Systems and methods for transforming raw sensor data captured in low-light conditions to well-exposed images using neural network architectures
US11037278B2 · kind B2 · utility
5Cited by
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20Claims
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Key dates
| Filing date | Jan 23, 2019 |
| Grant date | Jun 15, 2021 |
| Priority date | — |
| Expiry date | Mar 17, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This disclosure relates to improved techniques for generating images from raw image sensor data captured in low-light conditions without the use of flash photography. The techniques described herein utilize a neural network architecture to transform the raw image sensor data into well-exposed images. The neural network architecture can be trained using a multi-criterion loss function that jointly models both pixel-level and feature-level properties of the images. The images output by the neural network architecture can be provided to a contrast correction module that enhances the contrast of the images.
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