Multivariate Texture Measured by Local Binary Pattern for Multispectral Image Classification

Local Binary Pattern is a new texture measure which is theoretically simply but powerful. When used in remote sensing multi-channel image processing, the multivariate version of LBP operator should be considered. In this paper, a multivariate LBP operator was proposed to calculate multivariate texture for multi-spectral remote sensing image. Both single-band texture and multivariate texture were employed in the classification process. Segmented Minimum Noise Fraction transform was conducted before classification to reduce features. Experiment shows that compared to spectral classification, the classification accuracy can be significantly improved when the proposed classification scheme was used.