关键词: 显微高光谱, 神经分类, 端元, 特征光谱, K近邻分类

Abstract:

In the nerve repair surgery, the correct identification of nerve fascicles is the key to achieve good repairing result. This article will apply microscopic hyperspectral imaging technology in nerve classification and do some experimental researches on the feasibility of nerve classification. The results showed that it had certain effect. First, the authors uses microscopic hyperspectral neural collecting system to get the rabbit's motor and sensory nerves' hyperspectral image data, and then did pre-processing. Second, we obtained endmembers by using the pure endmember extraction algorithm and got each category's characteristic spectrum. Last, we analyzed the characteristics and differences of spectrum to find suitable classification algorithms. Based on K-nearest neighbor classifier, the authors used two classic and simple distance measure algorithms involve euclidean distance and spectral angle match distance to do classification in the experimental data. The results gotten by analying the advantages and disadvantages of the two methods can lay an important foundation for seeking other appropriate and more targeted classification methods.

Key words: microscopic hyperspectral imaging, nerve classification, endmember, characteristic spectrum, K-NN classification