure made are adjusted for every width figure
As m1 effect is best.
Step 2: building Retinex theoretical model, the specific steps are as follows:
Step 2-1: firstly, according to Retinex theory, using take the method for logarithm by irradiation component and reflecting component point
From, it may be assumed that
LogS (x, y)=logR (x, y)+logL (x, y)
Wherein, S represents the image that we are seen, L is incident light images, and R is the reflectivity properties of object.Retinex is just
It is the reflectivity properties R of object to be obtained by image S, that is, try to remove or reduce the influence of incident light L to obtain
The object script appearance having；
Step 2-2: by the weighted average of pixel in pixel in calculating image and peripheral region come to illumination in image
Variation, which is done, to be estimated, and is removed it, the last reflecting attribute for only retaining objects in images, then is rolled up with Gaussian template to original image
Product, that is, making low-pass filtering to original image, the image D (x, y) after obtaining low-pass filtering, F (x, y) indicate gaussian filtering letter
Number:
D (x, y)=S (x, y) * F (x, y)
Step 2-3: in log-domain, with the image after original image image subtraction low-pass filtering, the image G of high frequency enhancement is obtained
(x, y):
G (x, y)=logS (x, y)-logD (x, y)
Step 2-4: negating logarithm to G (x, y), obtains enhanced image R (x, y):
R (x, y)=exp G (x, y)
Step 3: according to the requirement of MSR scale, step 2-2 is carried out respectively to image with large, medium and small three kinds of scales respectively,
Step 2-3 and step 2-4, and summation is weighted to the result under each scale.
It further include following effect assessment step, step 1: being enhanced using Enhancement Method image, specific is respectively straight
Side's figure equalization, sobel operator enhance the image of input, obtain enhancing image m2, m3；
Step 2: obtained all enhancing images and original image being subjected to binaryzation, the result after obtaining binaryzation.
The features of the present invention and beneficial effect are:
Low-light (level) electronic speckle interference fringe pattern image intensifying method proposed by the present invention based on Retinex theory, is compared
In traditional electronic speckle interference fringe pattern image intensifying method, this method reinforcing effect is more preferable, as much as possible to maintain striped
Edge, the striped obtained from is more complete, more conducively subsequent skeleton line drawing and phase unwrapping.
Detailed description of the invention:
Fig. 1 is the method for the low-light (level) electronic speckle interference fringe pattern image intensifying method the present invention is based on Retinex theory
Flow chart；
Fig. 2 (a) (b) be variable density electronic speckle interference fringe pattern picture and its binaryzation, (c) (d) is to Fig. 2's (a)
MSR enhances image and its binaryzation, and (e) (f) is to enhance image and its binaryzation, (g) (h) to the histogram equalization of Fig. 2 (a)
It is that image and its binaryzation are enhanced to the sobel operator of Fig. 2 (a)；
Fig. 3 (a) (b) is the binaryzation of low-density electronic speckle interference fringe pattern picture and image, and (c) (d) is to Fig. 3 (a)
MSR enhancing image and its binaryzation, (e) (f) is to enhance image and its binaryzation to the histogram equalization of Fig. 3 (a), (g)
It (h) is that image and its binaryzation are enhanced to the sobel operator of Fig. 3 (a)；
Fig. 4 (a) (b) is the binaryzation of high density electronic speckle interference fringe pattern picture and image, and (c) (d) is to Fig. 4 (a)
MSR enhancing image and its binaryzation, (e) (f) is to enhance image and its binaryzation to the histogram equalization of Fig. 4 (a), (g)
It (h) is that image and its binaryzation are enhanced to the sobel operator of Fig. 4 (a)；
Specific embodiment
Next the low-light (level) electronic speckle interference fringe pattern image intensifying proposed by the present invention based on Retinex theory is applied
Method is enhanced.Specific step is as follows:
Step 1: carrying out the experimental image that experiment obtains low-light (level).According to the density feature of electronic speckle interference fringe pattern picture
It is tested, experiment obtains the electronic speckle interference fringe pattern picture of low-density and high density and variable density.
Step 2: building Retinex theoretical model.Specific step is as follows:
Step 2-1: firstly, according to Retinex theory, using take the method for logarithm by irradiation component and reflecting component point
From, it may be assumed that
LogS (x, y)=logR (x, y)+logL (x, y)
Wherein, S represents the image that we are seen, L is incident light images, and R is the reflectivity properties of object.Retinex is just
It is the reflectivity properties R of object to be obtained by image S, that is, try the influence of removal (or reduction) incident light L to obtain
To the object script appearance having.
