This Application is a Section 371 National Stage Application of International Application No. PCT/FR2012/050934, filed Apr. 26, 2012, which is incorporated by reference in its entirety and published as WO 2012/150407 on Nov. 8, 2012, not in English.
None.
None.
The present invention relates generally to the domain of image processing, and more specifically to encoding and decoding integral images and sequences of integral images.
The invention can in particular, but not exclusively, be applied to the video encoding used in existing video encoders and the amendments thereof (MPEG, H.264, H.264 SVC, H.264 MVC, etc.) or future video encoders (ITU-T/VCEG (H.265) or ISO/MPEG (HEVC)), and to the corresponding decoding.
Integral imaging is a technique for displaying images in relief. It is considered to be particularly promising in the development of 3D television, in particular because it offers a total parallax, as opposed to a stereoscopic image display.
An integral image conventionally comprises a large number of basic images that represent the different angles of a scene in three dimensions. The compression of an integral image therefore amounts to compressing all of the elemental images.
A known method for compressing integral images involves using the MPEG-4 AVC video format to encode each of the elemental images of an integral image. Such a method is relatively direct, because it simply involves processing the integral images as a traditional video sequence.
A drawback of such a method lies in the fact that the spatial and temporal redundancy is reduced indiscriminately. The specific form of integral images, according to which elemental images are likely to present numerous spatial and temporal redundancies between one another, is therefore not exploited optimally.
A more efficient method for compressing integral images without moving outside the MPEG-4 AVC standard involves reorganizing the elemental images. This enables the redundancies between elemental images to be exploited, but lots of redundant information remains unexploited, in particular the significant correlation between the elemental images of a current integral image and the corresponding elemental images of adjacent integral images.
Another known method involves encoding integral images using a 3D-DCT compression algorithm, as described in the document R. Zaharia, A. Aggoun, M. McCormick, ‘Adaptive 3D-DCT compression algorithm for continuous parallax 3D integral imaging’, Signal Processing: Image Communication 17 (2002) 231-242. This method is relatively close to the aforementioned methods based on the MPEG-4 AVC standard. Indeed, the reorganization of the elemental images is identical. The difference between this other known method and the aforementioned methods lies in the encoding structure of image sequences. This method undoubtedly improves the compression of integral images, but does not enable the redundancies characteristic of integral images to be reduced.
According to a first aspect, the present invention relates to a method for encoding at least one integral image representing at least one object in perspective in a scene and comprising a plurality of elemental images, such a method implementing a step in which a plurality of K sub-images is generated from the plurality of elemental images.
The encoding method according to the invention is noteworthy in that it implements the following steps:
On account of the reorganization of the sub-images thus arranged in relation to one another according to a predetermined pattern, such an arrangement makes it possible to optimally exploit the multiple spatial and temporal redundancies between the elemental images of an integral image. This makes the encoding of integral images more efficient.
Such a reorganization of the sub-images combined with adaptive compression of these sub-images also obviates the need to include redundant, and therefore unnecessary, encoding information in the signal to be transmitted. This generates a significant reduction in signaling costs.
According to a specific embodiment, the adaptive compression step implements the following sub-steps for a current multi-view image:
Such an arrangement makes it possible to significantly reduce encoding cost, in particular in the following two cases:
According to another specific embodiment, MVC encoding is used, if at least two of the K motion vectors calculated have different values.
Such an arrangement makes it possible to efficiently encode integral images, taking advantage of the spatial and temporal redundancies thereof by subjecting them to the standard MVC (English abbreviation of “multi-view coding”) encoding technique used until now for encoding multi-view images.
In order to encode such integral images even more efficiently, the invention proposes a variant comprising a modified MVC coding structure.
Accordingly, the present invention relates to a device for encoding at least one integral image representing at least one object in perspective in a scene and comprising a plurality of elemental images, such a device comprising means for generating a plurality of K sub-images from the plurality of elemental images.
