CN103813056A - Image stabilization method and device - Google Patents
Image stabilization method and device Download PDFInfo
- Publication number
- CN103813056A CN103813056A CN201210463920.8A CN201210463920A CN103813056A CN 103813056 A CN103813056 A CN 103813056A CN 201210463920 A CN201210463920 A CN 201210463920A CN 103813056 A CN103813056 A CN 103813056A
- Authority
- CN
- China
- Prior art keywords
- frame image
- point
- image
- vector
- current frame
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Landscapes
- Image Analysis (AREA)
- Studio Devices (AREA)
- Television Systems (AREA)
Abstract
The invention discloses an image stabilization method and an image stabilization device. The image stabilization method comprises the steps of: determining a specified feature point matched with the feature of the feature point of a current reference frame image from the feature points of a current frame image, wherein the feature point is the point in the image meeting preset feature conditions; determining the motion vector estimate point of the current frame image to be the other specified feature points in all specified feature points besides the specified feature point in a local motion image block, wherein the local motion image block is the image block in the current frame image including the image of a motion object; determining the compensational motion vector of the current frame image based on the coordinate of the motion vector estimate point in the current frame image and the coordinate of the feature point matched with the feature of the motion vector estimate point in the current reference frame image; performing image stabilization compensation to the current frame image based on the compensational motion vector. According to the method and the device provided by the invention, the problem of poor image stabilization effect is solved.
Description
Technical field
The present invention relates to video field, relate in particular to a kind of digital image stabilization method and device.
Background technology
The development experience of Video Stabilization technology mechanical steady picture, optics surely look like and three megastages of electronic steady image.Machinery similarly is surely to utilize stabilized platform to compensate the relative motion of camera system on pedestal and realize the stable of image sequence.Optics similarly is surely to utilize the compensating motion of some elements in optical system to realize the stable of image sequence.Compare with optics image stabilization system with traditional machinery, electronic steady image system has that volume is little, lightweight, easy operating, flexibility is strong, energy consumption is low and the advantage such as high-intelligentization processing in real time, so electronic image stabilizing is the important directions that surely looks like technical development.
In prior art, conventional electronic image stabilization method is to determine the motion vector of current frame image with respect to current reference frame image based on Gray Projection method, i.e. global motion vector, by global motion vector motion vector by way of compensation.In a lot of occasions, current frame image with respect to current reference frame image substantially without convergent-divergent, therefore ignore compensation contraction coefficient s, compensating motion vector only comprises compensation anglec of rotation horizontal component a, compensation anglec of rotation vertical component b, level compensating motion vector dx and these four kinds of vectors of VCP motion vector dy.
Adopt following formula to carry out steady picture compensation to current frame image based on this compensating motion vector:
α=tan
-1(b/a)；
Wherein, α is the compensation anglec of rotation;
for the coordinate of a certain pixel in current frame image,
for this pixel coordinate in image after steady picture compensation.
Visible, compensating motion vector surely plays conclusive effect as effect to video image.But, because actual environment complexity is various, in video image, may exist Moving Objects image, therefore, by the current frame image of determining based on Gray Projection method, with respect to the global motion vector of current reference frame image, motion vector is not accurate enough by way of compensation, and then reduced the Stability and veracity that successive image compensates, surely look like effect poor.
Summary of the invention
The embodiment of the present invention provides a kind of digital image stabilization method and device, surely looks like the poor problem of effect in order to solve the image existing in prior art.
The embodiment of the present invention provides a kind of digital image stabilization method, comprising:
From the characteristic point of current frame image, determine and the specific characteristic point of the characteristic point characteristic matching of current reference frame image, described characteristic point is the point that meets default characteristic condition in image;
Determine that the estimation of motion vectors point of described current frame image is in all specific characteristic points, other specific characteristic point the specific characteristic point in local motion image block; Described local motion image block is the image block that comprises Moving Objects image in described current frame image;
The coordinate of the described estimation of motion vectors point based in described current frame image, and in described current reference frame image with the coordinate of the characteristic point of described estimation of motion vectors point characteristic matching, determine the compensating motion vector of described current frame image;
Based on described compensating motion vector, described current frame image is carried out to steady picture compensation.
The embodiment of the present invention provides a kind of steady picture device, comprising:
Matching unit, for determining from the characteristic point of current frame image and the specific characteristic point of the characteristic point characteristic matching of current reference frame image, described characteristic point is the point that meets default characteristic condition in image;
The first determining unit, is all specific characteristic points for the estimation of motion vectors point of determining described current frame image, other specific characteristic point the specific characteristic point in local motion image block; Described local motion image block is the image block that comprises Moving Objects image in described current frame image;
The second determining unit, for the coordinate of the described estimation of motion vectors point based on described current frame image, with in described current reference frame image with the coordinate of the characteristic point of described estimation of motion vectors point characteristic matching, determine the compensating motion vector of described current frame image;
Compensating unit, for based on described compensating motion vector, carries out steady picture compensation to described current frame image.