Step 2-2: final reflected image can be estimated as space smoothing image with being assumed, and (its physical interpretation is exactly to pass through
It calculates pixel and the weighted average of pixel in peripheral region in image to estimate to do illumination change in image, and is gone
Remove, the last reflecting attribute for only retaining objects in images), it is possible to convolution is made to original image with Gaussian template, that is,
Low-pass filtering is made to original image, the image D (x, y) after obtaining low-pass filtering, F (x, y) indicate Gaussian filter function:
D (x, y)=S (x, y) * F (x, y)
Step 2-3: in log-domain, with the image after original image image subtraction low-pass filtering, the image G of high frequency enhancement is obtained
(x, y):
G (x, y)=logS (x, y)-logD (x, y)
Step 2-4: negating logarithm to G (x, y), obtains enhanced image R (x, y):
R (x, y)=exp G (x, y)
Step 3: according to the requirement of MSR scale, the size of scale selects most classic three scale, respectively with large, medium and small three
Kind scale carries out step 2-2, step 2-3 and step 2-4 to image respectively, and is weighted and asks to the result under each scale
With.
Step 4: the superiority in order to protrude method proposed by the invention, this experiment also have chosen two traditional figures
Image intensifying method, respectively histogram equalization Enhancement Method and sobel operator, enhance experimental image.
Step 5: obtained all enhancing images and original image being subjected to binaryzation, the result after obtaining binaryzation.
The flow chart of the algorithm is shown in attached drawing 1.
For the validity of verification method, experimental results.
Fig. 2 (a) is the electronic speckle interference fringe pattern picture of variable density, and Fig. 2 (b) is the result after Fig. 2 (a) binaryzation.
Likewise, Fig. 2 (c) (e) (g), respectively by MSR, histogram equalization and the enhanced image of sobel operator, and Fig. 2
(d) (f) (h) is respectively the binaryzation of above-mentioned three width image.Fig. 3 (a) is the electronic speckle interference fringe pattern picture of low-density, Fig. 3
(b) it is result after Fig. 3 (a) binaryzation.Likewise, Fig. 3 (c) (e) (g), respectively by MSR, histogram equalization with
And the enhanced image of sobel operator, and Fig. 3 (d) (f) (h) is respectively the binaryzation of above-mentioned three width image.Fig. 4 (a) is highly dense
The electronic speckle interference fringe pattern picture of degree, Fig. 4 (b) are the results after Fig. 4 (a) binaryzation.Likewise, Fig. 4 (c) (e) (g),
Respectively by MSR, histogram equalization and the enhanced image of sobel operator, and Fig. 4 (d) (f) (h) is respectively above-mentioned
The binaryzation of three width images.
Either from the image comparison after the comparison or binaryzation of enhancing image, it can be seen that proposed by the present invention
Image enchancing method can be good at enhancing the electronic speckle interference fringe pattern picture of the low-light (level) of various density features,
And the effect after binaryzation also has superiority.
Although above in conjunction with diagram, invention has been described, and the invention is not limited to above-mentioned specific implementations
Mode, the above mentioned embodiment is only schematical, rather than restrictive, and those skilled in the art are at this
Under the enlightenment of invention, without deviating from the spirit of the invention, many variations can also be made, these belong to of the invention
Within protection.
It will be appreciated by those skilled in the art that attached drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention
Serial number is for illustration only, does not represent the advantages or disadvantages of the embodiments.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (4)
1. a kind of low-light (level) electronic speckle interference fringe pattern image intensifying method, characterized in that the following steps are included:
Step 1: obtaining low-light (level) electronic speckle interference fringe pattern as f；
Step 2: building Retinex theoretical model；
Step 3: each scale parameter of multi-Scale Retinex Algorithm MSR, the enhancing image m1 made are adjusted for every width figure
Effect is best.
