CN106327432A - Image restoration method and device based on offset quantity - Google Patents

Abstract

The invention provides an image restoration method and device based on offset quantity. The method comprises the steps of forming an image cube by a to-be-restored target image and an image in an image library; dividing all images in the image cub into image blocks and obtaining a target image block of the target image and the image block of the image; obtaining a dominant offset quantity of the image block of a known region in the target image, wherein the dominant offset quantity is a statistic set of a plurality of offset quantities of the image blocks similar to the image block of the known region; restoring pixels of a missed region in the target image by employing an energy equation distribution strategy according to the dominant offset quantity, thereby obtaining a restored target image, wherein the target image comprises the known region and the missed region. According to the method and the device, the structure information of the target image is described effectively, extra information of the image library can be imported, and the restoration structure of the target image is more natural.

Description

Image repair method based on side-play amount and device

Technical field

The present invention relates to technical field of image processing, particularly relate to a kind of image based on side-play amount Restorative procedure and device.

Background technology

Image repair is lack part in a kind of process image, by lack part completion, and makes to repair Result after Fu looks natural technology.Utilize image repair technology, image can be completed dirty Point is removed, panorama picture formation, textures synthesis, removes watermark, and cultural relics and historic sites picture reparation etc. should With, video field can also be applied to simultaneously, carry out real border and merge, remove the complicated behaviour such as captions Make.

Seriality based on picture structure, an existing scheme is will to be lacked by partial differential equation The known color of mistake portion outboard travels to lack part and repairs.This scheme can effectively keep The original structure of image, but it is only applicable to less absent region, if absent region is relatively big, The result then repaired can obscure shortage details.

Self-similarity based on image, an existing scheme is to seek along the edge of lack part Look for similar block, the pixel value of similar block is filled up into, the most gradually complete repair process. This scheme also can keep details to bigger absent region, but Greedy strategy is often absorbed in Locally optimal solution, it is impossible to effectively keep the seriality of picture structure.

On the other hand, when single image is repaired, if target image loses information too much, Lack enough useful informations, also can bring difficulty to repair.So image repair needs Key problems-solving is in the face of bigger absent region and not enough useful information, how to repair Keep the structural continuity of image during Fu, and make reparation result look nature.

Summary of the invention

For defect of the prior art, the present invention provides a kind of image based on side-play amount to repair Multiple method and device, the method can effectively describe the structural information of target image, can draw again Enter the extraneous information of image library, make target image repair structure more natural.

First aspect, the present invention provides a kind of image repair method based on side-play amount, including:

By the image in target image to be repaired and image library, pie graph picture cube；

To the image block that each image division is partly overlapping r × r in image cube, obtain Obtaining target image block and the image block of image of target image, r is the natural number more than 1；

Obtain the leading side-play amount of the image block of known region in described target image；Described master Lead the similar image block of the image block to described known region that side-play amount is statistics some partially The set of shifting amount；

According to described leading side-play amount, use energy equation allocation strategy to described target image The pixel of middle absent region is repaired, and obtains the target image after repairing；

Described target image includes known region and absent region.

Alternatively, obtain the leading side-play amount of the image block of known region in described target image, Step include:

For each target image block in described known region, in described image cube Search the image block most like with this target image block；

Obtain the skew of each target image block image block most like with this target image block Amount；

Use statistical by described for selected part side-play amount combination in all side-play amounts leading inclined Shifting amount.

Alternatively, for each target image block in described known region, at described figure As cube in search the image block most like with this target image block, step include:

Use formula (1) to calculate the difference degree between two image blocks, stand at described image Side search minimum with each target image block difference degree as most like image Block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, Ψ_xRepresent in the known region of described target image point centered by pixel value x Target image block, Ψ_yFor in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient.

