# US 12,015,855 B2 · System and method for synthesizing low-light images > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,015,855 B2 - Document ID: US12015855B2 - Status: Granted - Kind: B2 - Application number: 17/566,425 - Filed: 2021-12-30 - Published: 2023-05-18 - Granted: 2024-06-18 - Earliest claimed: 2021-11-16 - Assignees: Samsung Electronics Co., Ltd. - Applicants: Samsung Electronics Co., Ltd. - Inventors: Abdullah Abuolaim; Abhijith Punnappurath; Abdelrahman Abdelhamed; Michael Scott Brown; Aleksai Levinshtein - Web page: https://patentgrep.com/patent/US12015855B2 ## CPC - H04N 23/73: by influencing the exposure time - H04N 23/80: Camera processing pipelines; Components thereof - H04N 23/617: Upgrading or updating of programs or applications for camera control - H04N 23/74: by influencing the scene brightness using illuminating means - H04N 23/88: for colour balance, e.g. white-balance circuits or colour temperature control - H04N 25/60: Noise processing, e.g. detecting, correcting, reducing or removing noise - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract A method of generating a low-light image is provided. The method includes receiving a raw image, removing an amount of first illumination from the raw image, applying a low exposure condition to the raw image having the amount of first illumination removed, and applying an amount of low-light illumination to the raw image having the applied low exposure condition. ## Claims ### Claim 1 A method of generating a low-light image, comprising: obtaining a raw image captured by a sensor; removing an amount of first illumination from the raw image; applying a low exposure condition to the raw image having the amount of first illumination removed; obtaining a low-light image by applying an amount of second illumination less than the amount of first illumination to the raw image having the applied low exposure condition; obtaining a noisy image by applying an amount of noise to the low-light image having the applied amount of second illumination; and training a neural network model for denoising an image based on the low-light image and the noisy image. ### Claim 2 (depends on 1) The method of claim 1, wherein the amount of low-light illumination comprises an amount of nighttime illumination. ### Claim 3 (depends on 1) The method of claim 1, wherein obtaining the low-light image comprises applying a single global illuminant to the raw image having the applied low exposure condition. ### Claim 4 (depends on 1) The method of claim 1, wherein obtaining a low-light image comprises applying a plurality of local illuminants to the raw image having the applied low exposure condition. ### Claim 5 (depends on 4) The method of claim 4, further comprising detecting at least one position of a light source in the raw image, wherein at least one of the plurality of local illuminants is applied to the at least one detected position of the light source. ### Claim 6 (depends on 1) The method of claim 1, wherein the amount of second illumination is applied based on an ambient light mask with a predetermined color and predetermined scale. ### Claim 7 A system for generating a low-light image, comprising: a memory storing instructions; and a processor configured to execute the instructions to: obtain a raw image captured by a sensor; remove an amount of first illumination from the raw image; apply a low exposure condition to the raw image having the amount of first illumination removed; obtain a low-light image by applying an amount of second illumination less than the amount of first illumination to the raw image having the applied low exposure condition; obtain a noisy image by applying an amount of noise to the low-light image having the applied amount of second illumination; and train a neural network model for denoising an image based on the low-light image and the noisy image. ### Claim 8 (depends on 7) The system of claim 7, wherein the amount of low-light illumination comprises an amount of nighttime illumination. ### Claim 9 (depends on 7) The system of claim 7, wherein the processor is further configured to apply a single global illuminant to the raw image having the applied low exposure condition. ### Claim 10 (depends on 7) The system of claim 7, wherein the processor is further configured to apply a plurality of local illuminants to the raw image having the applied low exposure condition. ### Claim 11 (depends on 10) The system of claim 10, wherein the processor is further configured to execute the instructions to detect at least one position of a light source in the raw image, wherein at least one of the plurality of local illuminants is applied to the at least one detected position of the light source. ### Claim 12 (depends on 7) The system of claim 7, wherein the amount of second illumination is applied based on an ambient light mask with a predetermined color and predetermined scale. ### Claim 13 A non-transitory computer-readable storage medium configured to store instructions that, when executed, cause at least one processor to: obtain a raw image captured by a sensor; remove an amount of first illumination from the raw image; apply a low exposure condition to the raw image having the amount of first illumination removed; obtain a low-light image by applying an amount of second illumination less than the amount of first illumination to the raw image having the applied low exposure condition; obtain a noisy image by applying an amount of noise to the low-light image having the applied amount of second illumination; and train a neural network model for denoising an image based on the low-light image and the noisy image. ### Claim 14 (depends on 13) The storage medium of claim 13, wherein the amount of low-light illumination comprises an amount of nighttime illumination. ### Claim 15 (depends on 13) The storage medium of claim 13, wherein the instructions, when executed, further cause the at least one processor to apply a single global illuminant to the raw image having the applied low exposure condition. ### Claim 16 (depends on 13) The storage medium of claim 13, wherein the instructions, when executed, further cause the at least one processor to apply a plurality of local illuminants to the raw image having the applied low exposure condition. ### Claim 17 (depends on 16) The storage medium of claim 16, wherein the instructions, when executed, further cause the at least one processor to detect at least one position of a light source in the raw image, wherein at least one of the plurality of local illuminants is applied to the at least one detected position of the light source.