Vehicle Vision System Color Correction Using Pre-computed Matrices
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Solution Overview
Problem
Vehicle imaging systems face challenges in accurately displaying and processing color images due to color variations caused by different lighting conditions, making it difficult to distinguish object colors, especially under nighttime driving conditions.
Innovation Solution
A color correction matrix (CCM) algorithm is used offline to pre-process and generate 3×3 matrix values for each color temperature along the Planckian Locus, reducing online computing power and enhancing color accuracy by utilizing polynomial curves and PID control for visual pleasing color balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time color correction is performed using complex algorithms, then color accuracy is improved, but computing power requirements and processing time increase
Solution Approach 1:
The patent pre-calculates and stores color correction matrices for various lighting conditions before actual image processing. By performing the computationally intensive algorithm work offline and storing results in lookup tables, the system avoids real-time computation of complex color correction algorithms, thus maintaining high color accuracy while reducing online computing power requirements
Solution Approach 2:
The patent creates simplified copies of color correction data in the form of pre-computed matrices and lookup tables. Instead of executing the full complex algorithm during real-time processing, the system uses these pre-generated matrix copies to perform rapid color corrections, significantly reducing processing time and computing power consumption while preserving color accuracy
2Measurement precision
If complex color correction algorithms are executed in real-time, then color accuracy is improved, but processing time increases
Solution Approach 1:
The system performs color correction matrix calculations in advance during system initialization or offline processing. By preparing correction matrices for various lighting scenarios before actual image processing begins, the patent eliminates the need for time-consuming real-time algorithm execution, thus reducing processing time while maintaining color accuracy through the use of pre-computed correction data
Solution Approach 2:
The patent creates pre-computed matrix copies that serve as rapid lookup tables during real-time processing. These matrix copies contain pre-calculated color correction parameters for different lighting conditions, allowing the system to perform accurate color corrections by simple matrix multiplication operations rather than executing complex algorithms, thereby significantly reducing processing time
3Measurement precision
If color correction data is stored for multiple illumination scenarios, then color accuracy under various lighting conditions is improved, but memory requirements increase
Solution Approach 1:
The patent implements adaptive memory allocation where different levels of color correction data granularity are stored for different lighting scenarios. Frequently encountered or critical lighting conditions receive more detailed correction matrices, while less common scenarios use coarser approximations. This local differentiation of data quality allows the system to maintain high color accuracy for important cases while reducing overall memory consumption
Solution Approach 2:
The system dynamically adjusts the resolution and detail level of stored color correction matrices based on operational requirements. By changing parameters such as matrix size, color space depth, and scenario coverage, the patent optimizes the balance between memory usage and color accuracy, allowing the system to adapt memory allocation to actual processing needs rather than maintaining fixed high-resolution data for all possible scenarios
Data Source
AI summary
A method for processing color image data captured by a vehicular camera to correct for color error includes providing a color camera with an imaging array having a plurality of photosensors, disposing one or more spectral filters at or in front of photosensors of the imaging array, and disposing the color camera at a vehicle so as to have a field of view exterior of the vehicle. An image processor is provided that processes image data captured by the color camera. The processing of image data includes processing image data in a color correction loop to correct color variation due to lighting conditions so that images derived from captured image data are color corrected. The color correction accounts for color of light emitted by an illumination source.