CN101072288A - Method for obtaining fish-eye image correction relationship and fish-eye correction - Google Patents
Method for obtaining fish-eye image correction relationship and fish-eye correction Download PDFInfo
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- CN101072288A CN101072288A CN 200710111159 CN200710111159A CN101072288A CN 101072288 A CN101072288 A CN 101072288A CN 200710111159 CN200710111159 CN 200710111159 CN 200710111159 A CN200710111159 A CN 200710111159A CN 101072288 A CN101072288 A CN 101072288A
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Abstract
The method includes steps: the picture taken by fish-eye lens is as original image; multiple coordinates of correction points (CCP) are obtained from the original image; estimating actual coordinates of actual plane from CCP; using CCP and actual coordinates calculate a set of parameter of image distortion; using CCP calculates out rearranged coordinates and outputting image of corrected image in order to build image correction relation table of coincidence relation between original image and coordinates of each position in the output image. Using implied functions of interpolation and resetting magnitude, the table corrects fish-eye distorted image better and rapidly in real time. When applying image correction relation table on hardware platform, the method uses interpolation function in table, and operational method in the invention to reduce calculation amount of digital signal processor greatly, obtain optimal corrected output result.
Description
Technical field
The present invention relates to the method that a kind of flake is proofreaied and correct, particularly relate to a kind of flake image distortion parameter and image correction relationship table obtained, and realize the method for flake alignment technique.。
Background technology
Opinion is traditional camera or digital camera, all need cooperate the camera lens imaging (for example: the silver salt egative film) or photosensory assembly (for example: CCD or CMOS) in photosensitive material, and camera can be changed multiple camera lens according to different occasions, and is first-class as wide-angle lens, fish eye lens and long lens.Fish eye lens is a kind of special lens of super wide-angle, because in order to allow camera lens reach maximum photography visual angle, the preceding optic diameter of this phtographic lens is very short and be parabolical to the anterior protrusion of camera lens, and is very similar with the eyes of fish, so the name fish eye lens.
Fish eye lens has the quite long depth of field and wide visual angle, helps showing the long depth of field of scene being shot and the effect (super wide-angle) that closely just can obtain near panorama, but utilizes fish eye lens to take the photograph to such an extent that deformation of image is quite serious.Also because utilize the situation of the captured image distortion distortion of fish eye lens serious, so these anamorphic images need be proofreaied and correct perspective projection image for people were accustomed to.
The persistence of vision of human eyes is about 1/16 second, be that per second is play the frame more than 16, we will produce illusion and think that this is continuous action, use the frame speed of per second 15 lattice so can see some video archive often, general frame speed is per second 29.97 width of cloth (NTSC) and per second 25 width of cloth (PAL), with the NTSC system, per ten minutes is 17982 frames, so, can on average when finishing, omit per minute two frames, then do not do the action of omitting frame on the tenth minute, so just can smoothly must play.With digitized data instance, the image of NTSC form, ITU-656 D1 quality, the video flowing of a width of cloth image (Video Stream) is 900,900 bytes, thus per second 13MB nearly, so data volume is quite surprising.
Traditional flake alignment technique must have heavy and complicated computational process, and video flowing (VideoStream) is sizable data volume, so can't be used for real-time treatment for correcting, and the distortion image of flake, be quite factitious for impression on the human vision.
In view of this, the present invention is directed to the defective of above-mentioned known technology, propose a kind of method that obtains flake image correction relationship and flake correction in real time, effectively to overcome above-mentioned problem.
Summary of the invention
Main purpose of the present invention is providing a kind of method that obtains the flake image correction relationship, and it utilizes plural check point coordinate and function to obtain group image distortion parameter, and inverse operation goes out the corresponding relation between raw video and image output pixel.
Another object of the present invention is providing a kind of method that obtains the flake image correction relationship, and its proportion of utilization chi is set up the corresponding relation of proofreading and correct back image and raw video, finds out the replacement coordinate of proofreading and correct the back image.
Another object of the present invention is providing a kind of method that obtains the flake image correction relationship, its relatively coordinate of raw video and image output whether be same visual field, the corresponding relation when setting up interpolation.
