自动调焦方法已被广泛应用到各种光学仪器中。为了解决推扫式高光谱相机自动调焦问题, 提出了一种利用基于四元数小波变换的光谱质量评价函数估计相机焦距的方法。首先将推扫线上单行光谱数据顺序排列成一个二维矩阵, 利用四元数小波变换对光谱像元矩阵进行分解得到低频和高频4个子带。通过对低频和高频的幅值和相位信息构造光谱质量评价函数, 指导相机自动调焦。调焦过程中, 利用自动调焦机构按一定步长旋转镜头, 计算不同离焦状态下的光谱质量指标值, 拟合光谱质量指标值与镜头伸缩量之间的高斯分布函数, 最终估算最佳调焦量。实验表明, 提出的光谱质量评价函数灵敏度高、准确度强。该调焦方法仅利用单行光谱数据进行调焦, 调焦准确。

The auto-focusing method has been widely incorporated in various optical instruments. To address the issue of auto-focusing for push-broom hyperspectral cameras, a method was proposed for estimating the optimal focus of a camera by employing a spectral quality evaluation function based on quaternion wavelet transform. A single line spectral data of the push sweep line was transformed into a two-dimensional matrix, and the matrix was subsequently decomposed into four low frequency and high frequency sub-bands. The spectral quality evaluation function was developed by incorporating the low frequency and high frequency amplitude and phase information for realizing the auto-focus feature. During the focusing process, the spectral quality metrics were calculated for different foci by rotating the lens at a certain stride length through an auto-focus mechanism. A Gaussian distribution function was fit between the spectral quality metrics and the extent of lens expansion and contraction, and the optimal focus was thereby estimated. Obtained results indicate that the proposed spectral quality evaluation function has superior sensitivity and accuracy. Furthermore, the proposed auto-focus method has superior accuracy owing to the usage of a single line of spectral data for focusing.