Beneficial effect of the present invention comprises:
The method that the embodiment of the present invention provides, in the time carrying out the screening of estimation of motion vectors point, remove the specific characteristic point in the local motion image block that comprises Moving Objects image in current frame image, the point using other specific characteristic point as estimation of motion vectors, can the compensating motion vector of image be made more accurately and being estimated, and then improved the Stability and veracity of successive image compensation, surely look like effect better.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for specification, is used from explanation the present invention with the embodiment of the present invention one, is not construed as limiting the invention.In the accompanying drawings:
The flow chart of the digital image stabilization method that Fig. 1 provides for the embodiment of the present invention;
The detail flowchart of the digital image stabilization method that Fig. 2 provides for the embodiment of the present invention;
The structural representation of the steady picture device that Fig. 3 provides for the embodiment of the present invention.
Embodiment
Improve in order to provide the implementation that image surely looks like effect, the embodiment of the present invention provides a kind of digital image stabilization method and device, below in conjunction with Figure of description, the preferred embodiments of the present invention are described, be to be understood that, preferred embodiment described herein only, for description and interpretation the present invention, is not intended to limit the present invention.And in the situation that not conflicting, the feature in embodiment and embodiment in the application can combine mutually.
The embodiment of the present invention provides a kind of digital image stabilization method, comprising:
The coordinate of step 103, this estimation of motion vectors point based in this current frame image, and in this current reference frame image with the coordinate of the characteristic point of this estimation of motion vectors point characteristic matching, determine the compensating motion vector of this current frame image.
Wherein, in step 103, the coordinate of the estimation of motion vectors point based in current frame image, with in current reference frame image with the coordinate of the characteristic point of estimation of motion vectors point characteristic matching, a kind of random sampling unification algorism that specifically can adopt the embodiment of the present invention to propose is determined the method for the compensating motion vector of current frame image.
Preferably, before execution step 104, reliability to the compensating motion vector of determining in step 103 judges, specifically can be by judging whether the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image meets the first default condition of similarity and realize the reliability judgement to compensating motion vector.The absolute difference of the corresponding vector that the various vectors that this first default condition of similarity can comprise for the compensating motion vector of current frame image comprise with the compensating motion vector of the previous frame image of current frame image respectively is all less than corresponding threshold value, can be also other condition of similarity.
In the time determining that the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image meets this first default condition of similarity, the reliability of compensating motion vector of determining current frame image is high, execution step 104, carries out steady picture compensation to current frame image; In the time determining that the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image does not meet this first default condition of similarity, the reliability of compensating motion vector of determining current frame image is low, do not perform step 104, cancel current frame image is carried out to steady picture compensation.
But, only by the first default condition of similarity, the reliability of compensating motion vector being judged, judged result may be not accurate enough.Therefore in the time determining that the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image does not meet this first default condition of similarity, directly cancelling current frame image is carried out to scheme that steady picture compensates is not scheme preferably.
Preferably, can be in the time determining that the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image does not meet this first default condition of similarity, carry out follow-up judgement by other condition again, determine whether to cancel current frame image is carried out to steady picture compensation.
And, in the time determining that the compensating motion vector of the compensating motion vector of current frame image and the previous frame image of current frame image does not meet the first default condition of similarity, upgrading current reference frame image is the next frame image of current frame image or current frame image, as the reference frame image of next frame image.Also can current reference frame image when being greater than frequency threshold value with reference to the number of times of two field picture, upgrading current reference frame image is the next frame image of current frame image or current frame image.
Above-mentioned digital image stabilization method, ignore compensation contraction coefficient s, be applicable to current frame image with respect to current reference frame image substantially without the occasion of convergent-divergent, can surely look like the output image of monitor video etc., the picture format of acquiescence is YUV color space form, if while carrying out video acquisition, the video image obtaining is not YUV color space form, need to carry out format conversion.And in the time carrying out video image acquisition, should be according to surely as the size of compensation range, image surrounding being expanded to collection.Below in conjunction with accompanying drawing, method provided by the invention and device are described in detail with specific embodiment.
The detail flowchart that Figure 2 shows that the digital image stabilization method that the embodiment of the present invention provides, specifically comprises following treatment step:
Wherein, characteristic point is specifically as follows the characteristic points such as angle point, sift characteristic point or surf characteristic point.Here be specifically described as an example of angle point example.
Current frame image and current reference frame image are carried out to Corner Detection, and respectively current frame image and current reference frame image are carried out to pyramid space delamination, calculate after the characteristic vector of each angle point, carry out the coupling of angle point according to characteristic vector, from the angle point of current frame image, determine and the appointment angle point of the corners Matching of current reference frame image, and record the successfully right coordinate of angle point of coupling.Concrete Corner Detection matching process is all to carry out under the gray level image of current frame image and current reference frame image, preferably, can be carrying out, before Corner Detection, the gray level image of current frame image is carried out to noise reduction process, this part is prior art, therefore be not described in detail in this.
Under reference frame image is not carried out more news, the detection of current reference frame image angle point and characteristic vector are calculated and are only once preserved.
Preferably, current frame image can be divided into the image block of an at least the three predetermined number homalographic, choose and comprise specific characteristic and put a fairly large number of a 3rd predetermined number image block, determine global level motion vector based on Gray Projection method, the local horizontal motion vector of each image block in overall situation vertical motion vector and the image block that is selected, partial vertical motion vector, determine that local motion image block is that in a 3rd predetermined number image block, the absolute difference of local horizontal motion vector and global level motion vector is greater than horizontal difference threshold, and/or partial vertical motion vector and the absolute difference of overall vertical motion vector are greater than the image block of vertical difference threshold.Wherein, global level motion vector is the horizontal motion vector of current frame image with respect to current reference frame image; Overall situation vertical motion vector is the vertical motion vector of current frame image with respect to current reference frame image; Local horizontal motion vector is that the image block of current frame image is with respect to the horizontal motion vector of the image block of same position in current reference frame image; Partial vertical motion vector is that the image block of current frame image is with respect to the vertical motion vector of the image block of same position in current reference frame image.