Such an encoding device is noteworthy in that it comprises:
According to a specific embodiment, the adaptive compression means include, for a current multi-view image:
According to another specific embodiment, MVC encoding is used if at least two of the K motion vectors calculated have different values.
According to a second aspect, the invention relates to a method for decoding a data signal representing at least one integral image that has been previously encoded, said integral image representing at least one object in perspective in a scene and comprising a plurality of elemental images.
This method according to the invention is noteworthy in that it implements the following steps:
According to a specific embodiment, the adaptive decompression step implements the following sub-steps for a current integral image to be reconstructed:
According to another specific embodiment, if the data signal contains K motion vector values, MVC decoding is used.
Accordingly, the invention relates to a device for decoding a data signal representing at least one integral image that has been previously encoded, said integral image representing at least one object in perspective in a scene and comprising a plurality of elemental images.
Such a device is noteworthy in that it comprises:
According to a specific embodiment, the adaptive decompression means include:
According to another specific embodiment, MVC decoding is used if the data signal contains K motion vector values.
According to a third aspect, the invention relates to a computer program containing instructions for implementing one of the methods according to the invention, when run on a computer.
The invention also relates to a computer program on a data medium, this program containing the instructions for implementing one of the methods according to the invention, as described above.
This program can use any programming language, and may be source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any other form required.
The invention also relates to a computer-readable data medium containing the instructions for a computer program, as mentioned above.
The data medium can be any unit or device able to store the program. For example, the medium may be a storage medium, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a magnetic storage medium, for example a floppy disk or a hard disk.
Moreover, the data medium may be a transmittable medium such as an electric or optical signal, that can be routed via an electrical or optical cable, by radio or using other means. The program according to the invention may in particular be downloaded from an Internet network.
Alternatively, the data medium may be an integrated circuit incorporating the program, the circuit being designed to run or to be used in the running of the present method.
The decoding method, the encoding device, the decoding device and the computer programs mentioned above provide at least the same benefits as provided by the encoding method according to the present invention.
Other features and advantages are set out in the preferred embodiments described with reference to the figures, in which:
An embodiment of the invention, in which the encoding method according to the invention is used to encode a sequence of integral images, is described below.
The encoding method according to the invention is shown in the form of an algorithm comprising steps C1 to C5, as shown in
According to the embodiment of the invention, the encoding method according to the invention is implemented in an encoding device CO shown in
The first step C1, shown in
An example of integral-image acquisition is shown in
In the example shown, the integral image InI represents an object OBJ in perspective in a scene SC in three dimensions. The integral image InI is acquired in the direction of the arrow F1 by a CCD (English abbreviation for “Charged-Coupled Device”) 2D scanner that is indicated with reference sign SCN in
In the example shown in
During acquisition, light rays from the object OBJ pass through each microlens ML1, ML2, ML3 and ML4, then hit the pixels of each cell CL1, CL2, CL3 and CL4, in the focal plane PF of said microlenses. In consideration of the specific arrangement of the lenticular screen RL and of the pixel matrix forming the screen EC, the light rays:
In a known manner, each angle of incidence corresponds to a specific viewing angle at which an observer can see the object OBJ in perspective. The values of these angles are limited by the value of the viewing angle of a microlens ML1, ML2, ML3, ML4. Such a viewing angle, corresponding to the viewing angle of the microlens ML2, is shown using a full bold line in
For the sake of clarity in
In the example shown, following the acquisition step C1, four images of the object OBJ from four different angles are recorded since there are four microlenses. In a known manner, these four images constitute the elemental images of the integral image InI.
During a step C2 shown in
An example of such a step C2 in which sub-images are generated from the integral image shown in
In the example shown, the integral image InI includes four elemental images IE1, IE2, IE3 and IE4 comprising respectively five differently colored pixels as mentioned above. The following is performed during the sub-image generation step C2:
grouping, in a first sub-image SI1, of the respective pixels P11, P21, P31, P41 of each of the elemental images IE1, IE2, IE3, IE4 corresponding to a first viewing angle in perspective,
For the sake of clarity of the figure, only the first two groupings are shown by the arrows.
