CN107295264A - One kind is based on homography conversion light-field data compression method - Google Patents
One kind is based on homography conversion light-field data compression method Download PDFInfo
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- CN107295264A CN107295264A CN201710648322.0A CN201710648322A CN107295264A CN 107295264 A CN107295264 A CN 107295264A CN 201710648322 A CN201710648322 A CN 201710648322A CN 107295264 A CN107295264 A CN 107295264A
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- H—ELECTRICITY
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Abstract
The invention discloses a kind of light-field data compression method based on homography conversion, including：Input original light field data collection Φ (S1,S2,…,Si), by sub-aperture image S thereiniIt is divided into center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai‑j；According to center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai‑jAsk for homography matrix Hi‑j, based on homography conversion by neighborhood sub-aperture image Ai‑jProject to center sub-aperture image CiPlace imaging plane converted after neighborhood sub-aperture image A 'i‑j, by the neighborhood sub-aperture image A ' after conversioni‑jWith center sub-aperture image CiSubtract each other and obtain residual plot Ri‑j；Whole center sub-aperture image C are concentrated to original light field dataiWith residual image Ri‑jIt is scanned respectively, generation centered video sequence VCWith residual video sequence VR；To center video sequence VCWith residual video sequence VRIt is compressed respectively.Redundancy in effectively reduction spatial domain of the invention, and then realize effective lifting of code efficiency.
Description
Technical field
The present invention relates to computer vision and digital image processing field, more particularly to a kind of light based on homography conversion
Field data compression method.
Background technology
The nearest full light camera based on microlens structure has triggered the extensive concern of academia and industrial quarters, what it was captured
All-optical data can record the positional information and angle information of light simultaneously, be imaged and virtual in three-dimensional reconstruction, stereoscopic display
The fields such as reality all illustrate huge application prospect.However, the image captured relative to traditional camera, full light image has
Ultrahigh resolution, while there is also huge information redundancy for its special lenticule pixel distribution form.The surge of data volume is given
The transmission of light field data and storage tape carry out immense pressure, therefore are badly in need of a kind of effective light-field data compression scheme, this be also by
Plane multimedia march toward the stereopsis epoch be badly in need of and necessary core technology.
The original light field image captured for light-field camera, can be pressed by rendering the sub-aperture image of generation to it
Contracting, the compression scheme can be roughly divided into three classes：The first kind is, by using different scanning forms, to be generated by sub-aperture image pseudo-
Video sequence, and then compression is completed based on video encoder, such scheme is analyzed due to that can not provide theoretic compression efficiency,
Therefore with certain uncertain；Equations of The Second Kind scheme is according to different visual angle relations, from spatial domain to time domain by sub-aperture image
Conversion, and then utilize in the compression of multi-vision-point encoding completion light field data, the program because multi-vision-point encoding needs to configure camera
Parameter, while the viewpoint number limitation of the visual angle number and multi-vision-point encoding device of sub-aperture image so that implement with certain difficult
Degree；Last class scheme is then the parallax relation having using adjacent sub-aperture image, and parallax is introduced in video encoder and is mended
The coding tools repaid reduces spatial redundancy information, and such scheme fails the similar pass effectively using the grand pixel in light field image
System, limits the further lifting of code efficiency.
The disclosure of background above technology contents is only used for design and the technical scheme that auxiliary understands the present invention, and it is not necessarily
Belong to the prior art of present patent application, without tangible proof show the above present patent application the applying date
In the case of disclosed, above-mentioned background technology should not be taken to evaluate the novelty and creativeness of the application.
The content of the invention
It is a primary object of the present invention to provide a kind of light-field data compression method based on homography conversion, effectively reduction
Redundancy in spatial domain, and then realize effective lifting of code efficiency.
To achieve these goals, the present invention uses following technical scheme：
The invention discloses a kind of light-field data compression method based on homography conversion, comprise the following steps：
A1：Input original light field data collection Φ (S1,S2,…,Si), by sub-aperture image S thereiniIt is divided into center sub-aperture
Footpath image CiWith corresponding neighborhood sub-aperture image Ai-j；
A2：According to center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai-jAsk for homography matrix Hi-j, base
In homography conversion by neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiAfter place imaging plane is converted
Neighborhood sub-aperture image A 'i-j, by the neighborhood sub-aperture image A ' after conversioni-jWith center sub-aperture image CiSubtract each other and obtain residual error
Scheme Ri-j；
A3：Whole center sub-aperture image C are concentrated to light field dataiWith residual image Ri-jIt is scanned, generates respectively
Centered video sequence VCWith residual video sequence VR；
A4：To center video sequence VCWith residual video sequence VRIt is compressed respectively.