Gray Projection method is to utilize ranks intensity profile to carry out the motion estimation algorithm of computing cross-correlation.This algorithm utilizes the ranks Gray Projection curve of image to do computing cross-correlation to obtain the motion vector of image.Below take calculate current frame image with respect to the vertical motion vector of current reference frame image as example, be illustrated concrete computational process.
First, respectively current frame image and current reference frame image are carried out to projection, projection formula is:
Cgray(j)=∑Cur(i,j)；
Cm=[∑Cgray(i,j)]/NC；
Cout(j)=Cgray(j)-Cm。
Wherein, Cgray (j) is the gray value sum of the pixel of j row;
Cur (i, j) is the gray value of the pixel of the capable j row of i;
Cm is the mean value of the gray value sum of the pixel of all row;
∑ Cgray (i, j) be the pixel of all row gray value sum and value;
NC is total columns;
Cout (j) is the projection value of j row.
Then, then to by current frame image being carried out to the projection value Cout that projection obtains
c(j), with by current reference frame image being carried out to the projection value Cout that projection obtains
r(j) carry out cross-correlation calculation, the computing formula of cross-correlation function C (v) is:
Wherein, v is vertical motion vector;
M is the window of cross-correlation calculation search, and 1≤v≤2m+1.
Make cross-correlation function C (v) value a hour corresponding vertical motion vector v be the vertical motion vector of current frame image with respect to current reference frame image, overall vertical motion vector.
Adopt said method can determine successively global level motion vector and the image block that is selected in local horizontal motion vector, the partial vertical motion vector of each image block.
The coordinate of step 204, estimation of motion vectors point based in current frame image, with in current reference frame image with the coordinate of the characteristic point of estimation of motion vectors point characteristic matching, the compensating motion vector of determining current frame image by random sampling unification algorism, is specially:
A, current frame image is divided into the image-region of at least the first predetermined number homalographic.
B, contain at least the second predetermined number for the first predetermined number the image-region of estimation of motion vectors point in each image-region, employing following steps are determined the consistent point motion vector in region of this image-region:
Determine the point motion vector of the each estimation of motion vectors point in this image-region; For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity; Determine the point motion vector of designated movement vector estimation point corresponding to the maximum of quantity of the each self-corresponding consistent point of each designated movement vector estimation point, as the consistent point motion vector in region of this image-region.
Preferably, if more than the first predetermined number, therefrom choosing estimation of motion vectors, the image-region of the estimation of motion vectors point that contains at least the second predetermined number puts the individual image-region of the first more predetermined number.Due to the coordinate of estimation of motion vectors point in current frame image
With in current reference frame image with the coordinate of the characteristic point of this estimation of motion vectors point characteristic matching
Meet following relationship:
Wherein, α ' is the anglec of rotation; Dx' is horizontal motion vector; Dy ' is vertical motion vector.By α '=tan
-1(b'/a') substitution obtains:
Wherein, a' is anglec of rotation horizontal component; B ' is anglec of rotation vertical component.
Can determine the point motion vector of each estimation of motion vectors point based on above-mentioned formula
The absolute difference of the corresponding vector that the second default condition of similarity can comprise with the point motion vector of designated movement vector estimation point respectively for the various vectors that the point motion vector of estimation of motion vectors point comprises is all less than corresponding threshold value, can be also other condition of similarity.
C, for every kind of vector in the consistent point motion vector in the first predetermined number region, adopt following steps determine this kind of compensation vector that vector is corresponding:
For the each specifies vector in this kind of vector, determine the quantity of the consistent vector of this specifies vector in other each vector, wherein, specifies vector is the vector of the 3rd predetermined number chosen from the first predetermined number this kind of vector, and the consistent vector of this specifies vector is the vector that meets the 3rd default condition of similarity with this specifies vector; Determine the mean value of the consistent vector of specifies vector corresponding to the maximum of quantity of the each self-corresponding consistent vector of each specifies vector, as this kind of compensation vector that vector is corresponding.
D, based on compensation vector corresponding to various vectors, obtain the compensating motion vector of current frame image.Formed the compensating motion vector of current frame image by four kinds of compensation vector corresponding to vector
When the absolute difference of determining the corresponding vector that various vectors that the compensating motion vector of current frame image comprises comprise with the compensating motion vector of the previous frame image of current frame image is not respectively, while being all less than corresponding threshold value, to enter step 206; In the time determining that the absolute difference of the corresponding vector that various vectors that the compensating motion vector of current frame image comprises comprise with the compensating motion vector of the previous frame image of current frame image respectively is all less than corresponding threshold value, enter step 207.
In the time determining that the each self-corresponding region of image-region of the estimation of motion vectors point that the first predetermined number contains at least the second predetermined number is unanimously put maximum in quantity and is not less than amount threshold, enter step 207; In the time determining that the each self-corresponding region of image-region of the estimation of motion vectors point that the first predetermined number contains at least the second predetermined number is unanimously put maximum in quantity and is less than amount threshold, finish this flow process, current frame image is not carried out to steady picture and compensate.