Alternatively, the image that each target image block is most like with this target image block is obtained The side-play amount of block, step include:

For target image block Ψ_xThe most like image block Ψ found_y, form similar block pair (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to the I in described image cube_k Image, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁,k)。

Alternatively, use statistical by selected part side-play amount combination institute in all side-play amounts State leading side-play amount, step include:

For all relative dimensional side-play amounts of all target image block of described known region, Extract the occurrence number leading side-play amount of relative dimensional side-play amount composition more than predetermined threshold value S={s₁,s₂,…,s_N}；

Or,

For all relative dimensional side-play amounts of all target image block of described known region, Extract N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

Alternatively, described according to described leading side-play amount, use energy equation allocation strategy pair In described target image, the pixel of absent region is repaired, and obtains the target figure after repairing Picture, step include:

Formula (2) is used to determine in described absent region selected by each target pixel points x Repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along 3-D migration Pixel in the image cube that amount is pointed to；

For each target pixel points x in absent region, distribute one for this target pixel points x Individual leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace this target Pixel x, it is thus achieved that the target image after reparation；Described target pixel points is target image block Central pixel point, pixel is the central pixel point of image block；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s(L\left(x\right),L\left(y\right))+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\right(x))---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.

Second aspect, the present invention also provides for a kind of image fixing apparatus based on side-play amount, bag Include:

Image cube Component units, for by the figure in target image to be repaired and image library Picture, pie graph picture cube；

Image block division unit, being used for each image division in image cube is part The image block of overlapping r × r, it is thus achieved that the target image block of target image and the image block of image, R is the natural number more than 1；

Leading side-play amount acquiring unit, for obtaining the figure of known region in described target image Leading side-play amount as block；Described leading side-play amount is the figure with described known region of statistics The set of some side-play amounts of the image block that picture block is similar；

Repair unit, for according to described leading side-play amount, use energy equation allocation strategy The pixel of absent region in described target image is repaired, obtains the target after repairing Image；

Described target image includes known region and absent region.

Alternatively, leading side-play amount acquiring unit, specifically for

For each target image block in described known region, in described image cube Search the image block most like with this target image block；

Obtain the skew of each target image block image block most like with this target image block Amount；

Use statistical by described for selected part side-play amount combination in all side-play amounts leading inclined Shifting amount.

Alternatively, leading side-play amount acquiring unit, specifically for

Use formula (1) to calculate the difference degree between two image blocks, stand at described image Side search minimum with each target image block difference degree as most like image Block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, Ψ_xRepresent in the known region of described target image point centered by pixel value x Target image block, Ψ_yFor in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient；

For target image block Ψ_xThe most like image block Ψ found_y, form similar block pair (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to the I in described image cube_k Image, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁,k)；

For all relative dimensional side-play amounts of all target image block of described known region, Extract the occurrence number leading side-play amount of relative dimensional side-play amount composition more than predetermined threshold value S={s₁,s₂,…,s_N}；

Or,

For all relative dimensional side-play amounts of all target image block of described known region, Extract N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

Alternatively, described reparation unit, specifically for

Formula (2) is used to determine in described absent region selected by each target pixel points x Repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along 3-D migration Pixel in the image cube that amount is pointed to；

For each target pixel points x in absent region, distribute one for this target pixel points x Individual leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace this target Pixel x, it is thus achieved that the target image after reparation, described target pixel points is target image block Central pixel point, pixel is the central pixel point of image block；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s(L\left(x\right),L\left(y\right))+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\right(x))---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.

As shown from the above technical solution, the image repair method based on side-play amount of the present invention and dress Put, by image cube, obtain leading side-play amount, and then obtain the target image after repairing, The method can effectively describe the structural information of target image, can introduce again the extra letter of image library Breath, is conducive to keeping the seriality of target image structure, improves the subjective vision repairing result Quality, makes target image repair structure more natural.

Accompanying drawing explanation

By reading the detailed description of hereafter preferred implementation, various other advantage and benefit Those of ordinary skill in the art be will be clear from understanding.Accompanying drawing is only used for illustrating and is preferable to carry out The purpose of mode, and it is not considered as limitation of the present invention.And in whole accompanying drawing, use Identical reference marks represents identical parts.In the accompanying drawings:

The flow process of the image repair method based on side-play amount that Fig. 1 provides for one embodiment of the invention Schematic diagram；

The schematic diagram of the image repair method that Fig. 2 provides for one embodiment of the invention；

The knot of the image fixing apparatus based on side-play amount that Fig. 3 provides for another embodiment of the present invention Structure schematic diagram.

