用共识图像实现多相机光谱成像的精准色彩校准
Inter-Camera Color Correction for Multispectral Imaging with Camera Arrays Using a Consensus Image
- 通过统计位置参数生成共识图像作为校准基准
- 线性回归校准后PSNR提升1.15 dB，iCID降低2.81
- 适合医疗、农业等多相机光谱成像应用
本文提出一种基于共识图像的多相机阵列光谱成像跨相机色彩校准新方法。在医疗、农业和环境监测中，多相机阵列成像日益重要。由于制造差异、噪声或设备变化，各相机像素敏感度不一致，影响分类精度，需进行色彩校准。现有方法仅选取某一相机图像作为参考，忽略了其他图像的颜色信息。本文方法不依赖单一参考，而是利用位置参数等统计信息生成共识图像作为校准基础。实验表明，该方法使线性回归色彩校准的PSNR提升1.15 dB，改进色差（iCID）降低2.81。
原文摘要 · Abstract (English)
This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural, and environmental processes. Due to fabrication differences, noise, or device altering, varying pixel sensitivities occur, influencing classification processes. Therefore, color calibration between the cameras is necessary. In existing methods, one of the camera images is chosen and considered as a reference, ignoring the color information of all other recordings. Our new approach does not just take one image as reference, but uses statistical information such as the location parameter to generate a consensus image as basis for calibration. This way, we managed to improve the PSNR values for the linear regression color correction algorithm by 1.15 dB and the improved color difference (iCID) values by 2.81.
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