为了防止彩色数码反射显微镜的白平衡算法失效,提高图像颜色采集精度,提出了基于非RAW数据的数码相机色度特征化方法。首先,利用色卡中性色块建立基于幂函数的非线性校正模型,将非RAW数据转换为与场景辐亮度线性相关的数据。然后,建立色度特征化模型。最后,通过实验测试非RAW数据校正前后的色度特征化精度,并分析光源亮度变化对非线性校正模型及色度特征化精度的影响。结果表明,校正后的非RAW数据将提高色度特征化精度,对于线性色度特征化模型效果尤为明显。同时,光源亮度改变将引起非线性校正模型以及色度特征化精度的变化,当亮度变化不剧烈时,可采用通用非线性校正模型。

In order to prevent the failure of the white balance algorithm of color digital reflection microscope and improve the accuracy of color acquisition, a colorimetric characterization method based on non-RAW data is proposed. First, a nonlinearity correction model based on power function is established by using the neutral patches of the color card. The non-RAW data is converted into the data linearly related to the scene radiance. Then, the colorimetric characterization model is established. Finally, experiments are conducted to test the accuracy of colorimetric characterization model before and after correction of non-RAW data, and the influence of luminance change of light source on nonlinearity correction model and the accuracy of colorimetric characterization is analyzed. The results show that the corrected non-RAW data will improve the accuracy of colorimetric characterization, and the improvement effect is especially obvious for the linear colorimetric characterization model. At the same time, the luminance change of the light source will cause the variation of the nonlinear correction model as well as the accuracy of colorimetric characterization, but when the luminance change is not sharp, the general nonlinear correction model can be used.