Detailed description of the invention

Embodiments of the invention are described below in detail, and the example of described embodiment is shown in the accompanying drawings Going out, the most same or similar label represents same or similar element or has phase With or the element of similar functions.The embodiment described below with reference to accompanying drawing is exemplary, It is only used for explaining the present invention, and is not construed as limiting the claims.

Those skilled in the art of the present technique are appreciated that unless expressly stated, odd number used herein Form " one ", " one ", " described " and " being somebody's turn to do " may also comprise plural form.Should manage further Solving, the wording used in the description of the present invention " includes " referring to existing described feature, whole Number, step, operation, element and/or assembly, but it is not excluded that existence or add one or Other features multiple, integer, step, operation, element, assembly and/or their group.

Those skilled in the art of the present technique are appreciated that unless otherwise defined, used herein all Term (includes technical term and scientific terminology), and have with art of the present invention is common Technical staff is commonly understood by identical meaning.Should also be understood that in such as general dictionary Those terms of definition, it should be understood that have and the meaning one in the context of prior art The meaning caused, and unless by specific definitions, otherwise will not be with idealization or the most formal containing Justice is explained.

Fig. 1 shows the image repair method based on side-play amount that one embodiment of the invention provides Schematic flow sheet, Fig. 2 shows showing of the image repair method that one embodiment of the invention provides It is intended to, shown in Fig. 1 and Fig. 2, the image repair method based on side-play amount of the present embodiment Comprise the steps:

101, by the image I in target image to be repaired and image library₁～I_w, pie graph picture stands Side C={I₀,I₁,…,I_w}；

102, to the image that each image division is partly overlapping r × r in image cube Block, it is thus achieved that the target image block of target image and the image block of image, r is the nature more than 1 Number.

In the present embodiment, can be to each image in image cube, with the most each picture Vegetarian refreshments is the upper left corner of block, divides an image into the image block of can be overlapping 8 × 8, it is thus achieved that mesh The target image block of logo image and the image block of image；The preferred r of the present embodiment is 8,10,16 Deng.

In the present embodiment, the position of target image block is by the center pixel of this target image block Point represents, the pixel value of target image block is the picture of the internal all pixels of this target image block The set of element value；The position of image block is represented by the central pixel point of this target image block, figure As the pixel value of block is the set of the pixel value of all pixels inside this target image block.

103, the leading side-play amount of the image block of known region in described target image is obtained；Institute If stating the similar image block of the image block to described known region that leading side-play amount is statistics The set of dry side-play amount；

In the present embodiment, described target image includes known region Φ and absent region Ω.

104, according to described leading side-play amount, use energy equation allocation strategy to described target In image, the pixel of absent region is repaired, and obtains the target image after repairing.

Such as: definition energy equation (equation below (2)) describes the quality of image repair, Solving energy equation, obtain optimum distributes a leading side-play amount for each unknown pixel Strategy, then known pixel values corresponding for side-play amount is filled up the unknown pixel of absent region.

It will be appreciated that during the image repair of the present embodiment, use and use known pixel values Repair unknown pixel, be not to repair target image block with known image block block.In the present embodiment Image block/the target image block of aforementioned division is overlapped, and each pixel occurs in some In individual block, it is not easily repaired based on image block.

The image repair method based on side-play amount of the present embodiment, by image cube, obtains Leading side-play amount, and then obtain the target image after repairing, the method can effectively describe mesh The structural information of logo image, can introduce again the extraneous information of image library, is conducive to keeping target The seriality of picture structure, improves the subjective visual quality repairing result, makes target image Repair structure more natural.

In actual applications, abovementioned steps 103 may particularly include the son not shown in following figure Step 1031 is to sub-step 1033:

1031, for each target image block in described known region, at described image The image block most like with this target image block is searched in cube；

Such as: use formula (1) to calculate the difference degree between two image blocks, described Image cube is searched minimum with each target image block difference degree as most like Image block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, during Ψ x represents the known region of described target image centered by pixel value x point Target image block, Ψ y be in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient, d (Ψ_x,Ψ_y) it is difference (Ψ_x,Ψ_y)。

1032, the image block that each target image block is most like with this target image block is obtained Side-play amount；

For example, for target image block Ψ_xThe most like image block Ψ found_y, group Become similar block to (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to described image to stand I in side_kImage, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁, k)。

1033, use statistical by described for selected part side-play amount combination in all side-play amounts Leading side-play amount.