In order to achieve the above object, the invention provides a kind of method that obtains the flake image correction relationship, comprise the following steps: to utilize a fish eye lens to shoot picture, and from raw video, obtain plural check point coordinate (x as raw video
d, y
d), estimate the check point coordinate and correspond to actual coordinate (x on the physical plane
u, y
u); Utilize check point coordinate and actual coordinate, with polynomial approximation equation x
u=x
d(1+k
1r
d 2+ k
2r
d 4), y
u=y
d(1+k
1r
d 2+ k
2r
d 4) calculate group image distortion parameter (k
1, k
2); Read in the coordinate position of each pixel in the raw video in regular turn; Extrapolate the size of raw video with function, and the coordinate of proportion of utilization chi calculating raw video corresponds to the replacement coordinate of correcting image at the correcting image of after overcorrect, obtaining; Again the replacement coordinate is utilized above-mentioned polynomial approximation equation inverse operation to go out the coordinate position of corresponding image output; And the image correction relationship table of setting up each coordinate position corresponding relation in raw video and the image output.
The present invention provides a kind of method of using the flake image correction relationship in addition, comprises the following steps: to store image data in internal memory, and sets up plural index and point to buffering area respectively; Read in the initial core position of each row in a flake image correction relationship table and the image data, and set up the original position table; Utilize pointer and original position table calculate the tram of image data in internal memory; The setting direct memory access (DirectMemory Access, the DMA) position that will read and write, and start this direct memory access; And the numerical value that utilizes flake image correction relationship table to be provided carries out interpolation method, changes every capable image data.Connect because buffering area is a ring-type, and image data is according to after the pointer input block, index is promptly pointed to next buffering area to handle the next line image data, to save the processing time.
The effect that is easier to understand purpose of the present invention, technology contents, characteristics and is reached is described in detail by specific embodiment below.
Description of drawings
Fig. 1 a obtains the flow chart of flake image distortion parameter for the present invention.
Fig. 1 b obtains the flow chart of flake image correction relationship for the present invention.
Fig. 2 a is raw video among the present invention and the image output schematic diagram in same visual field.
Fig. 2 b be middle raw video with image output in different visual fields and carry out the schematic diagram of interpolation.
Fig. 3 is for using the flow chart of obtained flake image correction relationship table among the present invention.
Fig. 4 is when using flake image correction relationship table, and four indexs are pointed to the schematic diagrames that four slow districts dash respectively.
The figure number explanation
10,12,14,16 is buffering area
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail:
The invention provides a kind of method that obtains flake image correction relationship and flake correction, it utilizes plural check point and polynomial approximation equation to ask for best image distortion parameter earlier, to calculate the corresponding relation of raw video and image output with this image distortion parameter and aforesaid polynomial approximation equation again, obtain the flake adjustment of image mapping table of implicit interpolation and replacement magnitude function.
Fig. 1 a obtains flake image distortion parameter for the present invention, and as described in step S100, the picture that utilizes fish eye lens to take the distortion image earlier uses as proofreading and correct, and claims that this picture is a correction graph; Among step S102～S104, in this raw video, choose plural check point coordinate (x
d, y
d), and extrapolate the actual coordinate (x that each check point coordinate corresponds to the physical plane in regular turn
u, y
u), then, judge whether corresponding at present check point coordinate is last check point as described in the step S106, if be not last check point, then repeating step S102 and S104 continue next check point coordinate is corresponded on the actual coordinate, up to all check points all correspondence finish.Continue, as described in step S108, utilize aforesaid corresponding relation, use the polynomial approximation equation to calculate the image distortion parameter (k of one group of the best
1, k
2), this polynomial approximation equation is as follows:
x
u＝x
d(1+k
1r
d 2+k
2r
d 4)
y
u＝y
d(1+k
1r
d 2+k
2r
d 4)
(x wherein
d, y
d) check point coordinate in the expression flake image; r
dThe distance of representing each check point and correction graph center; (x
u, y
u) expression corresponds to the coordinate of physical plane.By the many check point of whole raw video and corresponding physical plane coordinates of being distributed in, bring the image distortion parameter (k that calculates one group of the best in the above-mentioned polynomial approximation equation into
1, k
2).
The image distortion parameter needs to calculate earlier when using fish eye lens for the first time, can directly use after the second time, if but changed other camera lens, then need to carry out again one time step S100～S108, to obtain and the corresponding image distortion parameter of this fish eye lens.
Obtain image distortion parameter (k
1, k
2) after, just can set up flake image correction relationship table, its flow process at first as described in step S110 and the S112, is read in the image distortion parameter, and is read in the coordinate position of each pixel of raw video in regular turn shown in Fig. 1 b; Raw video is after overcorrect, obtain correcting image, its part with the edge torsional deformation is removed, in step S114, extrapolate the size of correcting image earlier with above-mentioned polynomial approximation equation, calculate raw video and correcting image image magnitude proportion relation, the coordinate of proportion of utilization chi calculating raw video corresponds to the replacement coordinate position of correcting image again; Again the replacement coordinate is utilized above-mentioned polynomial approximation equation to carry out among the step S116, calculate corresponding image output coordinate with the inverse function computing.Repeating step S112～S116 has corresponded to the coordinate position of image output up to each pixel coordinate of raw video.
