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A knowledge-integrated stepwise optimization model for feature mining in remotely sensed images
2003
International Journal of Remote Sensing
The selection of features, including spectral, texture, shape, size, and signal strength, is an important step in computerized information analysis of remotely sensed images. A feature space, which can be generally understood as a multidimensional space consisting of multiple individual features, can be modelled by estimating the distribution of the whole space with prior assumed probability distribution functions (PDFs) once only. However, due to the interoverlapping phenomenon among points or
doi:10.1080/0143116031000114833
fatcat:ze2ifok2bbg4lfubfjjnjl4qey