Such as, all relative dimensional for all target image block of described known region are inclined Shifting amount, extracts the occurrence number leading skew of relative dimensional side-play amount composition more than predetermined threshold value Amount S={s₁,s₂,…,s_N}；

Or, all relative dimensional for all target image block of described known region are inclined Shifting amount, extracts N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

Correspondingly, the step 104 shown in earlier figures 1 is not shown in may also include following figure The sub-step 1041 gone out and sub-step 1042；

1041, formula (2) is used to determine each target pixel points x in described absent region Selected repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along three Pixel in the image cube that dimension side-play amount is pointed to；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s(L\left(x\right),L\left(y\right))+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\right(x))---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.

1042, for each target pixel points x in absent region, for this target pixel points x Distribute leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace This target pixel points x, it is thus achieved that the target image after reparation.

Said method can effectively describe the structural information of target image, can introduce again image library Extraneous information, make image repair structure more natural.

Use concrete example that image repair method based on side-play amount is carried out below in conjunction with figure Illustrating, the image repair method based on side-play amount of the present embodiment comprises the steps:

A01, to target image I to be repaired₀With the image I in image library c₁～I_w, composition Image cube C={I₀,I₁,…,I_w}；

Wherein, target image I₀In absent region be labeled as Ω, it is known that zone marker is Φ.

In the present embodiment, each target image all includes absent region Ω and known region Φ.

A02, to image cube C={I₀,I₁,…,I_wEach image in }, with the most each Pixel is the upper left corner of block, divides an image into the image block of 8*8 that can be overlapping, it is thus achieved that The target image block of target image and the image block of image.

A03, to each target image block Ψ in known region Φ_x, in image library c Find the most most like image block Ψ_y。

Wherein, target image block Ψ_xRepresent the target image block of pixel centered by x.Block Shown in the most following formula of similar measurement criterion (1), whereinIt it is gradient operator.

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k.---\left(1\right)$

It should be noted that the computational methods of formula (1) can be color value squared differences and (k=2), it is also possible to be absolute difference (k=1) other criterions, it is also possible to add gradient terms (β ≠ 0) I.e. | | Ψ_x-▽Ψ_y||。

Specifically, according to the value of coefficient of balance β, the difference degree seeking two image blocks can To be divided into:

When β=0, there is no the latter half of plus sige in formula (1), namely there is no gradient terms；

When β ≠ 0, be equivalent to add gradient terms.

According to the value of k in formula (1), the difference degree of two blocks is asked to be divided into:

As k=1, represent that this formula asks is the absolute value sum of the difference of pixel in block.

As k=2, represent that this formula asks is square sum of the difference of pixel in image block.

For example, color difference of two squares sum and the absolute value sum of formula (1) the inside are schematic Be described as follows: tile size is as a example by 2 × 2: a1～a4, b1～b4 are pixel values,

$k=1:\left|\right|\mathrm{\Ψ}a-\mathrm{\Ψ}b|{|}_1^1=|a1-b1|+|a2-b2|+|a3-b3|+|a4-b4|$

$k=2:\left|\right|\mathrm{\Ψ}a-\mathrm{\Ψ}b|{|}_2^2={(a1-b1)}^2+{(a2-b2)}^2+{(a3-b3)}^2+{(a4-b4)}^2$

A04, in step A03, the similar block found is to (Ψ_x,Ψ_y), x=(x might as well be set₁,y₁), And y=(x₂,y₂), and Ψ_yBelong to image I_k, then Ψ is calculated_x,Ψ_yBetween relative dimensional inclined Shifting amount is s=(x₂-x₁,y₂-y₁,k)。

The all of 3-D migration amount calculated in A05, statistic procedure A03 and step A04, Extract the most 3-D migration amount of occurrence number and amount to N number of, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

The value of generally N according to the amount of images in image cube can set in advance such as 40,60,80,100 etc..

A06, definition energy equation:

$E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s(L\left(x\right),L\left(y\right))+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\left(x\right)\right)---\left(2\right)$

Wherein, L represents a kind of method of salary distribution, shows the pixel being positioned at x in absent region Distribute the individual leading side-play amount of L (x), i.e. s_L(x).E (L) has weighed the quality of this method of salary distribution, The least quality of numerical value is the highest.N₄Being four neighborhoods, α is used for balancing smooth item E_sWith data item E_d。 E_s(L (x), L (y)) is smooth item.

