基于零亏损冗余删减策略的最优光谱特征选择算法

为了以最小的代价筛选出最优的光谱特征，从信息亏损角度提出了一种Filter型光谱特征选择算法。该算法依据联合互信息的大小对特征进行排序，并采用一种零信息亏损原则对排序后特征全集中的冗余特征进行判断和删减。这样既能获得一个规模较小并可表现整个原始光谱特征的最优光谱特征子集，又减小了由冗余特征删减带来的信息亏损。

An Optimal Spectral Feature Selection Algorithm Based on Zero Loss Redundancy Reduction Strategy

In order to select optimal spectral features at the minimum cost, a Filter type algorithm for spectral feature selection is proposed from the perspective of information loss. The algorithm sorts the features according to the joint mutual information size and uses a zero information loss principle to judge and reduce the redundant features of the sorted feature set. In this way, a small and optimal subset of spectral features can be obtained, which can represent the whole original spectral features, and the information loss caused by the deletion of redundant features can be reduced.