Development of Data Reduction Function for Hyperspectral Imaging
Development of Data Reduction Function for Hyperspectral Imaging
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DOI：
10.1556/progress.3.2007.4
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发表时间：
2007-12
影响因子：
--
通讯作者：
F. Firtha
中科院分区：
文献类型：
--
作者：
F. Firtha
已经开发了用于控制高光谱设备的校准和测量周期的算法。特殊的校准和预处理方法是必要的，以获得合适的信号电平和可接受的测量重复性。从而降低了近红外传感器噪声的影响，提高了信号电平，同时保证了稳定性。为了研究适合于统计分析的对象数量的属性，所获得的超立方体的巨大尺寸（每个对象千兆字节）应该通过实时的矢量到标量数学运算符来减少以提取所需的特征。所开发的算法能够在扫描过程中计算操作员的分数，并且矩阵显示为伪图像以显示表面上的属性分布。在初步实验中，必须通过分析样本集来确定算子。以贮藏胡萝卜为模型样品，研究了利用高光谱特性检测水分损失的方法。确定不同组织的合适操作员有助于分析和模拟干燥过程，并控制存储。对不同胡萝卜品种在不同贮藏条件下的高光谱数据进行了测试。采用改进的测量方法，选择合适的算子，得到的光谱参数能较好地描述胡萝卜不同组织的水分损失。
Algorithms have been developed for controlling the calibration and the measurement cycles of hyperspectral equipment. Special calibration and preprocessing methods were necessary to obtain suitable signal level and acceptable repeatability of the measurements. Therefore, the effect of the noise of NIR sensor was decreased, the signal level was enhanced and stability was ensured simultaneously. In order to investigate the properties of the number of objects suitable for statistical analysis, the enormous size of acquired hypercube (gigabytes per object) should be reduced by vector-to-scalar mathematical operators in real-time to extract the desired features. The algorithm developed was able to calculate the score of operators during scanning and the matrices were displayed as pseudo-images to show the distribution of the properties on the surface. The operators had to be determined by analysis of a sample set in preliminary experiments. Stored carrot was chosen as a model sample for investigation of the detection of moisture loss by hyperspectral properties. Determination of the proper operator on different tissues could help to analyze and model drying process and to control storage. Hyperspectral data of different carrot cultivars were tested under different storage conditions. Using improved measurement method the spectral parameter of the suitable operator described quite well the moisture loss of the different carrot tissues.