Assume L (x)=i, L (y)=j, then the definition smoothing item is:

$E_s(i,j)=\left|\right|I(x+s_i)-I(x+s_j)|{|}_k^k+\mathrm{\β}||\▿I(x+s_i)-\▿I(x+s_j)|{|}_k^k,---\left(3\right)$

Formula (3) has been weighed pixel value corresponding to the side-play amount of adjacent two pixels distribution Structurally seriality, it is ensured that absent region internal repair result seriality structurally.

On the other hand, E (L (x)) is data item, is defined as:

Wherein, in formula (4)Represent the border of absent region.When unknown pixel is divided The side-play amount joined can not be allowed to find effective pixel points (i.e. falling at the pixel of known region) Time, data item gives maximum punishment, and (i.e.+∞ in formula (4) is exactly infinitely-great to one Energy), which ensure that final each unknown pixel has value to follow.

Pixel borderline for absent region, then when taking into full account reparation with outside boundaries Know the continuity degree of area pixel point, it is ensured that boundary transition is natural.

A07, use figure cut the minima of Algorithm for Solving energy equation, obtain the distribution side of optimum Case L.

A08, to each pixel in absent region, by x+s_L(x)The pixel of the pixel at place It is padded at x.

Just can make full use of inside image during repairing image according to above method Structural information, add image library extraneous information.In actual applications, have more Priori, by revising the definition of above-mentioned equation, can effectively utilize these priori and know Know, thus more tally with the actual situation and repair absent region more accurately.The introducing of image library is also Be process provides more motility, target image can be carried out minute surface symmetry transformation, Join in image library, to better profit from the self-similarity of image；For video, permissible Consecutive frame is joined in image library, it is provided that abundant inter-frame information；Can also use relevant Image retrieval technologies, make the image in image library higher with the degree of correlation of target image, Thus obtain more excellent reparation result.

Fig. 3 shows the image fixing apparatus based on side-play amount that another embodiment of the present invention provides Structural representation, as it is shown on figure 3, the image fixing apparatus based on side-play amount of the present embodiment Including: image cube Component units 31, image block division unit 32, leading side-play amount obtain single Unit 33 and reparation unit 34；

Wherein, image cube Component units 31 is for by target image to be repaired and image library In image, pie graph picture cube；

Image block division unit 32 is used for each image division in image cube being part The image block of overlapping r × r, it is thus achieved that the target image block of target image and the image block of image, R is the natural number more than 1；

Leading side-play amount acquiring unit 33 is for obtaining the figure of known region in described target image Leading side-play amount as block；Described leading side-play amount is the figure with described known region of statistics The set of some side-play amounts of the image block that picture block is similar；

Repair unit 34 for according to described leading side-play amount, employing energy equation allocation strategy The pixel of absent region in described target image is repaired, obtains the target after repairing Image；

Described target image includes known region and absent region.

In a kind of concrete implementation mode, aforesaid leading side-play amount acquiring unit 33 can have Body is used for

For each target image block in described known region, in described image cube Search the image block most like with this target image block；

Obtain the skew of each target image block image block most like with this target image block Amount；

Use statistical by described for selected part side-play amount combination in all side-play amounts leading inclined Shifting amount.

For example, leading side-play amount acquiring unit 33 specifically for

Use formula (1) to calculate the difference degree between two image blocks, stand at described image Side search minimum with each target image block difference degree as most like image Block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, Ψ_xRepresent in the known region of described target image point centered by pixel value x Target image block, Ψ_yFor in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient；

For target image block Ψ_xThe most like image block Ψ found_y, form similar block pair (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to the I in described image cube_k Image, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁,k)；

For all relative dimensional side-play amounts of all target image block of described known region, Extract the occurrence number leading side-play amount of relative dimensional side-play amount composition more than predetermined threshold value S={s₁,s₂,…,s_N}；

Or,

For all relative dimensional side-play amounts of all target image block of described known region, Extract N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

In alternatively possible implementation, described reparation unit 34 can be specifically for,

Formula (2) is used to determine in described absent region selected by each target pixel points x Repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along 3-D migration Pixel in the image cube that amount is pointed to；

For each target pixel points x in absent region, distribute one for this target pixel points x Individual leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace this target Pixel x, it is thus achieved that the target image after reparation, described target pixel points is target image block Central pixel point, pixel is the central pixel point of image block；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s(L\left(x\right),L\left(y\right))+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\left(x\right)\right)---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.

