Image analysis – Applications – 3-d or stereo imaging analysis
Reexamination Certificate
1998-06-12
2003-03-18
Werner, Brian (Department: 2721)
Image analysis
Applications
3-d or stereo imaging analysis
C382S236000, C382S250000
Reexamination Certificate
active
06535629
ABSTRACT:
This invention relates to storing and/or transmitting 3D images. 3D images can be formed in a variety of ways. No matter how they are formed, there is substantially more information content in a 3D image than in a corresponding 2D image—the depth information is additional. Storing and/or transmitting 3D images therefore is more demanding of storage space or bandwidth than for 2D images, much as colour images are more demanding than monochrome images. Coloured 3D images would appear on the face of it to be very demanding, but the problems can be eased by data compression techniques, surprisingly to such a degree as brings 3D television into immediate prospect.
Methods for making (and viewing) 3D images—autostereoscopic images, i.e. not requiring aids such as spectacles to view—are known and involve the use of an optical imaging system comprising a microlens array of small spherical or lenticular (i.e. cylindrical) lenses. Such imaging techniques produce images which are particularly well adapted, as it turns out, to compression, and the present invention is particularly concerned with such imaging techniques.
The invention comprises a method for storing and/or transmitting 3D image information comprising the steps of:
producing an image to be stored and/or transmitted comprising an array of strongly correlated neighbouring sub-images;
casting the sub-images on to a pixel screen capturing the sub-images as electronic data;
compressing the electronic data by eliminating redundancies associated with the sub-images;
storing and/or transmitting the compressed data;
the compression being reversible so as to expand the data to re-create the sub-images for viewing as a 3-D image through an optical viewing system comprising a microlens or lenticular array.
The image may be of a scene and produced using an optical imaging system comprising a microlens or lenticular array of small spherical or cylindrical lenses each of which images the scene from a slightly different viewpoint.
The image may however be electronically generated or partially electronically generated. Photographic images may be electronically scanned and captured as electronic data.
Small sub-image data sectors generated by the optical system are fed successively into an encoder where a previously fed sub-image is substracted from the most recently fed-in sub-image by a differential pulse code modulation (D P C M) coding technique to remove redundancies between the sub-images.
Redundancies may be eliminated within the sub-images themselves by techniques for example normally used in compression of two dimensional image data such for example as a discrete cosine transform (DCT) coding scheme.
A 3D-DCT coding scheme may be applied directly to groups of sub-images, the use of the third transform dimension eliminating inter-sub-group redundancies with the first two transform dimensions used to remove intra-sub-image redundancies.
A quantisation function may be applied to the coded data that sets small values to zero and transforms all other non-zero values to nearest values in a set of preferred values.
The coded data may then be entropy encoded.
The above coding schemes are suitable for compressing still image data. For storing and/or transmitting moving 3D image information a DPCM/3D-DCT coding scheme may be used, the DPCM coding decorrelating image data in the temporal domain and the 3D-DCT scheme eliminating spatial redundancies.
A hybrid DPCM2/DCT scheme may be used for compression of moving 3D image information, in which a 2D-DCT scheme decorrelates and hence removes redundancies within each sub-image and two DPCM loops are used, one to remove redundancies between sub-images in a spatial sense while the second is used to remove temporal (inter-frame) redundancies.
Both of these moving 3D-image compression schemes may make use of motion compensation to achieve greater overall image reduction.
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Aggoun Amar
Davies Neil
Forman Matthew Charles
McCormick Malcolm
De Montfort University
Gunter, Jr. Charles D.
Werner Brian
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