If while determining the compensating motion vector of current frame image, be not to determine by the random sampling unification algorism in step 204, can not directly obtain in this step the each self-corresponding region of image-region and unanimously put quantity, now, need to calculate in this step, computational methods, with in step 204, are not described in detail in this.
And, should not exceed maximum compensation range to the steady picture compensation of current frame image.
Obtain in scene at some video images, some factors such as illumination can constantly change, and therefore need reference frame image to carry out real-time update.Be specifically as follows:
When the absolute difference of determining the corresponding vector that various vectors that the compensating motion vector of current frame image comprises comprise with the compensating motion vector of the previous frame image of current frame image is not respectively while being all less than corresponding threshold value, or, when current reference frame image is when being greater than frequency threshold value with reference to the number of times of two field picture, upgrading current reference frame image is the next frame image of current frame image or current frame image, as the reference frame image of next frame image.And, in the time of to upgrade current reference frame image be current frame image next frame image, can not carry out steady picture operation to the next frame image of current frame image, directly next frame image is again carried out to steady picture operation.
The method that adopts the embodiment of the present invention to provide, in the time carrying out the screening of estimation of motion vectors point, remove the specific characteristic point in the local motion image block that comprises Moving Objects image in current frame image, the point using other specific characteristic point as estimation of motion vectors, can the compensating motion vector of image be made more accurately and being estimated, and the compensating motion vector estimating is further judged to its reliability, determine whether current frame image to compensate according to reliability, and then improved the Stability and veracity of successive image compensation, surely look like effect better.
Based on same inventive concept, the digital image stabilization method providing according to the above embodiment of the present invention, correspondingly, another embodiment of the present invention also provides steady picture device, and apparatus structure schematic diagram as shown in Figure 3, specifically comprises:
The first determining unit 302, is all specific characteristic points for the estimation of motion vectors point of determining this current frame image, other specific characteristic point the specific characteristic point in local motion image block; This local motion image block is the image block that comprises Moving Objects image in this current frame image;
The second determining unit 303, for the coordinate of this estimation of motion vectors point based on this current frame image, and in this current reference frame image with the coordinate of the characteristic point of this estimation of motion vectors point characteristic matching, determine the compensating motion vector of this current frame image;
Compensating unit 304, for based on this compensating motion vector, carries out steady picture compensation to this current frame image.
Further, compensating unit 304, be also the later image of the second two field picture for working as this current frame image, before this current frame image being carried out to steady picture compensation, determine that the compensating motion vector of the compensating motion vector of this current frame image and the previous frame image of this current frame image meets the first default condition of similarity.
Further, compensating unit 304, also, in the time determining that the compensating motion vector of the compensating motion vector of this current frame image and the previous frame image of this current frame image does not meet this first default condition of similarity, this current frame image is divided into the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of this estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, employing following steps determine that the region of this image-region unanimously puts quantity:
Determine the point motion vector of the each estimation of motion vectors point in this image-region; For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity; Determine the maximum of the quantity of each self-corresponding this consistent point of each designated movement vector estimation point, as unanimously putting quantity in the region of this image-region;
When each self-corresponding this region of image-region of this estimation of motion vectors point that contains at least the second predetermined number when this first predetermined number is unanimously put maximum in quantity and is less than amount threshold, cancel and this current frame image is carried out to steady picture compensate; When each self-corresponding this region of image-region of this estimation of motion vectors point that contains at least the second predetermined number when this first predetermined number is unanimously put maximum in quantity and is not less than amount threshold, based on this compensating motion vector, this current frame image is carried out to steady picture compensation.
Further, this surely looks like device, also comprises:
Updating block 305, for this current frame image being carried out to steady picture compensation in cancellation, or after this current frame image is carried out to steady picture compensation, in the time determining that the compensating motion vector of the compensating motion vector of this current frame image and the previous frame image of this current frame image does not meet this first default condition of similarity, upgrade the next frame image that this current reference frame image is this current frame image or this current frame image; Or in cancellation, this current frame image is carried out to steady picture compensation, or after this current frame image is carried out to steady picture compensation, when this current reference frame image is when being greater than frequency threshold value with reference to the number of times of two field picture, upgrade the next frame image that this current reference frame image is this current frame image or this current frame image.
Further, the second determining unit 303, specifically for determining the compensating motion vector of this current frame image by random sampling unification algorism.
Further, the second determining unit 303, specifically for being divided into this current frame image the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of this estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, adopts following steps to determine the consistent point motion vector in region of this image-region:
Determine the point motion vector of the each estimation of motion vectors point in this image-region; For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity; Determine the point motion vector of designated movement vector estimation point corresponding to the maximum of quantity of each self-corresponding this consistent point of each designated movement vector estimation point, as the consistent point motion vector in region of this image-region;
For every kind of vector in this first predetermined number consistent point motion vector in this region, adopt following steps to determine this kind of compensation vector that vector is corresponding:
For the each specifies vector in this kind of vector, determine the quantity of the consistent vector of this specifies vector in other each vector, wherein, specifies vector is the vector of the 3rd predetermined number chosen from this first predetermined number this kind of vector, and the consistent vector of this specifies vector is the vector that meets the 3rd default condition of similarity with this specifies vector; Determine the mean value of the consistent vector of specifies vector corresponding to the maximum of quantity of each self-corresponding this consistent vector of each specifies vector, as this kind of compensation vector that vector is corresponding;
Based on compensation vector corresponding to various vectors, obtain the compensating motion vector of this current frame image.