The image fixing apparatus based on side-play amount of the present embodiment, by image cube Component units Set up image cube, and then obtain leading side-play amount by leading side-play amount acquiring unit, and then Repairing unit and obtain the target image after repairing, this device can effectively describe the knot of target image Structure information, can introduce again the extraneous information of image library, is conducive to keeping the company of target image structure Continuous property, improves the subjective visual quality repairing result, makes target image repair structure more certainly So.

Through the above description of the embodiments, those skilled in the art it can be understood that Can be realized by hardware to the present invention, it is also possible to add the general hardware platform of necessity by software Mode realize.Based on such understanding, technical scheme can be with software product Form embody, this software product can be stored in a non-volatile memory medium (can To be CD-ROM, USB flash disk, portable hard drive etc.) in, including some instructions with so that one Platform computer equipment (can be personal computer, server, or the network equipment etc.) performs Method described in each embodiment of the present invention.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, attached Module or flow process in figure are not necessarily implemented necessary to the present invention.

It will be appreciated by those skilled in the art that the module in the system in embodiment can be according to reality Execute example description to carry out being distributed in the system of embodiment, it is also possible to carry out respective change and be positioned at difference In one or more systems of the present embodiment.The module of above-described embodiment can merge into one Module, it is also possible to be further split into multiple submodule.

The above is only the some embodiments of the present invention, it is noted that lead for this technology For the those of ordinary skill in territory, under the premise without departing from the principles of the invention, it is also possible to make Some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention.

Claims (10)

1. an image repair method based on side-play amount, it is characterised in that including:

By the image in target image to be repaired and image library, pie graph picture cube；

To the image block that each image division is partly overlapping r × r in image cube, obtain Obtaining target image block and the image block of image of target image, r is the natural number more than 1；

Obtain the leading side-play amount of the image block of known region in described target image；Described master Lead the similar image block of the image block to described known region that side-play amount is statistics some partially The set of shifting amount；

According to described leading side-play amount, use energy equation allocation strategy to described target image The pixel of middle absent region is repaired, and obtains the target image after repairing；

Described target image includes known region and absent region.

Method the most according to claim 1, it is characterised in that obtain described target figure The leading side-play amount of the image block of known region in Xiang, step include:

For each target image block in described known region, in described image cube Search the image block most like with this target image block；

Obtain the skew of each target image block image block most like with this target image block Amount；

Use statistical by described for selected part side-play amount combination in all side-play amounts leading inclined Shifting amount.

Method the most according to claim 2, it is characterised in that for described known district Each target image block in territory, searches and this target image block in described image cube Most like image block, step include:

Use formula (1) to calculate the difference degree between two image blocks, stand at described image Side search minimum with each target image block difference degree as most like image Block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, Ψ_xRepresent in the known region of described target image point centered by pixel value x Target image block, Ψ_yFor in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient.

Method the most according to claim 3, it is characterised in that obtain each target The side-play amount of the image block that image block is most like with this target image block, step include:

For target image block Ψ_xThe most like image block Ψ found_y, form similar block pair (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to the I in described image cube_k Image, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁,k)。

Method the most according to claim 4, it is characterised in that employing statistical will In all side-play amounts selected part side-play amount combine described leading side-play amount, step include:

For all relative dimensional side-play amounts of all target image block of described known region, Extract the occurrence number leading side-play amount of relative dimensional side-play amount composition more than predetermined threshold value S={s₁,s₂,…,s_N}；

Or,

For all relative dimensional side-play amounts of all target image block of described known region, Extract N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

Method the most according to claim 1, it is characterised in that described according to described master Lead side-play amount, use energy equation allocation strategy to the picture of absent region in described target image Vegetarian refreshments is repaired, obtain repair after target image, step include:

Formula (2) is used to determine in described absent region selected by each target pixel points x Repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along 3-D migration Pixel in the image cube that amount is pointed to；

For each target pixel points x in absent region, distribute one for this target pixel points x Individual leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace this target Pixel x, it is thus achieved that the target image after reparation；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s\left(L\right(x),L(y\left)\right)+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\right(x\left)\right)---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.

