Invention Grant
- Patent Title: Denoising images rendered using Monte Carlo renderings
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Application No.: US17093852Application Date: 2020-11-10
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Publication No.: US11983854B2Publication Date: 2024-05-14
- Inventor: Mustafa Isik , Michael Yanis Gharbi , Matthew David Fisher , Krishna Bhargava Mullia Lakshminarayana , Jonathan Eisenmann , Federico Perazzi
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FINCH & MALONEY PLLC
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06N3/045 ; G06N20/00 ; G06T3/40 ; G06T5/70 ; G06V10/56 ; G06V10/60

Abstract:
A plurality of pixel-based sampling points are identified within an image, wherein sampling points of a pixel are distributed within the pixel. For individual sampling points of individual pixels, a corresponding radiance vector is estimated. A radiance vector includes one or more radiance values characterizing light received at a sampling point. A first machine learning module generates, for each pixel, a corresponding intermediate radiance feature vector, based on the radiance vectors associated with the sampling points within that pixel. A second machine learning module generates, for each pixel, a corresponding final radiance feature vector, based on an intermediate radiance feature vector for that pixel, and one or more other intermediate radiance feature vectors for one or more other pixels neighboring that pixel. One or more kernels are generated, based on the final radiance feature vectors, and applied to corresponding pixels of the image, to generate a lower noise image.
Public/Granted literature
- US20220148135A1 DENOISING IMAGES RENDERED USING MONTE CARLO RENDERINGS Public/Granted day:2022-05-12
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