White Balance Correction for RCCG Sensors Using QE Curve Mapping
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Solution Overview
Problem
Existing image sensors using certain color filter arrays, such as RCCG arrays, suffer from poor white balance correction, resulting in color casts like reddish or purplish tones despite existing methods being unsuitable due to significant differences in imaging characteristics.
Innovation Solution
A method involving a reference image sensor with a type 2 color filter array, like RGGB, is used to determine a conversion matrix and white balance compensation parameter for a target image sensor with a type 1 array, like RCCG, using quantum efficiency response curves and Planckian curves to adaptively correct white balance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a reference image sensor with a type 2 color filter array (e.g., RGGB) is used for white balance correction, then the white balance correction method works well for reference sensors, but it cannot achieve good correction effects for target image sensors with type 1 color filter arrays (e.g., RCCG) due to significant differences in imaging characteristics
Solution Approach 1:
The patent transforms the white balance correction approach by changing from using fixed compensation parameters to using quantum efficiency response curves as the basis for determining correction parameters. By extracting response curve characteristics and comparing them across different color filter arrays, the system adapts the correction method to match the specific imaging characteristics of each sensor type, thereby resolving the contradiction between reliability for reference sensors and adaptability to target sensors with different CFA configurations
Solution Approach 2:
The patent introduces quantum efficiency response curves as an intermediary element between the reference image sensor and target image sensor. These response curves serve as a bridge that captures the imaging characteristics of different sensors, enabling the system to translate white balance correction strategies from reference sensors to target sensors with different color filter arrays. This intermediary mechanism allows the correction method to be adapted to various sensor types while maintaining accuracy
2Ease of operation
If existing white balance correction methods are applied to RCCG sensors, then the correction process is simple, but color casts occur and good white balance correction effects cannot be achieved
Solution Approach 1:
The patent applies preliminary action by pre-determining the quantum efficiency response curve characteristics for different color filter arrays before actual white balance correction is needed. The system pre-calculates the mapping relationships between different CFA types and stores these characteristics for later use. This preliminary preparation enables the correction process to be both simple (automated lookup and application) and reliable (based on pre-analyzed sensor characteristics)
Data Source
AI summary
Disclosed are a white balance correction method for images, a storage medium, and an electronic device. The method includes: determining a first quantum efficiency response curve for a reference image sensor, determining a second quantum efficiency response curve for a target image sensor, where a color filter array of the target image sensor is different from that of the reference image sensor; determining a target matrix for conversion between the second quantum efficiency response curve and the first quantum efficiency response curve; determining a first white balance Planckian curve for the target image sensor; determining a white balance compensation parameter adaptable to the target image sensor based on the target matrix, the first white balance Planckian curve, and a first image collected by the target image sensor; performing, based on the white balance compensation parameter, white balance correction on a second image collected by the target image sensor.