Einzeltreffer — DigiBib

Real-time light field reconstruction for defocus blur may be used to handle the case of simultaneous defocus and motion blur. By carefully introducing a few approximations, a very efficient sheared reconstruction filter is derived, which produces high quality images even for a very low number of input samples in some embodiments. The algorithm may be temporally robust, and is about two orders of magnitude faster than previous work, making it suitable for both real-time rendering and as a post-processing pass for high quality rendering in some embodiments.

Titel:	Layered Reconstruction for Defocus and Motion Blur
Link:	Find this record on USPTO (Volltext)
Veröffentlichung:	2015
Medientyp:	Patent
Sonstiges:	Nachgewiesen in: USPTO Patent Applications Sprachen: English Document Number: 20150206340 Publication Date: July 23, 2015 Appl. No: 14/274958 Application Filed: May 12, 2014 Claim: 1. A method comprising: grouping input samples from a sampled light field into partitions; integrating over lens positions and time within a frame; convolving in screen space using a reconstruction filter; and compositing layers in depth order using alpha blending based on opacity values. Claim: 2. The method of claim 1 including generating said light field by stochastic sampling in a distributed ray tracer or stochastic rasterizer. Claim: 3. The method of claim 1 including generating said light field using interleaved sampling in a rasterizer or ray tracer. Claim: 4. The method of claim 1 including generating the light field with a depth value, a three dimensional motion vector, and a radiance value for each five dimensional input coordinates. Claim: 5. The method of claim 1 wherein grouping into partitions includes deriving a set of depth layers for each screen space tile and applying a common sheared reconstruction filter in five dimensions for all samples within a partition. Claim: 6. The method of claim 1 including transforming the light field from a moving coordinate system at a depth to a light field at a sensor. Claim: 7. The method of claim 6 including using a coordinate transformed from angles to lens coordinates at the sensor and expressing the motion operator in terms of rotations and a motion purely along a coordinate axis aligned with a coordinate axis in screen space. Claim: 8. The method of claim 1 including separating the filter into integration and convolution paths and including integrating by scaling and reprojecting all samples to the center of a lens at a unique time. Claim: 9. The method of claim 8 including expressing the convolution path as a separable Gaussian filter in screen space. Claim: 10. The method of claim 1 including approximating irradiance by pre-integrating the radiance and opacity over the lens and shutter separately within each layer. Claim: 11. One or more non-transitory computer readable media storing instructions executed by a processor to perform a sequence comprising: grouping input samples from a sampled light field into partitions; integrating over lens positions and time within a frame; convolving in screen space using a reconstruction filter; and compositing layers in depth order using alpha blending based on opacity values. Claim: 12. The media of claim 11, said sequence including generating said light field by stochastic sampling in a distributed ray tracer or stochastic rasterizer. Claim: 13. The media of claim 11, said sequence including generating said light field using interleaved sampling in a rasterizer or ray tracer. Claim: 14. The media of claim 11, said sequence including generating the light field with a depth value, a three dimensional motion vector, and a radiance value for each five dimensional input coordinates. Claim: 15. The media of claim 11 wherein grouping into partitions includes deriving a set of depth layers for each screen space tile and applying a common sheared reconstruction filter in five dimensions for all samples within a partition. Claim: 16. The media of claim 11, said sequence including transforming the light field from a moving coordinate system at a depth to a light field at a sensor. Claim: 17. The media of claim 16, said sequence including using a coordinate transformed from angles to lens coordinates at the sensor and expressing the motion operator in terms of rotations and a motion purely along a coordinate axis aligned with a coordinate axis in screen space. Claim: 18. The media of claim 11, said sequence including separating the filter into integration and convolution paths and including integrating by scaling and reprojecting all samples to the center of a lens at a unique time. Claim: 19. The media of claim 18, said sequence including expressing the convolution path as a separable Gaussian filter in screen space. Claim: 20. The media of claim 11, said sequence including approximating irradiance by pre-integrating the radiance and opacity over the lens and shutter separately within each layer. Claim: 21. An apparatus comprising: a processor to: group input samples from a sampled light field into partitions, integrate over lens positions and time within a frame, convolve in screen space using a reconstruction filter, and composite layers in depth order using alpha blending based on opacity values; and a storage coupled to said processor. Claim: 22. The apparatus of claim 21, said processor to generate said light field by stochastic sampling in a distributed ray tracer or stochastic rasterizer. Claim: 23. The apparatus of claim 21, said processor to generate said light field using interleaved sampling in a rasterizer or ray tracer. Claim: 24. The apparatus of claim 21, said processor to generate the light field with a depth value, a three dimensional motion vector, and a radiance value for each five dimensional input coordinates. Claim: 25. The apparatus of claim 21 wherein grouping into partitions includes deriving a set of depth layers for each screen space tile and applying a common sheared reconstruction filter in five dimensions for all samples within a partition. Claim: 26. The apparatus of claim 21, said processor to transform the light field from a moving coordinate system at a depth to a light field at a sensor. Claim: 27. The apparatus of claim 26, said processor to use a coordinate transformed from angles to lens coordinates at the sensor and expressing the motion operator in terms of rotations and a motion purely along a coordinate axis aligned with a coordinate axis in screen space. Claim: 28. The apparatus of claim 21 including an operating system. Claim: 29. The apparatus of claim 21 including a battery. Claim: 30. The apparatus of claim 21 including firmware and a module to update said firmware. Current International Class: 06; 06; 06; 06; 06

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Layered Reconstruction for Defocus and Motion Blur