CN106780378B - A kind of blind convolved image restored method that two lenses lens have been corrected for aberration - Google Patents
A kind of blind convolved image restored method that two lenses lens have been corrected for aberration Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20076—Probabilistic image processing
Abstract
The present invention provides a kind of blind convolved image restored method that two lenses lens have been corrected for aberration, the two lenses lens imaging system that this method has been corrected based on aberration, the deblurring problem of blurred picture is converted into blind convolved image and restores problem, for the fuzzy core priori needed for blind convolved image rejuvenation target function, on the basis of being had corrected that in two lenses lens chromatic aberration, substantial residual monochromatic aberration, its fuzzy core are approximately disk annular shape, can be simulated with Gaussian term.The addition of this Gaussian Blur core priori can further improve image restoration quality, improve the practical value for the two lenses lens that aberration has corrected, and this method all has very important significance in image procossing and camera design field.
Description
Technical field
Present invention relates generally to digital image processing field, refer in particular to a kind of correct the blind of two lenses lens for aberration
Convolved image restored method.
Background technology
At present, slr camera is with the image quality of its high definition, selection of abundant camera lens, fast response speed, remarkable
The advantages such as manual ability play more and more important effect in daily life.
In modern optical system, picture quality can reduce because of optical parallax, and the overwhelming majority has spherical mirror knot
Single convex lens of structure all can be by the influence such as aberration, spherical aberration, coma.In order to solve this predicament, existing optical imagery
System is mainly to make up the aberration of single eyeglass by the combined lens of complexity, for example, to make up the several of eyeglass in single anti-camera lens
What distortion and aberration, image quality is further improved, the design of single anti-camera lens is increasingly complicated, or even includes the list of dozens of independence
Eyeglass or lens set.But however, complicated camera lens undoubtedly can also increase the volume of camera lens while image quality is improved
And weight, also cause the cost of camera lens to greatly improve.The increase of camera lens volume and weight is brought not to the routine use of user
Just, also the single reversely large area user of inconvenience promotes the use of for the raising of cost.Therefore, eyeglass aberration is being eliminated as far as possible, be added to picture
While quality, how to reduce camera lens cost, make it more light, also as current slr camera design important need it
One.Unzoned lens system has potential prospect, such as unmanned plane, remotely sensed image and medical imaging in many scientific domains.
In recent years, with the fast development of image restoration technology, more and more ripe, certain in camera lens the methods of image deblurring
A little aberrations and the eyeglass of Modified geometrical distortion of eliminating can be calculated camera work replacement, therefore, unzoned lens imaging by deblurring etc.
The combination of (as shown in Figure 1) and calculating camera work is increasingly becoming a new research direction.Found in specific experiment, color
Inevitable a kind of aberration when difference is single image lenses, and using computational methods eliminate the cost of simple lens aberration compared with
Greatly.
The content of the invention
For aberration in existing unzoned lens imaging method be present, and using the generation of computational methods elimination simple lens aberration
The problem of valency is larger, the present invention provide a kind of blind convolved image restored method that two lenses lens have been corrected for aberration.This hair
It is bright to use the two lenses lens with two eyeglasses, it is intended to correct the aberration (as shown in Figure 2) of single eyeglass.For this aberration
The two lenses lens corrected using blind convolved image restoration algorithm, it is necessary to the blurred picture of its direct shooting restore
To picture rich in detail.
Blind convolved image restores crucial in selecting suitable image prior and fuzzy core priori in object function, so
Final picture rich in detail is tried to achieve using optimized algorithm afterwards.Because the two lenses lens that aberration has corrected that, only monochromatic aberration shape
Into fuzzy core, this kind of fuzzy core can use the priori of Gaussian term is approximate to replace typically into annulus disc-shaped.Therefore, for color
The blind convolved image restored method for the two lenses lens that difference has corrected that, it is first that suitable fuzzy core is such as added in the conventional method
Test, can further improve final image restoration quality.
The technical scheme is that
A kind of blind convolved image restored method that two lenses lens have been corrected for aberration, comprises the following steps：
S1：Blurred picture is obtained using the camera with two lenses lens, wherein two lenses lens refer to include two panels list
The lens of lenses.The design of two eyeglasses of the invention is intended to correcting chromatic aberration, and this is the common method of optical design arts.Mould
Paste image is the blurred picture that is obtained by two lenses lens camera under normal aperture size.
S2：The deblurring problem of blurred picture is converted into blind convolved image and restores problem.
Blind convolved image restoration algorithm is the blind convolved image restoration algorithm based on Maximize, after maximum
Test under probabilistic model, the statistical models that blind convolved image restores problem can be expressed as：
ArgmaxP (k, x | and y)=argmaxP (y | x, k) P (x) P (k) (1)
Wherein, k represents the fuzzy core of two lenses lens；X represents picture rich in detail；Y represents blurred picture；P (k, x | y) represent
Under blurred picture y known conditions, fuzzy core corresponding with blurred picture y and picture rich in detail are respectively k and x probability；P(y|
X, k) represent if it is known that fuzzy core k and picture rich in detail x, corresponding blurred picture are y probability；P (x) is represented to picture rich in detail
Prior probability known to x；P (k) represents fuzzy core k prior probability.