Till step S116, tentatively finish the mapping table of implicit replacement magnitude function, then in order to improve the jagged problem of image, the function that adds interpolation, as described in step S118, judge whether the coordinate of image output and the coordinate position of raw video are same visual field, if be all odd number visual field (OddField) or even number visual field (Even Field), then as directly setting up the corresponding relation of point coordinates as described in the step S120, otherwise, if the coordinate position of image output and raw video is in same visual field, then as described in the step S122, find out in the same visual field 2 coordinate position up and down, and set up the corresponding relation of interpolation.Then as described in the step S124, judge whether that the every bit coordinate of raw video is corresponding all, repeating step S112～S124 then if not is if then image output is proofreaied and correct mapping table.
Fig. 2 a and Fig. 2 b be raw video and image output whether at the schematic diagram of same visual field, among the figure "." be corresponding point coordinates.In 2a figure, the point coordinates of raw video and the point coordinates of the image output odd number visual field that coexists; In 2b figure, the point coordinates of raw video is in the even number visual field, but the point coordinates of image output is in the odd number visual field, therefore 2 coordinate position " △ " is set up the relation of interpolation about obtaining in the odd number visual field of raw video, to obtain and the corresponding points coordinate " " of image output in same visual field.
Be the method that flake image correction relationship table provided by the present invention is used in explanation below, for the embodiment utilization realize that based on ADSP BlackFin 561 hardware platforms flake proofreaies and correct.The 3rd figure is a flow process of using this hardware platform, as described in step S200, earlier with digital signal processor (Digital SignalProcessing, DSP) initialization, wherein must planning direct memory access (Direct Memory Access, behavior pattern DMA).Interior nonresident portion, plan that four buffering areas stack video data, and these four buffering areas are respectively video input storage area, video output storage area, Video processing reference area and Video processing buffering area, this four block buffer memories framework connects into ring buffer, and with firmware (Firm ware), also there are four indexs to point to this four buffering areas respectively, and it is same numerical value that these four indexs can not have more than any two, if any equating that expression input data have problem, must restarting systems.
Figure 4 shows that the relation of four indexs and buffering area, as shown in the figure, four buffering areas 10,12,14,16, and four pointers are video input storage area pointer, video output storage area pointer, Video processing reference area pointer and Video processing buffer pointer.As shown in the figure, video input storage area pointed buffering area 14, video output storage area pointed buffering area 16, the Video processing buffer pointer is pointed to buffering area 10, Video processing reference area pointed buffering area 12, and after handling group image data, four pointers all point to next buffering area, video input storage area pointed buffering area 16, video output storage area pointed buffering area 10, the Video processing buffer pointer is pointed to buffering area 12, Video processing reference area pointed buffering area 14, therefore image data is after the output of video output storage area, and same buffering area can be accepted next group image data that video input storage area pointer is imported, faster processing time.
After finishing system initialization, as described in step S202, read in the flake checking list to SDRAM (Synchronous Dynamic Random Access Memory, SDRAM) in, this table in include interpolation numerical value; Then, in order to reduce the operand of digital signal processor,, use in order to digital signal processor so, earlier each line start core position of actual image data in the video data is found out, and it is expressed as form in advance as described in the step S204.Step S206 is described for another example, utilizes resulting four pointers among the step S200, sets the position that direct memory access will read and write, and after finishing setting, as described in step S208, revise the set point of direct memory access, send triggering signal, to start direct memory access.
Because in the hardware operation, the output signal of camera might be unstable, can cause synchronizing signal inconsistent, so need as described in step S210, to check, whether test mode is for to scan the header file position of vision signal for be maintained on the same core position always periodically, in this way, problem does not take place in expression, on the contrary synchronizing signal generation problem; If it is asynchronous that synchronizing signal takes place, then as step S212, (parallel peripheral interface PPI) and direct memory access, allows the hardware can be synchronous with vision signal once more to restart parallel perimeter interface.