During a step C3 shown in
The form of the pattern is selected to optimize the spatial and temporal correlation between the sub-images generated.
Said arrangement step C3 is implemented by a software module ASI_CO as shown in
The different forms of patterns are shown in
In all cases, for a plurality K of sub-images SI1, SI2, . . . , SIK generated during step C2, the sub-image SIr (1≦r≦K) for which the corresponding r-th viewing angle has a zero value, constitutes, according to the invention, the reference view Vr of the multi-view image MVV1 to be formed at time t1 and is placed at the center of said multi-view image.
According to a first preferential example shown in
According to a second example shown in
According to a fourth example shown in
During a subsequent step C4 shown in
Such a step is implemented by a CMP compression software module shown in
Again with reference to
Such a step is implemented by an entirely conventional SGM segmentation software module, which is shown in
During a sub-step C42 shown in
Such a step is performed by a first calculation software module CAL1_CO as shown in
According to a first alternative shown in
MVi=ΔZ×tan θi where ΔZ represents the depth moved by the object OBJ and θi represents the viewing angle of an i-th pixel pji of a j-th pixel cell considered CLj (1≦j≦4).
As MVi and θi are known values to the encoder CO, the calculation
is performed during a step C43a.
According to a second alternative shown in
According to a third alternative (not shown) for which the object OBJ moves in three dimensions in the scene SC or only in two dimensions, all of the current motion vectors MV1n, MV2n, . . . , MVKn are calculated during a sub-step C43c.
During a sub-step C44 shown in
Such a step is performed by a second prediction software module PRD_CO as shown in
During a sub-step C45 shown in
During a sub-step C46a shown in
During a sub-step C46b shown in
Such an encoding step C46a or C46b is performed by an entirely conventional encoder, as shown in
During a step C46c, the different motion vectors calculated during the aforementioned sub-step C43c are encoded.
According to the invention, in the case of the multi-view images shown in
With regard to the multi-view image formed preferentially in
As shown in
On completion of the encoding step C46a, C46b or C46c, an encoded video signal SG is generated and sent during a step C5 shown in
The encoding method described above is repeated for a plurality of integral images belonging to a given sequence.
During a first step D1, the current multi-view image MVVn is decompressed using the information contained in the signal SG received. Said decompression is adaptive because it is implemented as a function of the information on the type of motion performed by the object OBJ in the scene SC, as contained in the signal SG received.
Such a step is performed by a decompression module DCMP as shown in
Again with reference to
If the signal SG contains the depth value ΔZ that the object OBJ has moved exclusively in the scene SC, this value is extracted during a sub-step D12a, then, for each current sub-image to be reconstructed, the respective motion vector thereof MV1n, MV2n, . . . , MVKn is calculated during a sub-step D13a, according to the relationship MVi=ΔZ×tan θi in which 1≦i≦K.
If the signal SG contains a single motion vector value MVi as calculated in the aforementioned encoding sub-step C43b, this value is extracted during a sub-step D12b, then, for each current sub-image to be reconstructed, the respective motion vector thereof MV1n, MV2n, . . . , MVKn is calculated during a sub-step D13b, according to the relationship MV1n=MV2n= . . . =MVKn=MVi.
If the signal SG contains different motion vector values MV1n, MV2n, . . . , MVin, . . . , MVKn as calculated in the aforementioned encoding sub-step C43c, these values are extracted during a sub-step D12c.
Each of the steps D13a and D13b is implemented by a first calculation software module CAD_DO as shown in
The following is performed during a subsequent sub-step D14:
Said step D14 is performed by a second prediction software module PRD_DO as shown in
During a sub-step D15, the predicted sub-images obtained in step D14 are decoded using a decoder DEC shown in
During a subsequent decoding step D2, the current decoded sub-images SID1, SID2, . . . , SIDK obtained in sub-step D15 are arranged in the order in which the current sub-images were decoded, this order complying with the direction of one of the patterns shown in
Said arrangement step D2 is performed by a software module ASI_DO as shown in
During a subsequent decoding step D3, a plurality of elemental images EI is generated on the basis of the arrangement of the decoded sub-images implemented in the previous step D2.
