Invention Grant
- Patent Title: Systems and methods for transforming raw sensor data captured in low-light conditions to well-exposed images using neural network architectures
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Application No.: US16254796Application Date: 2019-01-23
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Publication No.: US11037278B2Publication Date: 2021-06-15
- Inventor: Syed Waqas Zamir , Salman Hameed Khan , Fahad Shahbaz Khan , Aditya Arora , Ling Shao
- Applicant: Inception Institute of Artificial Intelligence, Ltd.
- Applicant Address: AE Abu Dhabi
- Assignee: Inception Institute of Artificial Intelligence, Ltd.
- Current Assignee: Inception Institute of Artificial Intelligence, Ltd.
- Current Assignee Address: AE Abu Dhabi
- Agency: Bryan Cave Leighton Paisner LLP
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06N3/08 ; G06T5/50 ; G06N20/00

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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