Further, the first determining unit 302, specifically for being divided into this current frame image an at least the three predetermined number image block; Determine that this local motion image block is that in a 3rd predetermined number image block, the absolute difference of local horizontal motion vector and global level motion vector is greater than horizontal difference threshold, and/or partial vertical motion vector and the absolute difference of overall vertical motion vector are greater than the image block of vertical difference threshold; The image block that this local horizontal motion vector is this current frame image is with respect to the horizontal motion vector of the image block of same position in this current reference frame image; This global level motion vector is the horizontal motion vector of this current frame image with respect to this current reference frame image; The image block that this partial vertical motion vector is this current frame image is with respect to the vertical motion vector of the image block of same position in this current reference frame image; This overall situation vertical motion vector is the vertical motion vector of this current frame image with respect to this current reference frame image.
The function of above-mentioned each module can, corresponding to the respective handling step in flow process shown in Fig. 1 or Fig. 2, not repeat them here.
In sum, the scheme that the embodiment of the present invention provides is determined and the specific characteristic point of the characteristic point characteristic matching of current reference frame image from the characteristic point of current frame image, and this characteristic point is the point that meets default characteristic condition in image; Determine that the estimation of motion vectors point of this current frame image is in all specific characteristic points, other specific characteristic point the specific characteristic point in local motion image block; This local motion image block is the image block that comprises Moving Objects image in this current frame image; The coordinate of this estimation of motion vectors point based in this current frame image, and in this current reference frame image with the coordinate of the characteristic point of this estimation of motion vectors point characteristic matching, determine the compensating motion vector of this current frame image; Based on this compensating motion vector, this current frame image is carried out to steady picture compensation.Adopt scheme provided by the invention, solved the problem that image surely looks like weak effect.
The application's embodiment provides surely can realize by computer program as device.Those skilled in the art should be understood that; above-mentioned Module Division mode is only the one in numerous Module Division modes; if be divided into other modules or do not divide module, as long as surely there is above-mentioned functions as device, all should be within the application's protection range.
The application is with reference to describing according to flow chart and/or the block diagram of the method for the embodiment of the present application, equipment (system) and computer program.Should understand can be by the flow process in each flow process in computer program instructions realization flow figure and/or block diagram and/or square frame and flow chart and/or block diagram and/or the combination of square frame.Can provide these computer program instructions to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing device to produce a machine, the instruction that makes to carry out by the processor of computer or other programmable data processing device produces the device for realizing the function of specifying at flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame.
These computer program instructions also can be stored in energy vectoring computer or the computer-readable memory of other programmable data processing device with ad hoc fashion work, the instruction that makes to be stored in this computer-readable memory produces the manufacture that comprises command device, and this command device is realized the function of specifying in flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, make to carry out sequence of operations step to produce computer implemented processing on computer or other programmable devices, thereby the instruction of carrying out is provided for realizing the step of the function of specifying in flow process of flow chart or multiple flow process and/or square frame of block diagram or multiple square frame on computer or other programmable devices.
Obviously, those skilled in the art can carry out various changes and modification and not depart from the spirit and scope of the present invention the present invention.Like this, if within of the present invention these are revised and modification belongs to the scope of the claims in the present invention and equivalent technologies thereof, the present invention is also intended to comprise these changes and modification interior.
Claims (14)
1. a digital image stabilization method, is characterized in that, comprising:
From the characteristic point of current frame image, determine and the specific characteristic point of the characteristic point characteristic matching of current reference frame image, described characteristic point is the point that meets default characteristic condition in image;
Determine that the estimation of motion vectors point of described current frame image is in all specific characteristic points, other specific characteristic point the specific characteristic point in local motion image block; Described local motion image block is the image block that comprises Moving Objects image in described current frame image;
The coordinate of the described estimation of motion vectors point based in described current frame image, and in described current reference frame image with the coordinate of the characteristic point of described estimation of motion vectors point characteristic matching, determine the compensating motion vector of described current frame image;
Based on described compensating motion vector, described current frame image is carried out to steady picture compensation.
2. the method for claim 1, is characterized in that, when described current frame image is the later image of the second two field picture, before described current frame image being carried out to steady picture compensation, also comprises:
The compensating motion vector of determining the compensating motion vector of described current frame image and the previous frame image of described current frame image meets the first default condition of similarity.
3. method as claimed in claim 2, is characterized in that, also comprises:
In the time determining that the compensating motion vector of the compensating motion vector of described current frame image and the previous frame image of described current frame image does not meet the described first default condition of similarity, described current frame image is divided into the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of the described estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, employing following steps determine that the region of this image-region unanimously puts quantity:
Determine the point motion vector of the each estimation of motion vectors point in this image-region;
For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity;
Determine the maximum of the quantity of the each self-corresponding described consistent point of each designated movement vector estimation point, unanimously put quantity as the region of this image-region;
When the each self-corresponding described region of image-region of the described estimation of motion vectors point that contains at least the second predetermined number when described the first predetermined number is unanimously put maximum in quantity and is less than amount threshold, cancel and described current frame image is carried out to steady picture compensate;
When the each self-corresponding described region of image-region of the described estimation of motion vectors point that contains at least the second predetermined number when described the first predetermined number is unanimously put maximum in quantity and is not less than amount threshold, based on described compensating motion vector, described current frame image is carried out to steady picture compensation.
