Illuminant Estimation Using RGB Camera Image and Ambient Light Sensor Signal

Illuminant estimation in camera color space is a critical step in the image signal processing pipeline, which is commonly performed based on the RGB RAW images captured by a camera. Recently, most smartphones are equipped with an ambient light sensor (ALS) around the camera. In this work, we propose an illuminant estimation method (i.e., RACC) using both RGB RAW images and ALS signals as the inputs. A large dataset containing both RGB RAW images and ALS signals of more than 1300 scenes was collected, which was used to develop and evaluate the proposed RACC method. The results show that the RACC method results in much smaller angular errors and requires much fewer computational resources. In particular, the method was designed with a training mechanism to consider a practical challenge of incomplete or missing ALS signals under low light conditions, which was verified to have stable performance. These clearly suggest that the RACC method can be deployed for practical applications.