Preferably, step A1 is specially：To sub-aperture image S thereiniIt is divided into center according to spatial domain arrangement position relationship
Sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai-j。
Preferably, step A1 is specially：The original light field data collection Φ (S of input1,S2,…,Si) scheme for N × N squares
As array, N × N square-shaped image arrays are divided into (N/3) × (N/ by 9 sub-aperture images using adjacent 3 × 3 as one group
3) sub-aperture image sets are organized, wherein the sub-aperture image S at the center in every group of sub-aperture image setsiSub-aperture figure centered on definition
As Ci, 8 adjacent sub-aperture image S of surroundingiIt is defined as corresponding neighborhood sub-aperture image Ai-j。
Preferably, step A2 is specially：
A21：Based on SIFT image matching algorithms and DLT direct linear transformation's algorithms, center sub-aperture figure is solved respectively
As CiWith corresponding neighborhood sub-aperture image Ai-jHomography matrix Hi-j：
A22：By neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiAfter place imaging plane is converted
Neighborhood sub-aperture image A 'i-j：
[x ', y ', 1]=[x, y, 1] Hi-j
Wherein, (x, y) is neighborhood sub-aperture image Ai-jIn pixel coordinate, (x ', y ') for conversion after neighborhood sub-aperture
Image A 'i-jIn pixel coordinate；
A23：By the neighborhood sub-aperture image A ' after conversioni-jWith corresponding center sub-aperture image CiSubtract each other, obtain residual error
Scheme Ri-j：
IR(u, v)=IA(u,v)-Ic(u,v)
Wherein, (u, v) is the pixel coordinate in image, IR、IA、ICRespectively Ri-j、A′i-jAnd CiIn pixel value.
Preferably, whole center sub-aperture image C are concentrated in step A3 to light field dataiThe method being scanned is Z
Font is scanned or S-shaped scanning, and wherein zigzag scanning represents the center sub-aperture image C between adjacent rowsiIt is from beginning to end, S-shaped
Scanning represents the center sub-aperture image C between adjacent rowsiHead is connected or afterbody is connected.
Preferably, whole residual image R are concentrated in step A3 to light field datai-jThe method being scanned is swept for zigzag
Retouch or S-shaped scanning, wherein zigzag scanning represents the residual image R between adjacent rowsi-jFrom beginning to end, S-shaped scanning represents phase
Two residual image R in the ranks of neighbouri-jHead is connected or afterbody is connected.
Preferably, whole residual image R are concentrated in step A3 to light field datai-jThe method being scanned is swept to turn-take
Retouch, scanning of turn-taking is represented to 8 residual image R in sub- subaperture image groupi-jTurn-take after scanning, with other group of adjacent sub-aperture
Residual image R in the image sets of footpathi-jJoin end to end.
Preferably, step A4 is also included to whole homography matrix Hi-jCoding compression.
Preferably, step A4 is also included to whole homography matrix Hi-jCarry out block code compression.
Preferably, step A4 is specially：To center video sequence VCWith residual video sequence VRIt is utilized respectively video encoder
It is compressed coding.
Compared with prior art, the beneficial effects of the present invention are：The light field data based on homography conversion of the present invention
Compression method, sub-aperture image and corresponding neighborhood sub-aperture image centered on original light field data collection is divided first, is based on
Homography conversion completes the mapping of neighborhood sub-aperture image and center sub-aperture image, so by the residual image to acquisition and
Center sub-aperture image is scanned the pseudo- video sequence of generation respectively, to realizing that light field data is compiled after video sequence and then compression
Effective lifting of code efficiency；The light-field data compression method, takes full advantage of the design feature of light field data, light is reduced as best one can
The redundancy of field data, so as to effectively improve the coding compression efficiency of light field image.
