Gr-Gb Gain Imbalance Reduction in Bayer Pattern Digital Cameras
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Solution Overview
Problem
Digital cameras with CMOS sensors face Gr-Gb gain imbalance, leading to image artifacts and reduced edge sharpness due to differences in green cell gain, which existing methods either fail to address effectively or compromise image quality by averaging green cells or limiting interpolation methods.
Innovation Solution
An activity-based system and method that computes activity measures for adjacent green cells, calculates green precompensation factors, and blends local green pixel amplitudes based on image activity to reduce Gr-Gb gain imbalance, maintaining edge sharpness and compatibility with various interpolation methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If green cells are averaged to remove Gr-Gb gain imbalance, then gain imbalance is reduced, but edge sharpness is lost
Solution Approach 1:
The patent applies different processing strategies to different local regions of the image based on activity measures. In low-activity regions, averaging is applied to reduce gain imbalance, while in high-activity regions, edge-preserving methods are used to maintain sharpness. This local differentiation resolves the contradiction by adapting the processing approach to the specific characteristics of each region.
Solution Approach 2:
The patent dynamically adjusts the processing approach based on computed activity measures for each local region. The system transitions between different processing modes (averaging vs. edge-preserving) depending on the detected image content characteristics, rather than applying a fixed processing method throughout the entire image.
2Reliability
If CFA interpolation methods are made insensitive to Gr-Gb gain imbalance, then gain imbalance is removed, but the choice of interpolation methods is limited
Solution Approach 1:
The patent performs gain imbalance correction as a preliminary step before CFA interpolation. By pre-compensating the green channel values based on activity measures and surrounding pixel relationships, the system enables the use of various interpolation methods without being constrained by gain imbalance issues, thus maintaining versatility while ensuring reliability.
3Reliability
If some CFA interpolation methods are used to address Gr-Gb gain imbalance, then gain imbalance is reduced, but edge sharpness is reduced
Solution Approach 1:
The patent computes activity measures for each local region and applies different processing approaches accordingly. In high-activity regions containing edges, the system uses edge-preserving methods that maintain sharpness while still addressing gain imbalance. In low-activity regions, more aggressive averaging can be applied since edge preservation is less critical.
Data Source
AI summary
An activity-based system for, and method of, reducing Gr-Gb gain imbalance and a digital camera incorporating the system or the method. In one embodiment, the system includes: (1) a sensor configured to provide a input Bayer pattern array containing amplitudes corresponding to Gr and Gb cells and (2) a processor coupled to the sensor and configured to (2a) compute for at least some of the Gr and Gb cells: activity measures for pluralities of adjacent, same-type cells, green precompensation factors based on the activity measures, averages for the pluralities of adjacent, same-type cells and averages for pluralities of adjacent, opposite-type cells and (2b) use the green precompensation factors, the averages for the pluralities of adjacent, same-type cells and the averages for the pluralities of adjacent, opposite-type cells to form an output Bayer pattern in which the Gr-Gb gain imbalance is reduced.