Hyperspectral remote sensing technology has the unique advantages of reflecting the spatial and spectral characteristics of remote sensing objects at the same time, but these advantages also bring such problems as too many bands and their strong correlation, high data redundancy, and difficult further processing and utilization.Dimensionality reduction can reduce redundant information in the data and improve the processing efficiency.As an important method of dimensionality reduction, feature extraction has the advantage of fast dimensionality reduction.Therefore, feature extraction is of great significance to the application of hyperspectral images.This paper introduces the basic principle of hyperspectral image dimensionality reduction, classifies and summarizes the advantages and disadvantages of different hyperspectral image feature extraction methods, points out the problems in the research of hyperspectral image feature extraction methods, and puts forward the development trend of hyperspectral image feature extraction technology.