US 12,335,667 B2
Apparatus and method for white balance editing
Mahmoud Nasser Mohammed Afifi, Toronto (CA); and Michael Scott Brown, Toronto (CA)
Assigned to SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed by SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed on Feb. 28, 2023, as Appl. No. 18/175,887.
Application 18/175,887 is a continuation of application No. 17/077,837, filed on Oct. 22, 2020.
Claims priority of provisional application 62/939,286, filed on Nov. 22, 2019.
Prior Publication US 2023/0209029 A1, Jun. 29, 2023
Int. Cl. G06T 5/00 (2024.01); G06T 3/40 (2006.01); G06T 5/50 (2006.01); H04N 9/73 (2023.01); G06F 3/04847 (2022.01)
CPC H04N 9/73 (2013.01) [G06T 3/40 (2013.01); G06T 5/50 (2013.01); G06F 3/04847 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20084 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A mobile device comprising:
a camera module including a lens module and an image sensing module configured to obtain first image data from light collected through the lens module;
a sensor module configured to obtain information about a shooting condition;
a storage module storing information about a plurality of artificial intelligence (AI) models for white-balance control;
an image signal processor configured to obtain second image data by processing at least one of the stored AI models; and
at least one application processor,
wherein the at least one application processor is configured to:
determine an AI model corresponding to the shooting condition among the plurality of AI models, for white-balance control, stored in the storage module, based on the information about the shooting condition o7btained by the sensor module; and
control the determined AI model to be loaded into the image signal processor, and
the image signal processor is further configured to input the first image data to the determined AI model so as to obtain the second image data with a white balance controlled to correspond to the shooting condition,
wherein the shooting condition is a condition for identifying whether the mobile device is located indoors or outdoors,
wherein the plurality of AI models shares a common encoder model and comprises a plurality of different decoder models.