In further scheme, arrange position relationship to divide sub-aperture image according to the spatial domain of sub-aperture image, so
The visual angle effect of neighborhood sub-aperture image and center sub-aperture image is completed by homography conversion afterwards, and then scans structure center
Multi-view video sequence and residual video sequence, to make full use of the geometry of imaged viewing angle between light field data sub-aperture image to close
System's light intensity arrangement feature similar with having each other, due to the similitude between image, residual image relative smooth, and then causes
Fully reduce code check expense in cataloged procedure, the redundancy of light field data is further effectively reduced, so as to further improve
The coding compression efficiency of light field image.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the light-field data compression method based on homography conversion of the preferred embodiment of the present invention；
Fig. 2 a are the schematic diagrames of the light field data collection of the preferred embodiment of the present invention；
Fig. 2 b are the enlarged diagrams at T in Fig. 2 a；
Fig. 3 a are that the zigzag for center sub-aperture image in the preferred embodiment of the present invention scans schematic diagram；
Fig. 3 b are that the S-shaped for center sub-aperture image in the preferred embodiment of the present invention scans schematic diagram；
Fig. 4 a are that the zigzag for residual image in the preferred embodiment of the present invention scans schematic diagram；
Fig. 4 b are that the S-shaped for residual image in the preferred embodiment of the present invention scans schematic diagram；
Fig. 4 c are the scanning schematic diagrames of turn-taking for residual image in the preferred embodiment of the present invention.
Embodiment
Below against accompanying drawing and with reference to preferred embodiment the invention will be further described.
As shown in figure 1, the preferred embodiment of the present invention discloses a kind of light-field data compression method based on homography conversion,
Comprise the following steps：
A1：Input original light field data collection Φ (S1,S2,…,Si), to sub-aperture image S thereiniArranged according to spatial domain
Position relationship is divided into center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai-j；
Wherein, the original light field data collection Φ (S of input1,S2,…,Si) by sub-aperture image SiComposition.Sub-aperture image Si
The original full light image generated as obtained by being gathered light-field camera (such as LytroIllum) after a series of processing of early stages is through wash with watercolours
Contaminate obtained by algorithm, and be N × N square-shaped image arrays according to the arrangement of its imaged viewing angle relation；Generated with LytroIllum
Exemplified by light field data, Φ (S1,S2,…,Si) for 15 × 15 totally 225 sub-aperture images, as shown in Figure 2 a.For image battle array
Former N × N square-shaped images array is divided into (N/3) × (N/3) by row, 9 sub-aperture images using adjacent 3 × 3 as one group
Group, as shown in Figure 2 b, the sub-aperture image S at every group of centeriSub-aperture image C centered on definitioni, 8 adjacent sub-aperture figures of surrounding
As being defined as neighborhood sub-aperture image Ai-j, ignored and skipped (such as the invalid sub-aperture image of some light fields of corner around
Shown in light gray color lump in Fig. 2 a at four angles).
A2：According to center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai-jAsk for homography matrix Hi-j, base
In homography conversion by neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiAfter place imaging plane is converted
Neighborhood sub-aperture image A 'i-j, by the neighborhood sub-aperture image A ' after conversioni-jWith center sub-aperture image CiSubtract each other and obtain residual error
Scheme Ri-j；
For each ready-portioned 3 × 3 sub-aperture image sets, directly linearly become based on SIFT image matching algorithms and DLT
Scaling method, solves 8 neighborhood sub-aperture image A around respectivelyi-jWith center sub-aperture image CiHomography matrix Hi-j；Enter
And homography conversion is utilized by neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiPlace imaging plane is converted
Neighborhood sub-aperture image A ' afterwardsi-j：
[x ', y ', 1]=[x, y, 1] Hi-j
Wherein, (x, y) is former neighborhood sub-aperture image Ai-jIn pixel coordinate, (x ', y ') for conversion after neighborhood sub-aperture
Footpath image A 'i-jIn pixel coordinate.
By the neighborhood sub-aperture image A ' obtained by conversioni-jWith corresponding center sub-aperture image CiSubtract each other, obtain residual plot
Ri-j：
IR(u, v)=IA(u,v)-Ic(u,v)
Wherein, (u, v) is the pixel coordinate in image, IR、IA、ICRespectively Ri-j、A′i-jAnd CiIn pixel value.
A3：Whole center sub-aperture image C are concentrated to original light field dataiWith residual image Ri-jAccording to respective sky
Domain scan mode generates centered video sequence V respectivelyCWith residual video sequence VR；
Wherein, for center sub-aperture image Ci, can be using zigzag scanning (Zigzag scannings) or S-shaped scanning (S-
Shape is scanned), wherein zigzag scanning form is the center sub-aperture image C between adjacent rowsiIt is from beginning to end, such as Fig. 3 a institutes
Show；And S-shaped scanning form is the center sub-aperture image C between adjacent rowsiHead is connected or afterbody is connected, such as Fig. 3 b institutes
Show.