For double lens imaging system, picture rich in detail refers to the image ideally obtained in not extraneous error.It is double
The fuzzy core of eyeglass lens can be understood as the two lenses lens errors of itself, and the error can cause the image ratio that double lens is clapped
It is relatively fuzzy.
S3：Gaussian prior is added in the object function of blind convolved image restoration algorithm as fuzzy core priori；
The object function of blind convolved image restoration algorithm can be expressed as：
Wherein, k represents the fuzzy core of two lenses lens；X represents picture rich in detail；Y represents blurred picture；Represent convolution behaviour
Make；Represent the gradient of fuzzy core；Section 1It is data fit term；Section 2It is image prior, | | x |
|1With | | x | |2It is 1 norm and 2 norms of picture rich in detail respectively；Section 3It is the Gaussian Blur core priori of addition, because
Fuzzy core approximation disk is circular, therefore can be represented with Gauss；α and β is control data fit term and the power of fuzzy core priori
Weight.
S4：The object function of blind convolved image recovery is solved using existing optimized algorithm, obtains final picture rich in detail.Wherein
Optimized algorithm uses the optimized algorithm that existing image restoration field is commonly used, it is ensured that can obtain optimal solution, such as ADMM
(Alternating Direction Method of Multipliers) optimized algorithm.
As described above, the two lenses lens imaging system that the present invention has been corrected based on aberration, by the deblurring of blurred picture
Problem is converted to blind convolved image and restores problem, for the fuzzy core priori needed for blind convolved image rejuvenation target function, examines
Consider on the basis of two lenses lens chromatic aberration has corrected that, substantial residual monochromatic aberration, its fuzzy core is approximately disk annulus
Shape, it can be simulated with Gaussian term.The addition of this Gaussian Blur core priori can further improve image restoration quality, improve
The practical value for the two lenses lens that aberration has corrected, this method all have very heavy in image procossing and camera design field
The meaning wanted.
Brief description of the drawings
Fig. 1 is unzoned lens imaging schematic diagram；
Fig. 2 is the schematic diagram of the two lenses lens corrected in the present invention comprising 2 eyeglass aberration；
Fig. 3 is the flow chart of the present invention；
Fig. 4 is the blurred picture obtained in the embodiment of the present invention；
Fig. 5 is to carry out restoring resulting picture rich in detail using the inventive method blurred picture；
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing to embodiment party of the present invention
Formula is described in further detail.
As shown in figure 3, a kind of blind convolved image that two lenses lens have been corrected for aberration that the present embodiment provides restores
Method, comprise the following steps：
Step 1：Blurred picture is obtained using two lenses lens camera.
Two lenses lens are the two lenses lens corrected comprising 2 eyeglass aberration used by the present embodiment, such as Fig. 2 institutes
Show.The double lens lens are installed on camera, blurred picture, resulting blurred picture such as Fig. 4 are shot under normal aperture
It is shown.
Step 2：The deblurring problem of blurred picture is converted into blind convolved image and restores problem.Comprise the following steps that：
Blind convolved image restoration algorithm is the blind convolved image restoration algorithm based on Maximize, after maximum
Test under probabilistic model, the statistical models that blind convolved image restores problem can be expressed as：
ArgmaxP (k, x | and y)=argmaxP (y | x, k) P (x) P (k) (1)
Wherein, k represents the fuzzy core of unzoned lens；X represents picture rich in detail；Y represents the blurred picture that step 1 obtains；P
(k, x | y) represent under blurred picture y known conditions, fuzzy core corresponding with blurred picture y and picture rich in detail are respectively k and x
Probability；P (y | x, k) represent if it is known that fuzzy core k and picture rich in detail x, corresponding blurred picture are y probability；P (x) tables
Show to prior probability known to picture rich in detail；P (k) represents the prior probability of fuzzy core.
For the two lenses lens imaging system in the present invention, picture rich in detail refers in not extraneous error ideally
Obtained image.The fuzzy core of two lenses lens can be understood as the two lenses lens errors of itself, the error can cause it is double thoroughly
The image that mirror is clapped is relatively fuzzyyer.
Step 3：Gaussian prior is added in the object function of blind convolved image restoration algorithm as fuzzy core priori.
The object function of blind convolved image restoration algorithm can be expressed as：
Wherein, k represents the fuzzy core of two lenses lens；X represents picture rich in detail；Y represents the fuzzy graph obtained by step 1
Picture；Represent convolution operation；Represent the gradient of fuzzy core；Section 1It is data fit term；Section 2It is image prior, | | x | |1With | | x | |2It is 1 norm and 2 norms of picture rich in detail respectively；Section 3It is addition
Gaussian Blur core priori because fuzzy core approximation disk is circular, therefore can be represented with Gauss；α and β intends for control data
Close item and the weight of fuzzy core priori.
