LumChromNet: A Dual-Path Neural Network Framework for Optical Measurement in VR Systems

Traditional optical instruments for VR glasses are costly, bulky, and complex, while current automated solutions lack sufficient measurement range and accuracy. To optimize VR glasses' optical characteristics, we introduce LumChrom-Net, an innovative dual-path neural network framework for automated production solutions. LumChromNet comprises two key components: First, for luminance calibration, it utilizes a stacked neural network combining Gaussian Process Regression (GPR) and Multilayer Perceptron (MLP) to capture luminance features under low illumination and to process nonlinear characteristics across different light levels. By integrating the multiscale hybrid features of GPR with the perceptual capabilities of MLP and fusing through Random Forest, it achieves high precision calibration and a wide range under limited data samples. Second, for chromaticity calibration, it employs the Adaptive Multidimensional Color Space Transformation Network (AMCS-TransNet), expanding the dimensions of the color space and incorporating a linear transformation layer with a dynamic learning matrix to enhance the stability of color space conversion. This ensures accurate conversion from RGB to CIE XYZ space, adaptable to white points across different dimensions. LumChromNet extends the luminance grayscale range to 0–255, with a fitting error below <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.87\%$</tex>), and enhances color space <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{R}^{2}$</tex> to 0.998 with an average error within <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1.5\%$</tex>). It expands the luminance measurement range to 0–250 cd/m<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>and maintains optical property errors under <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pm 5\%$</tex>, providing a cost-effective, flexible, and automated strategy for VR glasses and other devices.