Multispectral image compression by an on-board scene segmentation

This paper investigates an on-board unsupervised feature extraction method that reduces the complexity and costs associated with the analysis of multispectral images and data transmission, storage, archival and distribution as well. Typically in remote sensing a scene is represented by a pixel-oriented features. It is possible to. reduce data redundancy by an unsupervised segment-feature extraction process, where the segment-features, rather than the pixel-features, are used for multispectral scene representation. The algorithm partitions the observation space into exhaustive set of disjoint segments. Then, pixels belonging to each segment are characterized by segment features. Illustrative examples are presented, and the performance of features is investigated