Hyper spectral picture evaluation is an effective tool for analyzing large volumes of excessive-dimensional facts. In this paper, a brand new method to hyper spectral photo analysis is provided that integrates fuzzy C-means clustering and function choice. The proposed approach permits for significant quantification of the exclusive additives within a hyper spectral image and allows for the identification of key spectral functions. Additionally, the fuzzy C-way clustering approach is used to identify awesome clusters within the photograph, supplying a useful method for studying complicated datasets. The characteristic choice technique facilitates to further lessen the data set and to achieve the maximum meaningful capabilities for further evaluation. The overall performance of the proposed technique is evaluated via the use of an actual-international hyper spectral photo, and the effects exhibit the effectiveness of the proposed technique for hyper-spectral photograph analysis.