On the Texture of Multi-spectral and Super-dimensional Images

This paper proposes a new concept of remote sensed image, which can be considered as the mapping mode of the spectral space for ground features to the projective space that is two-dimensional imaging space. This concept can express well the texture information in multi-spectral and super-dimensional images, as well as that in single band image or black-white images. In order to analyze the texture information in multi-spectral and super-dimensional images, a necessary way is the coding for spectral vector of every pixel with all the spectral information. The texture of multi-spectral and super-dimensional images is based upon that kind of coding. Several approaches have been proposed for the coding of spectral vector: the coding based on the spectral similarity, the coding based on the density analysis of spectral space, the coding based on the image analysis of principal components, etc. The result of texture classifications based on one way of coding has been given out to show the effectiveness of the proposed method.