4. method as claimed in claim 3, is characterized in that, described current frame image is carried out to steady picture compensation cancelling, or after described current frame image is carried out to steady picture compensation, also comprises:
In the time determining that the compensating motion vector of the compensating motion vector of described current frame image and the previous frame image of described current frame image does not meet the described first default condition of similarity, upgrade the next frame image that described current reference frame image is described current frame image or described current frame image; Or
When described current reference frame image is when being greater than frequency threshold value with reference to the number of times of two field picture, upgrade the next frame image that described current reference frame image is described current frame image or described current frame image.
5. the method for claim 1, is characterized in that, determines the compensating motion vector of described current frame image, is specially:
Determine the compensating motion vector of described current frame image by random sampling unification algorism.
6. method as claimed in claim 5, is characterized in that, determines the compensating motion vector of described current frame image by random sampling unification algorism, is specially:
Described current frame image is divided into the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of the described estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, adopts following steps to determine the consistent point motion vector in region of this image-region:
Determine the point motion vector of the each estimation of motion vectors point in this image-region;
For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity;
Determine the point motion vector of designated movement vector estimation point corresponding to the maximum of quantity of the each self-corresponding described consistent point of each designated movement vector estimation point, as the consistent point motion vector in region of this image-region;
For every kind of vector in described the first predetermined number consistent point motion vector in described region, adopt following steps to determine this kind of compensation vector that vector is corresponding:
For the each specifies vector in this kind of vector, determine the quantity of the consistent vector of this specifies vector in other each vector, wherein, specifies vector is the vector of the 3rd predetermined number chosen from described the first predetermined number this kind of vector, and the consistent vector of this specifies vector is the vector that meets the 3rd default condition of similarity with this specifies vector;
Determine the mean value of the consistent vector of specifies vector corresponding to the maximum of quantity of the each self-corresponding described consistent vector of each specifies vector, as this kind of compensation vector that vector is corresponding;
Based on compensation vector corresponding to various vectors, obtain the compensating motion vector of described current frame image.
7. the method for claim 1, is characterized in that, specifically determines in the following way described local motion image block:
Described current frame image is divided into an at least the three predetermined number image block; Determine that described local motion image block is that in a 3rd predetermined number image block, the absolute difference of local horizontal motion vector and global level motion vector is greater than horizontal difference threshold, and/or partial vertical motion vector and the absolute difference of overall vertical motion vector are greater than the image block of vertical difference threshold; The image block that described local horizontal motion vector is described current frame image is with respect to the horizontal motion vector of the image block of same position in described current reference frame image; Described global level motion vector is the horizontal motion vector of described current frame image with respect to described current reference frame image; The image block that described partial vertical motion vector is described current frame image is with respect to the vertical motion vector of the image block of same position in described current reference frame image; Described overall vertical motion vector is the vertical motion vector of described current frame image with respect to described current reference frame image.
8. a steady picture device, is characterized in that, comprising:
Matching unit, for determining from the characteristic point of current frame image and the specific characteristic point of the characteristic point characteristic matching of current reference frame image, described characteristic point is the point that meets default characteristic condition in image;
The first determining unit, is all specific characteristic points for the estimation of motion vectors point of determining described current frame image, other specific characteristic point the specific characteristic point in local motion image block; Described local motion image block is the image block that comprises Moving Objects image in described current frame image;
The second determining unit, for the coordinate of the described estimation of motion vectors point based on described current frame image, with in described current reference frame image with the coordinate of the characteristic point of described estimation of motion vectors point characteristic matching, determine the compensating motion vector of described current frame image;
Compensating unit, for based on described compensating motion vector, carries out steady picture compensation to described current frame image.
9. device as claimed in claim 8, it is characterized in that, described compensating unit, be also the later image of the second two field picture for working as described current frame image, before described current frame image being carried out to steady picture compensation, determine that the compensating motion vector of the compensating motion vector of described current frame image and the previous frame image of described current frame image meets the first default condition of similarity.
10. device as claimed in claim 9, it is characterized in that, described compensating unit, also, in the time determining that the compensating motion vector of the compensating motion vector of described current frame image and the previous frame image of described current frame image does not meet the described first default condition of similarity, described current frame image is divided into the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of the described estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, employing following steps determine that the region of this image-region unanimously puts quantity:
Determine the point motion vector of the each estimation of motion vectors point in this image-region; For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity; Determine the maximum of the quantity of the each self-corresponding described consistent point of each designated movement vector estimation point, unanimously put quantity as the region of this image-region;
When the each self-corresponding described region of image-region of the described estimation of motion vectors point that contains at least the second predetermined number when described the first predetermined number is unanimously put maximum in quantity and is less than amount threshold, cancel and described current frame image is carried out to steady picture compensate; When the each self-corresponding described region of image-region of the described estimation of motion vectors point that contains at least the second predetermined number when described the first predetermined number is unanimously put maximum in quantity and is not less than amount threshold, based on described compensating motion vector, described current frame image is carried out to steady picture compensation.