Step 4：The object function of blind convolved image recovery, such as ADMM are solved using existing optimized algorithm
(Alternating Direction Method of Multipliers) optimized algorithm, obtains final picture rich in detail, such as Fig. 5
It is shown.
As described above, the two lenses lens imaging system that the present invention has been corrected based on aberration, by the image of two lenses lens
Recovery is converted into blind convolved image restoration algorithm, for the fuzzy core priori needed for blind convolved image rejuvenation target function, examines
Consider on the basis of two lenses lens chromatic aberration has corrected that, substantial residual monochromatic aberration, its fuzzy core is approximately disk annulus
Shape, it can be simulated with Gaussian term.The addition of this Gaussian Blur core priori can further improve image restoration quality, improve
The practical value for the two lenses lens that aberration has corrected, this method all have very heavy in image procossing and camera design field
The meaning wanted.
The explanation of the preferred embodiment of the present invention contained above, this be in order to describe the technical characteristic of the present invention in detail, and
It is not intended to the content of the invention being limited in the concrete form described by embodiment, according to other of present invention purport progress
Modifications and variations are also protected by this patent.The purport of present invention is to be defined by the claims, rather than by embodiment
Specific descriptions are defined.
Claims (2)
1. a kind of blind convolved image restored method that two lenses lens have been corrected for aberration, it is characterised in that including following step
Suddenly：
S1：Blurred picture is obtained using the camera with two lenses lens, wherein two lenses lens refer to include two panels simple lens
The lens of eyeglass；
S2：The deblurring problem of blurred picture is converted into blind convolved image and restores problem；
Blind convolved image restoration algorithm employed in step S2 restores for the blind convolved image based on Maximize to be calculated
Method, under maximum a posteriori probability model, the statistical models that blind convolved image restores problem are expressed as：
ArgmaxP (k, x | and y)=argmaxP (y | x, k) P (x) P (k) (1)
Wherein, k represents the fuzzy core of two lenses lens；X represents picture rich in detail；Y represents blurred picture；P (k, x | y) represent in mould
Paste under image y known conditions, fuzzy core corresponding with blurred picture y and picture rich in detail are respectively k and x probability；P(y|x,k)
Represent if it is known that fuzzy core k and picture rich in detail x, corresponding blurred picture are y probability；P (x) is represented to picture rich in detail x
The prior probability known；P (k) represents fuzzy core k prior probability；
S3：Gaussian prior is added in the object function of blind convolved image restoration algorithm as fuzzy core priori；
In step S3, the object function of blind convolved image restoration algorithm is expressed as：
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Wherein, k represents the fuzzy core of two lenses lens；X represents picture rich in detail；Y represents blurred picture；Represent convolution operation；Represent the gradient of fuzzy core；Section 1It is data fit term；Section 2It is image prior, | | x | |1
With | | x | |2It is 1 norm and 2 norms of picture rich in detail respectively；Section 3It is the Gaussian Blur core priori of addition；α and β are
Control data fit term and the weight of fuzzy core priori；
S4：The object function of blind convolved image recovery is solved using optimized algorithm, obtains final picture rich in detail.
2. the blind convolved image restored method according to claim 1 that two lenses lens have been corrected for aberration, its feature
It is, the optimized algorithm used in step S4 is ADMM optimized algorithms.
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| CN107590790B (en) * | 2017-09-21 | 2021-04-13 | 长沙全度影像科技有限公司 | Simple lens edge area deblurring method based on symmetric edge filling |
| CN107680062A (en) * | 2017-10-12 | 2018-02-09 | 长沙全度影像科技有限公司 | A kind of micro- burnt Restoration method of blurred image based on l1/l2 priori combination Gaussian priors |
| CN107833193A (en) * | 2017-11-20 | 2018-03-23 | 长沙全度影像科技有限公司 | A kind of simple lens global image restored method based on refinement network deep learning models |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1740838A (en) * | 2004-08-27 | 2006-03-01 | 清华大学 | Micro-camera lens system |
| CN104574423A (en) * | 2015-02-03 | 2015-04-29 | 中国人民解放军国防科学技术大学 | Single-lens imaging PSF (point spread function) estimation algorithm based on spherical aberration calibration |
| CN104599254A (en) * | 2015-02-03 | 2015-05-06 | 中国人民解放军国防科学技术大学 | Single lens computational imaging method based on combined fuzzy nuclear structure prior |
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| JP3685486B2 (en) * | 2001-09-07 | 2005-08-17 | フジノン株式会社 | Shooting lens |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1740838A (en) * | 2004-08-27 | 2006-03-01 | 清华大学 | Micro-camera lens system |
| CN104574423A (en) * | 2015-02-03 | 2015-04-29 | 中国人民解放军国防科学技术大学 | Single-lens imaging PSF (point spread function) estimation algorithm based on spherical aberration calibration |
| CN104599254A (en) * | 2015-02-03 | 2015-05-06 | 中国人民解放军国防科学技术大学 | Single lens computational imaging method based on combined fuzzy nuclear structure prior |
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