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Remote Sensing Image Color Correction Method Based on Automatic Piecewise Polynomial Method

机译:基于分段自动多项式的遥感图像色彩校正方法

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In the process of remote sensing image restoration, color correction is very important. The polynomial algorithmcolor correction method based on standard color card is the most commonly used method. However, the traditional polynomial fitting method needs to determine the most appropriate combination of polynomials, and only one polynomial function fitting method is used. So it is difficult to guarantee high accuracy and good generalization performance at the same time. In order to solve the above problems effectively, this paper proposes an automatic piecewise polynomial fitting method. This study established the mapping between collected RGB value and standard RGB value through the calibration of the X-rite Color Checker, and represented the color difference by computing $Delta E$ in CIELab color space. This improved algorithm adopts the idea of segmentation to select the most suitable function in different intervals, and the interval of segmentation is automatically determined by the chromatic aberration standard. The experimental results show that this algorithm has high correction accuracy and this algorithm is more adaptable to photos under different lighting conditions.
机译:在遥感图像恢复过程中,色彩校正非常重要。基于标准色卡的多项式算法色彩校正方法是最常用的方法。但是,传统的多项式拟合方法需要确定最合适的多项式组合,并且仅使用一种多项式函数拟合方法。因此,难以同时保证高精度和良好的泛化性能。为了有效解决上述问题,提出了一种自动分段多项式拟合方法。本研究通过X-rite Color Checker的校准建立了收集的RGB值和标准RGB值之间的映射,并通过在CIELab颜色空间中计算$ \ Delta E $来表示色差。改进后的算法采用分割的思想在不同的间隔中选择最合适的函数,并且分割的间隔由色差标准自动确定。实验结果表明,该算法具有较高的校正精度,并且更适合不同光照条件下的照片。

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