Pest image classification method based on context sensing dictionary learning

The invention provides a pest image classification method based on context sensing dictionary learning. The method comprises the following steps that: context sensing information of pest images in the known category is added into a pest image sample base to obtain a plurality of types of training samples, a learning function is constructed, and the training samples are used for completing pest image redundant dictionary learning; the pest images to be classified are subjected to preprocessing to obtain test samples; the test samples are subjected to sparse representation dimensionality reduction processing; the test samples subjected to the sparse representation dimensionality reduction processing are read into a sparse representation classifier, and the residual error of the context sensing information of the test samples and various types of the training samples is calculated according to a redundant dictionary obtained through learning; and the residual error of the context sensing information of the test samples and various types of the training samples is analyzed, and the categories of the test samples are determined. The pest image classification method has the advantages that the precision and the efficiency of the pest image classification in complicated scenes can be improved, and a traditional crop pest diagnosis mode is improved.