Otherwise, if there is not the asynchronous problem that takes place, then enter the vision signal program of handling as step S214, at first, obtain the coordinate position of any point in the raw video earlier, it utilizes the resulting original position table of step S204, four of matching step S200 indexs are as substrate (base address) again, every capable image data original position table is as side-play amount (offset value), so can find out the tram of every capable real image data in the internal memory fast, formula is as follows:
A＝pBase+Offset[y]
Wherein y represents that y-th is capable, and pBase represents buffering area to be processed beginning core position, Offset[y] side-play amount of the capable image data of expression y-th, A is for truly corresponding to the core position in the SDRAM.The method also can be derived the position of any point, and formula is as follows:
B＝(pBase+Offset[y])+2x+1
Wherein x is the x coordinate points on the video pictures, and B is coordinate x, and y truly corresponds to core position in the SDRAM, because ITU 656 reference formats are YUV 4:2:2, so, must cooperate the x position to try to achieve following formula in order to obtain correct UV position:
Ifx％2
pU＝(pBase+Offset[y])+2x
pV＝(pBase+Offset[y])+2x+2
else
pU＝(pBase+Offset[y])+2x+2
pV＝(pBase+Offset[y])+2x
Wherein, pU is picture x, y point U value truly correspond to core position in the SDRAM, pV is for being picture x, y point V value truly correspond to the interior core position of SDRAM.The method can obtain the coordinate position of any point fast, significantly reduces the digital signal processor operand.
After obtaining the coordinate position of any point, carry out interpolation.Because according to video standard form size, each point coordinates all has from pairing two numerical value of flake checking list, this two numerical value promptly is the core position of doing interpolation.Take out the numerical value of these two indexs respectively, do the average interpolation method, replace the point of handling at present, up to have a few all dispose till, formula is as follows:
Y[p]
new＝(Y1[p]
org+Y2[p]
org)/2
Y[p wherein]
NewBe the value after last the correction; Y1[p]
OrgFirst point value that is provided for flake image correction relationship table; Y2[p]
OrgSecond point value that is provided for flake image correction relationship table; P is the p point of image data, for example with ITU-656 NTSC, and total 720*486=349920 point.
At last as described in the step S216, when handle one complete look the width of cloth (frame) after, according to rule shown in Figure 4, change four buffering areas that pointer is pointed, prepare the processing that next looks the width of cloth.
In sum, the present invention utilizes the polynomial approximation equation to ask for best image distortion parameter, sets up the flake adjustment of image mapping table of implicit interpolation and replacement magnitude function again with this.Realize the flake timing on the hardware platform when being applied in this flake image correction relationship table, more can significantly reduce the operand of digital signal processor via method provided by the present invention, faster processing time, and exempt the inconsistent problem that may cause of synchronizing signal, perfection presents the flake image.
The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; can also make some improvements and modifications, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (20)
1. a method that obtains the flake image correction relationship is characterized in that, comprises the following steps:
Utilize the fish eye lens pictures taken as raw video, and from described raw video, obtain plural check point coordinate, estimate the actual coordinate of described check point coordinate on the physical plane;
Utilize described check point coordinate and described actual coordinate to calculate group image distortion parameter;
Utilize described check point coordinate computation to go out image output; And
Set up the adjustment of image mapping table of each coordinate position corresponding relation in described raw video and the described image output.
2. the method that obtains the flake image correction relationship as claimed in claim 1 is characterized in that, wherein said picture is the distortion image.
3. the method that obtains the flake image correction relationship as claimed in claim 1 is characterized in that, wherein said check point coordinate is (x
d, y
d), described actual coordinate is (x
u, y
u), described image distortion parameter is (k
1, k
2), the described polynomial approximation equation that utilizes described check point coordinate and described actual coordinate to calculate the described image distortion parameter of calculating in the group image distortion parameter is x
u=x
d(1+k
1r
d 2+ k
2r
d 4), y
u=y
d(1+k
1r
d 2+ k
2r
d 4), r
dDistance for the center of described check point coordinate and described raw video.
4. the method that obtains the flake image correction relationship as claimed in claim 1 is characterized in that, wherein saidly utilizes described check point coordinate computation to go out to comprise in the image output step down:
Read in the coordinate position of each pixel in the described raw video in regular turn;
Extrapolate the size of described raw video with function, and the proportion of utilization chi coordinate that calculates described raw video corresponds to the replacement coordinate of described correcting image at the correcting image that after overcorrect, obtains;
Utilize described function inverse operation to go out the coordinate position of corresponding described image output on described replacement coordinate; And
Repeating step has all corresponded to the coordinate position of described image output up to each pixel coordinate of described raw video.
5. the method that obtains the flake image correction relationship as claimed in claim 4, it is characterized in that, wherein saidly extrapolate the size of described raw video, and the described function that the proportion of utilization chi coordinate that calculates described raw video corresponds in the replacement coordinate of described correcting image is x at the correcting image that after overcorrect, obtains with function
u=x
d(1+k
1r
d 2+ k
2r
d 4), y
u=y
d(1+k
1r
d 2+ k
2r
d 4), (x wherein
d, y
d) be described check point coordinate, (x
u, y
u) be described actual coordinate, (k
1, k
2) be described image distortion parameter, r
dDistance for the center of described check point coordinate and described raw video.