Such a step is implemented by a elemental-image generation module MGEI.
Once all of the decoded elemental images have been generated, the integral image InI is reconstructed during a step D4 on the basis of the elemental images generated in step D3.
Such a step is implemented by an image-reconstruction module MRI as shown in
The decoding method described above is repeated for a plurality of integral images to be reconstructed belonging to a given sequence.
Naturally, the embodiments described above are provided exclusively for illustrative purposes and are in no way limiting, and numerous modifications could easily be made by the person skilled in the art without thereby moving outside the scope of the invention.
Number | Date | Country | Kind |
---|---|---|---|
11 53852 | May 2011 | FR | national |
Filing Document | Filing Date | Country | Kind | 371c Date |
---|---|---|---|---|
PCT/FR2012/050934 | 4/26/2012 | WO | 00 | 11/5/2013 |
Publishing Document | Publishing Date | Country | Kind |
---|---|---|---|
WO2012/150407 | 11/8/2012 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
20090153652 | Barenbrug | Jun 2009 | A1 |
20100238313 | Ohki | Sep 2010 | A1 |
20110280300 | Tourapis | Nov 2011 | A1 |
Number | Date | Country |
---|---|---|
2306742 | Apr 2011 | EP |
Entry |
---|
R. Zaharia et al., “Adaptive 3D-DCT compression algorithm for continuous parallax 3D integral imaging”, Signal Processing: Image Communication 17 (2002) 231-242. |
International Search Report and Written Opinion dated Jun. 25, 2012 for corresponding International Application No. PCT/FR20121/050934, filed Apr. 26, 2012. |
Kang H. H. et al., “Efficient Compression of Motion-Compensated Sub-Images with KarhunenLoeve Transform in Three-Dimensional Integral Imaging”, Optics Communications, North-Hollans Publishing Co. Amsterdam, NL, vol. 283, No. 6, Mar. 15, 2010 (Mar. 15, 2010), pp. 920-928, XP026868630. |
Dick J. et al., “3D Holoscopic Video Coding Using MVC” EUROCON—International Conference on Computer as a Tool (EUROCON), 2011 IEEE, Apr. 27, 2011 (Apr. 27, 2011), pp. 1-4, XP002653889. |
Olsson R., “Synthesis, Coding, and Evaluation of 3D Images Based on Integral Imaging”, MID Sweden University Doctoral Thesis, Mittuniversitetet, Sundsvall, Sweden, no. Doctoral Thesis No. 55, Jan. 1, 2008 (Jan. 1, 2008), pp. I-XXI, 1, XP001562238. |
Olsson R. et al., “Evaluation of a Combined Pre-Processing and H.264-Compression Scheme for 3D Integral Images”, Visual Communications and Image Processing; Jan. 30, 2007-Jan. 2, 2007; San Jose, Jan. 30, 2007 (Jan. 30, 2007), XP030081158. |
Anthony Verto et al., “Towards a 3D Video Format for Auto-Stereoscopic Displays”, Applications of Digital Image Processing XXXI : Aug. 11-14, 2008, San Diego, California, USA; [Proceedings of SPIE ; 7073], SPIE, Bellingham, Wash, vol. 7073, No. TR2008-057, Aug. 11, 2008 (Aug. 11, 2008), pp. 1-12, XP002603277. |
Ying Chen et al., “The Emerging MVC Standard for 3D Video Services”, Eurasip Journal on Advances in Signal Processing, vol. 2009, Mar. 5, 2008 (Mar. 5, 2008), pp. 786015-1, XP002634721. |
English translation of the Written Opinion dated Jun. 25, 2012 for corresponding International Application No. PCT/FR2012/050934, filed Apr. 26, 2012. |
Number | Date | Country | |
---|---|---|---|
20140085417 A1 | Mar 2014 | US |