Illuminant Estimation Using PCA Subspaces
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Solution Overview
Problem
Existing white balance correction programs in digital cameras struggle to quickly and accurately estimate the correct illuminant in various lighting conditions, leading to inaccurate color representation of objects in images.
Innovation Solution
An image apparatus that utilizes a capturing system and an illuminant database, where the database includes subspaces of multi-dimensional color information computed using Principal Components Analysis, allowing for efficient and accurate estimation of the illuminant by comparing input colors to possible illuminants and applying appropriate color adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing white balance correction programs are used to estimate illuminant color, then color representation accuracy can be improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The illuminant estimation process is segmented into discrete steps: extracting color information from image regions, comparing against pre-computed subspace models for different illuminants, and selecting the best match. This segmentation reduces computational complexity by breaking down a complex estimation problem into manageable components, while maintaining accuracy through systematic comparison of multiple illuminant candidates.
Solution Approach 2:
Subspace models for multiple illuminants are pre-computed and stored before image processing. This preliminary action eliminates the need for complex real-time calculations during image processing, as the system only needs to compare extracted colors against pre-available subspace representations. The pre-computation handles the computationally intensive portions, leaving simpler comparison operations for actual image processing.
2Measurement precision
If existing white balance correction programs are used to estimate illuminant color, then color representation accuracy can be improved, but processing time increases
Solution Approach 1:
The subspace models for various illuminants are pre-computed and stored in advance. During image processing, the system extracts color information and compares it against these pre-available subspace models, eliminating the need for time-consuming real-time calculations. This preliminary computation approach significantly reduces processing time while maintaining estimation accuracy.
Solution Approach 2:
Instead of performing complex calculations during image processing, the system uses simplified subspace copies or representations of illuminant characteristics that were pre-computed. These subspace models serve as efficient proxies for the full illuminant color information, allowing rapid comparison and matching without the computational burden of analyzing complete color data in real-time.
3Measurement precision
If multi-dimensional color information is used for illuminant estimation, then estimation accuracy improves, but computational requirements increase
Solution Approach 1:
The system extracts only the essential color information needed for illuminant estimation from the full multi-dimensional color space. By identifying and working with the most significant color characteristics (such as dominant wavelengths and saturation levels) rather than processing all dimensional data, the system maintains estimation accuracy while reducing computational energy requirements.
Solution Approach 2:
Different regions of the color space are treated with different levels of computational detail. The system applies more sophisticated analysis to critical color dimensions that significantly impact illuminant identification, while using simpler processing for less influential dimensions. This localized quality approach maintains accuracy where it matters most while conserving computational resources.
Data Source
AI summary
An image apparatus for providing an estimated illuminant of a scene and subsequently providing an adjusted image of the scene includes a capturing system and an illuminant database. The capturing system captures information for an input image of the scene. The input image is defined by a plurality of input colors. The illuminant database includes a separate subspace of information for a plurality of possible illuminants. The subspaces can be created from multi-dimensional color information from its respective possible illuminant that is computed using Principal Components Analysis. This allows for more accurate illuminant estimation of the scene and the use of Principal Components Analysis to generate the one or more subspaces allows for accurate and relatively easy generation of the subspaces. Additionally, the image apparatus can include a control system that compares the input colors to the subspaces in the illuminant database.