For residual image Ri-j, (Zigzag scannings), S-shaped scanning (S-Shape scannings) can be scanned with zigzag or is turned
Circle scanning (Circle scannings), wherein zigzag scanning and S-shaped scanning form and center bore image CiIt is similar, namely zigzag sweeps
It is the residual image R between adjacent rows to retouch formi-jIt is from beginning to end, as shown in fig. 4 a；And S-shaped scanning form is between adjacent rows
Residual image Ri-jHead is connected or afterbody is connected, as shown in Figure 4 b；And scanning form of turn-taking is the sub-aperture figure to 3 × 3
As 8 residual image R in groupi-jTurn-take after scanning, joined end to end with the residual image in other adjacent groups, such as Fig. 4 c institutes
Show.
A4：To center video sequence VCWith residual video sequence VRIt is utilized respectively video encoder to be compressed, while to complete
The homography matrix H in portioni-jCoding compression.
Wherein, to center video sequence VCWith residual video sequence VRIt is utilized respectively video encoder and is compressed coding, together
When to whole homography matrix Hi-jCarry out block code compression.And the process of decoding and rebuilding is then the inverse process of said process,
It will not be repeated here.
The preferred embodiments of the present invention disclose a kind of light-field data compression method based on homography conversion, first according to
The position relationship of sub-aperture image space arrangement is concentrated to carry out center sub-aperture image and field according to original light field data is inputted
The division of subaperture image, carries out homography conversion using the similitude of sub-aperture image and neighborhood sub-aperture image, completes neighborhood
Mapping from sub-aperture image to center sub-aperture image；Obtained using the neighborhood sub-aperture image after conversion and center sub-aperture image
To residual image, respectively by scanning generation center sub-aperture path image sequence and neighborhood residual error sub-aperture path image sequence, due to figure
Similitude as between, residual image relative smooth, and then fully to reduce code check expense in an encoding process；The wherein light field
Encoding scheme takes full advantage of in light field data visual angle relation in the imaging process of adjacent sub-aperture image, and adjacent sub-aperture
Similar light intensity arrangement relation between image, smooth residual image avoids substantial amounts of code check expense, can be swept from different
Retouch mode and provide multiple choices for the lifting of code efficiency, the light-field data compression method cause light field image research field and
The marketization of light-field camera is benefited extensively.
Above content is to combine specific preferred embodiment further description made for the present invention, it is impossible to assert
The specific implementation of the present invention is confined to these explanations.For those skilled in the art, do not taking off
On the premise of from present inventive concept, some equivalent substitutes or obvious modification can also be made, and performance or purposes are identical, all should
When being considered as belonging to protection scope of the present invention.
Claims (10)
1. a kind of light-field data compression method based on homography conversion, it is characterised in that comprise the following steps：
A1：Input original light field data collection Φ (S1,S2,…,Si), by sub-aperture image S thereiniIt is divided into center sub-aperture image
CiWith corresponding neighborhood sub-aperture image Ai-j；
A2：According to center sub-aperture image CiWith corresponding neighborhood sub-aperture image Ai-jAsk for homography matrix Hi-j, answered based on single
Property become and change commanders neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiNeighborhood after place imaging plane is converted is sub
Subaperture image A 'i-j, by the neighborhood sub-aperture image A ' after conversioni-jWith center sub-aperture image CiSubtract each other and obtain residual plot Ri-j；
A3：Whole center sub-aperture image C are concentrated to light field dataiWith residual image Ri-jIt is scanned respectively, generates center
Video sequence VCWith residual video sequence VR；
A4：To center video sequence VCWith residual video sequence VRIt is compressed respectively.
