Luminance Distribution Measurement With Spectral-RGB Feedback Correction
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Solution Overview
Problem
Existing luminance and color measurement systems fail to accurately reproduce the human visual perception of color due to differences in spectral sensitivity between recording devices and the human eye, leading to suboptimal color fidelity in digital displays.
Innovation Solution
An algorithm optimizes the recorded image in a feedback loop to ensure differences between spectral correction and RGB parameters are below a set threshold, maintaining XYZ values within distinguishability and bit resolution thresholds without optimizing RGB parameters for cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard RGB measurement systems are used, then device complexity is reduced, but color fidelity and measurement precision deteriorate due to spectral sensitivity mismatches
Solution Approach 1:
The patent introduces an intermediary spectral correction algorithm that acts as a mediator between the standard RGB measurement system and human visual perception. The algorithm converts RGB values to spectral power distributions, applies human eye sensitivity corrections, and reconstructs accurate color measurements without requiring complex physical hardware modifications.
Solution Approach 2:
The patent transforms the measurement parameters from direct RGB values to spectral power distributions through mathematical conversion. By changing the parameter representation and applying spectral sensitivity corrections, the system achieves human-perception-accurate measurements while maintaining standard RGB sensor hardware.
2Measurement precision
If 24-bit color depth is used to maintain several million color distinctions, then color fidelity improves, but image memory complexity increases to 18 MB per eye
Solution Approach 1:
The patent applies partial spectral correction only to the extent necessary for human visual perception accuracy. Rather than processing all possible color variations at full 24-bit depth throughout the system, the correction is applied selectively during measurement analysis, reducing unnecessary memory overhead while maintaining perceptual accuracy.
3Ease of operation
If luminance range is compressed to 8 bits per channel for display compatibility, then ease of operation improves, but measurement precision and luminance differentiation capability deteriorate
Solution Approach 1:
The patent moves the precision preservation from the spatial dimension (8-bit per channel) to the spectral dimension. By performing spectral corrections and measurements in the spectral power distribution domain before converting to display-compatible RGB values, the system maintains high luminance differentiation capability while producing display-ready output.
Data Source
Figure 1
AI summary
The method of measuring and analyzing luminance distributions uses an algorithm that continuously optimizes in a feedback loop recorded image for at least 2 different multi-colored light sources in such a way that differences recorded by equipment with spectral correction and differences recorded after converting the XYZ parameters into RGB parameters of a given camera, were below a set threshold, located within a single bit of the stored value of tristimulus/RGB components to obtain the highest possible color fidelity in XYZ system in order to keep the XYZ values within the distinguishability threshold, while not optimizing the RGB parameters for the camera, and the threshold of distinguishability is set at a level from 5% to 10% below the threshold of distinguishability of the luminance gradient and color for the human eye, and optimization is carried out to obtain the highest possible color fidelity in the RGB system to keep the RGB values within the bit resolution threshold for the recorded luminance span range, without optimizing the XYZ parameters for the needs of the human eye.