Morphological independence and hyperspectral image indexing
Manuel Graña, Orlando Maldonado, David Vicente · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
Content based image retrieval (CBIR) systems are database management systems that emply features extracted from the image as the indices used in the search of the database. Images are retrieved on the basis of the similarity with the query image. Indexing hyperspectral images is a special case of CBIR, with the added complexity of the high dimensionality of the pixels. We propose the use of endmembers as the hyperspectral image characterization. We thus define a similarity measure between hyperspectral images based on these image endmembers. The endmembers must be induced from the image data in order to automate the process. Enmembers can be assumed to be morphologically independent, a notion originally introduced to study the noise robustnes of Morphological Networks. For this induction we use Associative Morphological Memories (AMM) as detectors of Morphological Independence conditions.