Remote sensing image analysis by aggregation of segmentation-classification collaborative agents

Highlights：

• Two new approaches for collaborative remote sensing image analysis are presented. They both are based on a multi-paradigm framework which uses classification to guide a segmentation process.

• The proposed methods aggregate many mono-class extractors in order to make multi-class remote sensing image classification.

• Experiments show that the proposed methods give better results (both in terms of classification and segmentation) than a hybrid object-based approach as well as a deep learning approach, even if the training data is limited in quantity and quality.