AUTOMATIC REMOTE SENSING IMAGE CLASSIFICATION METHOD BASED ON SPECTRAL ANGLE AND SPECTRAL DISTANCE

The remote sensing image classification is a key issue and hot topic in remote sensing image processing domain. Considering that the classification results of methods based on spectral angle or spectral distance are usually not satisfying, a novel remote sensing image classification method based on the combination of spectral angle and spectral distance is proposed in this paper. The proposed method utilizes the complementary of them to classify an image, that spectral angle is not sensitive to image gray. Moreover, based on the actual category of samples, weights of spectral angle and distance are automatically adjusted during the training process. Statistical and visual results show that, the proposed method is superior to methods respectively based on spectral angle and spectral distance in terms of visual effect, while overall classification accuracy and Kappa coefficient also confirm its superior performance.