11. devices as claimed in claim 10, is characterized in that, also comprise:
Updating block, for described current frame image being carried out to steady picture compensation in cancellation, or after described current frame image is carried out to steady picture compensation, in the time determining that the compensating motion vector of the compensating motion vector of described current frame image and the previous frame image of described current frame image does not meet the described first default condition of similarity, upgrade the next frame image that described current reference frame image is described current frame image or described current frame image; Or in cancellation, described current frame image is carried out to steady picture compensation, or after described current frame image is carried out to steady picture compensation, when described current reference frame image is when being greater than frequency threshold value with reference to the number of times of two field picture, upgrade the next frame image that described current reference frame image is described current frame image or described current frame image.
12. devices as claimed in claim 8, is characterized in that, described the second determining unit, specifically for determining the compensating motion vector of described current frame image by random sampling unification algorism.
13. devices as claimed in claim 12, is characterized in that, described the second determining unit, specifically for being divided into described current frame image the image-region of at least the first predetermined number homalographic;
Each image-region in the image-region of the described estimation of motion vectors point that contains at least the second predetermined number for the first predetermined number, adopts following steps to determine the consistent point motion vector in region of this image-region:
Determine the point motion vector of the each estimation of motion vectors point in this image-region; For the each designated movement vector estimation point in this image-region, determine the quantity of the consistent point of this designated movement vector estimation point in other each estimation of motion vectors point, wherein, designated movement vector estimation point is the estimation of motion vectors point of the second predetermined number of choosing in all estimation of motion vectors points from this image-region, and the consistent point of this designated movement vector estimation point is the estimation of motion vectors point that the point motion vector of point motion vector and this designated movement vector estimation point meets the second default condition of similarity; Determine the point motion vector of designated movement vector estimation point corresponding to the maximum of quantity of the each self-corresponding described consistent point of each designated movement vector estimation point, as the consistent point motion vector in region of this image-region;
For every kind of vector in described the first predetermined number consistent point motion vector in described region, adopt following steps to determine this kind of compensation vector that vector is corresponding:
For the each specifies vector in this kind of vector, determine the quantity of the consistent vector of this specifies vector in other each vector, wherein, specifies vector is the vector of the 3rd predetermined number chosen from described the first predetermined number this kind of vector, and the consistent vector of this specifies vector is the vector that meets the 3rd default condition of similarity with this specifies vector; Determine the mean value of the consistent vector of specifies vector corresponding to the maximum of quantity of the each self-corresponding described consistent vector of each specifies vector, as this kind of compensation vector that vector is corresponding;
Based on compensation vector corresponding to various vectors, obtain the compensating motion vector of described current frame image.
14. devices as claimed in claim 8, is characterized in that, described the first determining unit, specifically for being divided into described current frame image an at least the three predetermined number image block; Determine that described local motion image block is that in a 3rd predetermined number image block, the absolute difference of local horizontal motion vector and global level motion vector is greater than horizontal difference threshold, and/or partial vertical motion vector and the absolute difference of overall vertical motion vector are greater than the image block of vertical difference threshold; The image block that described local horizontal motion vector is described current frame image is with respect to the horizontal motion vector of the image block of same position in described current reference frame image; Described global level motion vector is the horizontal motion vector of described current frame image with respect to described current reference frame image; The image block that described partial vertical motion vector is described current frame image is with respect to the vertical motion vector of the image block of same position in described current reference frame image; Described overall vertical motion vector is the vertical motion vector of described current frame image with respect to described current reference frame image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210463920.8A CN103813056B (en) | 2012-11-15 | 2012-11-15 | A kind of digital image stabilization method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210463920.8A CN103813056B (en) | 2012-11-15 | 2012-11-15 | A kind of digital image stabilization method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103813056A true CN103813056A (en) | 2014-05-21 |
| CN103813056B CN103813056B (en) | 2016-03-16 |
Family
ID=50709221
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210463920.8A Active CN103813056B (en) | 2012-11-15 | 2012-11-15 | A kind of digital image stabilization method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103813056B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105007397A (en) * | 2015-04-30 | 2015-10-28 | 南方电网科学研究院有限责任公司 | Video compensation method of eliminating line segment cross mismatching point |