2. light-field data compression method according to claim 1, it is characterised in that step A1 is specially：To son therein
Subaperture image SiIt is divided into center sub-aperture image C according to spatial domain arrangement position relationshipiWith corresponding neighborhood sub-aperture image Ai-j。
3. light-field data compression method according to claim 1, it is characterised in that step A1 is specially：What is inputted is original
Light field data collection Φ (S1,S2,…,Si) it is N × N square-shaped image arrays, 9 sub-aperture images using adjacent 3 × 3 is one
Group, is divided into (N/3) × (N/3) group sub-aperture image sets, wherein every group of sub-aperture image sets by N × N square-shaped image arrays
In center sub-aperture image SiSub-aperture image C centered on definitioni, 8 adjacent sub-aperture image S of surroundingiIt is defined as phase
The neighborhood sub-aperture image A answeredi-j。
4. light-field data compression method according to claim 1, it is characterised in that step A2 is specially：
A21：Based on SIFT image matching algorithms and DLT direct linear transformation's algorithms, center sub-aperture image C is solved respectivelyiWith
Corresponding neighborhood sub-aperture image Ai-jHomography matrix Hi-j：
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A22：By neighborhood sub-aperture image Ai-jProject to center sub-aperture image CiPlace imaging plane converted after neighborhood
Sub-aperture image A 'i-j：
[x ', y ', 1]=[x, y, 1] Hi-j
Wherein, (x, y) is neighborhood sub-aperture image Ai-jIn pixel coordinate, (x ', y ') for conversion after neighborhood sub-aperture image
A′i-jIn pixel coordinate；
A23：By the neighborhood sub-aperture image A ' after conversioni-jWith corresponding center sub-aperture image CiSubtract each other, obtain residual plot
Ri-j：
IR(u, v)=IA(u,v)-Ic(u,v)
Wherein, (u, v) is the pixel coordinate in image, IR、IA、ICRespectively Ri-j、A′i-jAnd CiIn pixel value.
5. light-field data compression method according to claim 1, it is characterised in that complete is concentrated to light field data in step A3
The center sub-aperture image C in portioniThe method being scanned is that zigzag is scanned or S-shaped scanning, and wherein zigzag scanning represents phase
Two center sub-aperture image C in the ranks of neighbouriFrom beginning to end, S-shaped scanning represents the center sub-aperture image C between adjacent rowsiHead
It is connected or afterbody is connected.
6. light-field data compression method according to claim 1, it is characterised in that complete is concentrated to light field data in step A3
The residual image R in portioni-jThe method being scanned is that zigzag is scanned or S-shaped scanning, and wherein zigzag scanning represents adjacent rows
Between residual image Ri-jFrom beginning to end, S-shaped scanning represents the residual image R between adjacent rowsi-jHead is connected or afterbody phase
Even.
7. light-field data compression method according to claim 3, it is characterised in that complete is concentrated to light field data in step A3
The residual image R in portioni-jThe method being scanned is scanning of turn-taking, and scanning of turn-taking is represented to 8 residual errors in sub- subaperture image group
Image Ri-jTurn-take after scanning, with the residual image R in other group of adjacent sub-aperture image setsi-jJoin end to end.
8. light-field data compression method according to claim 1, it is characterised in that step A4 also includes should to whole lists
Property matrix Hi-jCoding compression.
9. light-field data compression method according to claim 1, it is characterised in that step A4 also includes should to whole lists
Property matrix Hi-jCarry out block code compression.
10. light-field data compression method according to claim 1, it is characterised in that step A4 is specially：To centered video
Sequence VCWith residual video sequence VRIt is utilized respectively video encoder and is compressed coding.
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| CN107770537A (en) * | 2017-11-02 | 2018-03-06 | 中国科学技术大学 | Based on the light field image compression method linearly rebuild |
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| CN109099857A (en) * | 2018-08-24 | 2018-12-28 | 中国工程物理研究院机械制造工艺研究所 | A kind of sub-aperture stitching method based on SURF characteristic matching |
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| CN110191359A (en) * | 2019-05-16 | 2019-08-30 | 华侨大学 | A kind of light field image compression method chosen based on crucial sub-aperture image |
| CN110392266A (en) * | 2019-07-25 | 2019-10-29 | 清华大学深圳研究生院 | A kind of light field method for video coding and terminal device based on pseudo- video sequence |
| CN111147848A (en) * | 2019-12-30 | 2020-05-12 | 清华大学深圳国际研究生院 | Light field video coding method based on content self-adaptation |
| CN111182312A (en) * | 2020-01-03 | 2020-05-19 | 杭州电子科技大学 | Hierarchical residual error light field video coding method |
| CN111757125A (en) * | 2019-03-29 | 2020-10-09 | 曜科智能科技（上海）有限公司 | Multi-view video compression method based on light field, device, equipment and medium thereof |
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