2. low-light (level) electronic speckle interference fringe pattern image intensifying method as described in claim 1, characterized in that step 2: building
Retinex theoretical model, the specific steps are as follows:
Step 2-1: firstly, according to Retinex theory, using taking the method for logarithm to separate irradiation component and reflecting component, it may be assumed that
LogS (x, y)=logR (x, y)+logL (x, y)
Wherein, S represents the image that we are seen, L is incident light images, and R is the reflectivity properties of object.Retinex is exactly logical
Image S is crossed to obtain the reflectivity properties R of object, that is, tries to remove or reduce the influence of incident light L to obtain object
Originally the appearance having；
Step 2-2: by the weighted average of pixel in pixel in calculating image and peripheral region come to illumination change in image
It does and estimates, and remove it, the last reflecting attribute for only retaining objects in images, then convolution is made to original image with Gaussian template,
That is, making low-pass filtering to original image, the image D (x, y) after obtaining low-pass filtering, F (x, y) indicate Gaussian filter function:
D (x, y)=S (x, y) * F (x, y)
Step 2-3: in log-domain, with the image after original image image subtraction low-pass filtering, the image G (x, y) of high frequency enhancement is obtained:
G (x, y)=logS (x, y)-logD (x, y)
Step 2-4: negating logarithm to G (x, y), obtains enhanced image R (x, y):
R (x, y)=exp G (x, y)
Step 3: according to the requirement of MSR scale, step 2-2, step being carried out respectively to image with large, medium and small three kinds of scales respectively
2-3 and step 2-4, and summation is weighted to the result under each scale.
3. low-light (level) electronic speckle interference fringe pattern image intensifying method as described in claim 1, characterized in that further include as follows
Effect assessment step, step 1: image being enhanced using Enhancement Method, specifically respectively histogram equalization, sobel are calculated
Son enhances the image of input, obtains enhancing image m2, m3.
4. low-light (level) electronic speckle interference fringe pattern image intensifying method as described in claim 1, characterized in that in step 2 also
Including obtained all enhancing images and original image are carried out binaryzation, the result after obtaining binaryzation.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111179183A (en) * | 2019-11-29 | 2020-05-19 | 北京时代民芯科技有限公司 | Image enhancement method under non-uniform illumination environment in nuclear-grade environment |
| CN112565637A (en) * | 2020-11-20 | 2021-03-26 | 中国航空工业集团公司洛阳电光设备研究所 | Method for removing stripe noise under low illumination in single-color sCMOS camera |
| CN114862786A (en) * | 2022-04-29 | 2022-08-05 | 清远蓄能发电有限公司 | Retinex image enhancement and Ostu threshold segmentation based isolated zone detection method and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105844601A (en) * | 2016-05-20 | 2016-08-10 | 中国矿业大学(北京) | Mine image enhancement method based on bilateral filtering and multi-scale Retinex algorithm |
| CN106780375A (en) * | 2016-12-02 | 2017-05-31 | 南京邮电大学 | A kind of image enchancing method under low-light (level) environment |
-
2019
- 2019-05-31 CN CN201910472424.0A patent/CN110211074A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105844601A (en) * | 2016-05-20 | 2016-08-10 | 中国矿业大学(北京) | Mine image enhancement method based on bilateral filtering and multi-scale Retinex algorithm |
| CN106780375A (en) * | 2016-12-02 | 2017-05-31 | 南京邮电大学 | A kind of image enchancing method under low-light (level) environment |
Non-Patent Citations (3)
| Title |
|---|
| 李勇: "基于Retinex理论的低照度图像增强算法研究与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 董静薇等: "基于同态滤波及多尺度Retinex的低照度图像增强算法", 《科学技术与工程》 * |
| 韩海峰: "低照度图像增强方法的研究与应用", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111179183A (en) * | 2019-11-29 | 2020-05-19 | 北京时代民芯科技有限公司 | Image enhancement method under non-uniform illumination environment in nuclear-grade environment |
| CN111179183B (en) * | 2019-11-29 | 2023-11-21 | 北京时代民芯科技有限公司 | Image enhancement method in non-uniform illumination environment in nuclear-grade environment |
| CN112565637A (en) * | 2020-11-20 | 2021-03-26 | 中国航空工业集团公司洛阳电光设备研究所 | Method for removing stripe noise under low illumination in single-color sCMOS camera |
| CN112565637B (en) * | 2020-11-20 | 2022-07-29 | 中国航空工业集团公司洛阳电光设备研究所 | Method for removing stripe noise under low illumination in monochromatic sCMOS camera |
| CN114862786A (en) * | 2022-04-29 | 2022-08-05 | 清远蓄能发电有限公司 | Retinex image enhancement and Ostu threshold segmentation based isolated zone detection method and system |
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