| CN107911615A (en) * | 2017-12-26 | 2018-04-13 | 北京理工大学 | A kind of Gray Projection digital image stabilization method and system |
| CN108111760A (en) * | 2017-12-26 | 2018-06-01 | 北京理工大学 | A kind of electronic image stabilization method and system |
| CN109003245A (en) * | 2018-08-21 | 2018-12-14 | 厦门美图之家科技有限公司 | Coordinate processing method, device and electronic equipment |
| CN110602393A (en) * | 2019-09-04 | 2019-12-20 | 南京博润智能科技有限公司 | Video anti-shake method based on image content understanding |
| WO2021004041A1 (en) * | 2019-07-05 | 2021-01-14 | Zhejiang Dahua Technology Co., Ltd. | Methods and systems for video stabilization |
| CN115442522A (en) * | 2022-08-10 | 2022-12-06 | 深圳市贝嘉技术有限公司 | Microscope-based imaging adjustment method, device, equipment and storage medium |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108805908B (en) * | 2018-06-08 | 2020-11-03 | 浙江大学 | Real-time video image stabilization method based on time sequence grid stream superposition |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101511024A (en) * | 2009-04-01 | 2009-08-19 | 北京航空航天大学 | Movement compensation method of real time electronic steady image based on motion state recognition |
| CN102148934A (en) * | 2011-04-02 | 2011-08-10 | 北京理工大学 | Multi-mode real-time electronic image stabilizing system |
| CN102231792A (en) * | 2011-06-29 | 2011-11-02 | 南京大学 | Electronic image stabilization method based on characteristic coupling |
| CN102780846A (en) * | 2012-07-11 | 2012-11-14 | 清华大学 | Electronic image stabilization method based on inertial navigation information |
-
2012
- 2012-11-15 CN CN201210463920.8A patent/CN103813056B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101511024A (en) * | 2009-04-01 | 2009-08-19 | 北京航空航天大学 | Movement compensation method of real time electronic steady image based on motion state recognition |
| CN102148934A (en) * | 2011-04-02 | 2011-08-10 | 北京理工大学 | Multi-mode real-time electronic image stabilizing system |
| CN102231792A (en) * | 2011-06-29 | 2011-11-02 | 南京大学 | Electronic image stabilization method based on characteristic coupling |
| CN102780846A (en) * | 2012-07-11 | 2012-11-14 | 清华大学 | Electronic image stabilization method based on inertial navigation information |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105007397A (en) * | 2015-04-30 | 2015-10-28 | 南方电网科学研究院有限责任公司 | Video compensation method of eliminating line segment cross mismatching point |
| CN105007397B (en) * | 2015-04-30 | 2018-06-19 | 南方电网科学研究院有限责任公司 | A kind of video comfort method eliminated line segment and intersect Mismatching point |
| CN107911615A (en) * | 2017-12-26 | 2018-04-13 | 北京理工大学 | A kind of Gray Projection digital image stabilization method and system |
| CN108111760A (en) * | 2017-12-26 | 2018-06-01 | 北京理工大学 | A kind of electronic image stabilization method and system |
| CN107911615B (en) * | 2017-12-26 | 2019-07-02 | 北京理工大学 | A kind of Gray Projection digital image stabilization method and system |
| CN109003245A (en) * | 2018-08-21 | 2018-12-14 | 厦门美图之家科技有限公司 | Coordinate processing method, device and electronic equipment |
| CN109003245B (en) * | 2018-08-21 | 2021-06-04 | 厦门美图之家科技有限公司 | Coordinate processing method and device and electronic equipment |
| WO2021004041A1 (en) * | 2019-07-05 | 2021-01-14 | Zhejiang Dahua Technology Co., Ltd. | Methods and systems for video stabilization |
| CN110602393A (en) * | 2019-09-04 | 2019-12-20 | 南京博润智能科技有限公司 | Video anti-shake method based on image content understanding |
| CN115442522A (en) * | 2022-08-10 | 2022-12-06 | 深圳市贝嘉技术有限公司 | Microscope-based imaging adjustment method, device, equipment and storage medium |
| CN115442522B (en) * | 2022-08-10 | 2023-11-21 | 深圳市贝嘉技术有限公司 | Imaging adjustment method, device, equipment and storage medium based on microscope |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103813056B (en) | 2016-03-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103813056B (en) | A kind of digital image stabilization method and device | |
| US11830163B2 (en) | Method and system for image generation | |
| US10972661B2 (en) | Apparatus and methods for image alignment | |
| US9025885B2 (en) | Method of detecting global motion and global motion detector, and digital image stabilization (DIS) method and circuit including the same | |
| US10073531B2 (en) | Electronic device pose identification based on imagery and non-image sensor data | |
| US9792709B1 (en) | Apparatus and methods for image alignment | |
| US10254854B2 (en) | Tracker for cursor navigation | |
| CN102779334B (en) | Correction method and device of multi-exposure motion image | |
| US20180137673A1 (en) | Method and device for processing dvs events | |
| US20150178568A1 (en) | Method for improving tracking using dynamic background compensation with centroid compensation | |
| CN106797451A (en) | The visual object tracking system verified with model and managed | |
| US11062464B2 (en) | Image processing apparatus, method, and storage medium to derive optical flow | |
| CN104299188B (en) | Image correcting method and system | |
| CN105100546A (en) | Movement estimation method and device | |
| CN115701125B (en) | Image anti-shake method and electronic equipment | |
| KR101806453B1 (en) | Moving object detecting apparatus for unmanned aerial vehicle collision avoidance and method thereof | |
| CN106550172A (en) | Video stabilization in assemble of the satellite based on subregion Gray Projection | |
| CN112565605B (en) | Image display method and device and electronic equipment | |
| CN202931463U (en) | Characteristic block based video image stabilization device | |
| CN104021575A (en) | Moving object detection method, device and system | |
| CN113873099B (en) | Video image stabilizing method, device and medium for power transmission channel | |
| CN102905104B (en) | Motion vector searching method for dynamic image compensation | |
| US20230290061A1 (en) | Efficient texture mapping of a 3-d mesh | |
| US8693800B2 (en) | Image processing device, processing method thereof, and image processing system having the same | |
| US11451718B1 (en) | Detecting flicker bands using multi-exposure sensors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |