[Research on spectral classification algorithm based on spatial feature].

With the wide use of imaging spectroscopy, applying data cubes to classification and identification of materials has been developed to be an important research content. The classification algorithms play a vital role in accuracy and precision of object identification. The most common classification algorithms mainly make use of the information gained from spectral dimension and classify the materials based on spectral match. The material reflectance spectra collected by imaging spectroscopy is determined not only by the sorts, but also by the geometry structure and roughness of material surface, and so on. Then classification and identification algorithms only using the reflection spectra have errors to some extent. This paper puts forward an algorithm based on the common classification algorithms that controls the classification process by using the spatial feature of image to promote the correctness of classification. This algorithm was applied to identify the true leaves from the fake ones. The result shows preferable spatial continuity. To a great extent, the algorithm overcomes "ma pixel" domino effect, and is proved valid.