METHOD, COMPUTER PROGRAM, SYSTEM AND COMPUTER SYSTEM FOR ELIMINATING NOISE IN AN IMAGE SEQUENCE

Patent number:

WO21229129

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Provided are methods, programs and systems for eliminating noise in an image sequence produced by a method for generating images with volumetric data, using an algorithm for tracing light ray paths in participating media. Each image in the sequence comprises pixels, and the path-tracing algorithm produces path samples for each pixel. These methods comprise, for each pixel of a current image in the sequence: temporarily reprojecting the pixel according to a motion vector to obtain an average accumulated colour and a predictive model of the pixel; averaging a colour of the pixel with the average accumulated colour to obtain an updated average accumulated colour; including the updated average accumulated colour in a feature vector; and determining a final colour of the pixel by updating the predictive model according to the updated feature vector and obtaining the final colour from the updated predictive model.

Countries:
Spain
Regions:
Galicia
Centers:
UNIVERSIDADE DA CORUNA, UNIVERSITAT AUTONOMA DE BARCELONA
Other entities:
This patent is co-owned by the UDC and the UAB
Sectors:
Health
Other
Automotive & Rail
Subsectors:
Computer technology
TRL Level:
TRL 4 – technology validated in lab
BRL Level:
BRL2: First business concept described market potential & competitive overview
PDF Link:
Download here
Video Link:
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Sustainable Development Goal:
SDG03: Good health and well-being
Applications

This technique introduces one of the first practical approximations for the noise elimination in real-time, suitable for the volumetric data visualization systems based on 3-D reconstruction algorithms simulating photorrealistic illumination effects (CVR). It allows a significantly reduction in the levels of noise in sequency of images generated by MC rendering techniques (VPT)

Comments

This technique and technology improves the quality of image at a very advanced levels, which makes it suitable for 3-D visualization, medical (diagnostic imaging), AR and VR, autonomous driving, musealistic installations...

Currently working on TRL 5 achievement with external institutions, and open to discuss collaboration opportunities.

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