6. the method that obtains the flake image correction relationship as claimed in claim 1, it is characterized in that, when the coordinate of wherein said image output and described raw video is same visual field, can directly sets up the corresponding relation of point coordinates, thereby obtain described image correction relationship table.
7. the method that obtains the flake image correction relationship as claimed in claim 1, it is characterized in that, when wherein said image output is different visual field with the coordinate of described raw video, then find out described image output and described raw video 2 coordinate up and down in same visual field, set up the corresponding relation of interpolation, thereby obtain described adjustment of image mapping table.
8. the method that obtains the flake image correction relationship as claimed in claim 1 is characterized in that, wherein said image distortion parameter remains unchanged when using same described fish eye lens.
9. the method that obtains the flake image correction relationship as claimed in claim 1 is characterized in that, wherein said raw video is removed the part of edge deformation at timing.
10. the method for a flake adjustment of image is characterized in that, comprises the following steps:
In internal memory, store image data, and set up plural index and point to buffering area respectively;
Read in the initial core position of each row in flake image correction relationship table and the described image data, and set up the original position table;
Utilize described pointer and described original position table calculate the tram of described image data in described internal memory;
Set the position that direct memory access will read and write, and start described direct memory access;
The numerical value that utilizes described flake image correction relationship table to be provided carries out interpolation method, changes every capable image data.
11. the method for flake adjustment of image as claimed in claim 10 is characterized in that, wherein said flake image correction relationship table comprises at least one interpolation numerical value.
12. the method for flake adjustment of image as claimed in claim 10 is characterized in that, wherein said index is different numerical value.
13. the method for flake adjustment of image as claimed in claim 10 is characterized in that, wherein said index has both above during for identical numerical value, then restarts described direct memory access and parallel peripheral interface.
14. the method for flake adjustment of image as claimed in claim 10 is characterized in that, after wherein said direct memory access starts, if find that described image data is asynchronous, then restarts described direct memory access and parallel perimeter interface.
15. the method for flake adjustment of image as claimed in claim 14, when it is characterized in that wherein said image data is asynchronous, the header file position of described image data ties up to diverse location in the described internal memory.
16. the method for flake adjustment of image as claimed in claim 10 is characterized in that, every bit all has pairing two numerical value of described flake image correction relationship table in the wherein said image data, with the core position as interpolation.
17. the method for flake adjustment of image as claimed in claim 16, it is characterized in that, wherein said interpolation method is the average interpolation method, and every bit is all got the average of two numerical value that described flake image correction relationship table provided in the described image data, is last corrected value.
18. the method for flake adjustment of image as claimed in claim 10 is characterized in that, after wherein said image data disposes, changes described index buffering area pointed, to carry out the processing of next image data.
19. the method for flake adjustment of image as claimed in claim 10 is characterized in that, wherein said buffering area comprises video input storage area, video output storage area, Video processing reference area and Video processing buffering area.
20. the method for flake adjustment of image as claimed in claim 19 is characterized in that, wherein said buffering area is annular arrangement, and described index can be pointed to next described buffering area automatically when transmitting next group image data.
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| CN101814181A (en) * | 2010-03-17 | 2010-08-25 | 天津理工大学 | Unfolding method for restoration of fisheye image |
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| CN101726855B (en) * | 2009-11-13 | 2011-05-11 | 河北工业大学 | Correction method of fisheye image distortion on basis of cubic projection |
| CN101814181A (en) * | 2010-03-17 | 2010-08-25 | 天津理工大学 | Unfolding method for restoration of fisheye image |
| CN106530212B (en) * | 2015-09-09 | 2019-08-27 | 奥特润株式会社 | Lens video distortion correction device |
| CN106530212A (en) * | 2015-09-09 | 2017-03-22 | 奥特润株式会社 | Apparatus for correcting image distortion of lens |
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| CN110211209A (en) * | 2019-05-13 | 2019-09-06 | 广州视源电子科技股份有限公司 | Vector graphic animation transition method and device and intelligent terminal equipment |
| CN110264397A (en) * | 2019-07-01 | 2019-09-20 | 广东工业大学 | A kind of method and apparatus of effective coverage that extracting fish eye images |
| CN113342173A (en) * | 2021-06-30 | 2021-09-03 | 厦门元馨智能科技有限公司 | Self-adaptive learning method of integrative glasses based on somatosensory operation |
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