7. an image fixing apparatus based on side-play amount, it is characterised in that including:

Image cube Component units, for by the figure in target image to be repaired and image library Picture, pie graph picture cube；

Image block division unit, being used for each image division in image cube is part The image block of overlapping r × r, it is thus achieved that the target image block of target image and the image block of image, R is the natural number more than 1；

Leading side-play amount acquiring unit, for obtaining the figure of known region in described target image Leading side-play amount as block；Described leading side-play amount is the figure with described known region of statistics The set of some side-play amounts of the image block that picture block is similar；

Repair unit, for according to described leading side-play amount, use energy equation allocation strategy The pixel of absent region in described target image is repaired, obtains the target after repairing Image；

Described target image includes known region and absent region.

Device the most according to claim 7, it is characterised in that leading side-play amount obtains Unit, specifically for

For each target image block in described known region, in described image cube Search the image block most like with this target image block；

Obtain the skew of each target image block image block most like with this target image block Amount；

Use statistical by described for selected part side-play amount combination in all side-play amounts leading inclined Shifting amount.

Device the most according to claim 7, it is characterised in that leading side-play amount obtains Unit, specifically for

Use formula (1) to calculate the difference degree between two image blocks, stand at described image Side search minimum with each target image block difference degree as most like image Block；

$d({\mathrm{\Ψ}}_x,{\mathrm{\Ψ}}_y)=\left|\right|{\mathrm{\Ψ}}_x-{\mathrm{\Ψ}}_y|{|}_k^k+\mathrm{\β}||\▿{\mathrm{\Ψ}}_x-\▿{\mathrm{\Ψ}}_y|{|}_k^k$ Formula (1)

Wherein, Ψ_xRepresent in the known region of described target image point centered by pixel value x Target image block, Ψ_yFor in described image cube centered by pixel value y point image block,Being gradient operator, β represents the color item in equation of equilibrium (1) and the balance of gradient terms Coefficient；

For target image block Ψ_xThe most like image block Ψ found_y, form similar block pair (Ψ_x,Ψ_y), if x=is (x₁,y₁), y=(x₂,y₂), and Ψ_yBelong to the I in described image cube_k Image, then Ψ_x, Ψ_yBetween relative dimensional side-play amount be s=(x₂-x₁,y₂-y₁,k)；

For all relative dimensional side-play amounts of all target image block of described known region, Extract the occurrence number leading side-play amount of relative dimensional side-play amount composition more than predetermined threshold value S={s₁,s₂,…,s_N}；

Or,

For all relative dimensional side-play amounts of all target image block of described known region, Extract N number of relative dimensional side-play amount that occurrence number is most, the leading side-play amount of composition S={s₁,s₂,…,s_N}。

Device the most according to claim 7, it is characterised in that described reparation unit, Specifically for

Formula (2) is used to determine in described absent region selected by each target pixel points x Repairing pixel point x+s_L(x), described repairing pixel point is that target pixel points is along 3-D migration Pixel in the image cube that amount is pointed to；

For each target pixel points x in absent region, distribute one for this target pixel points x Individual leading side-play amount s_L(x), by pixel x+s in described image cube_L(x)Value replace this target Pixel x, it is thus achieved that the target image after reparation, described target pixel points is target image block Central pixel point, pixel is the central pixel point of image block；

Wherein, $E\left(L\right)=\underset{(x,y)\∈N_4}{\Σ}{E}_s\left(L\right(x),L(y\left)\right)+\mathrm{\α}\underset{x\∈\mathrm{\Ω}}{\Σ}{E}_d\left(L\right(x\left)\right)---\left(2\right)$

L represents a kind of method of salary distribution, shows that the pixel to being positioned at x in absent region distributes L (x) individual leading side-play amount s_L(x), E (L) is for weighing the quality of the described method of salary distribution, N₄ Being four neighborhoods, α represents for balancing smooth item E_sWith data item E_dCoefficient of balance, E_s(L (x), L (y)) is smooth item, E_d(L (x)) is data item.