Abstract
Presented here Is an algorithm that partitions a digitized multispectral image into parts that correspond to objects in the scene being sensed. The algorithm partitions an image into successively smaller rectangles and produces a partition that tends to minimize a criterion function.
Supervised and unsupervised classification techniques can be applied to partitioned images. This partition- then-classify approach is used to process Images sensed from aircraft and the ERTS-1 satellite, and the method is shown to give relatively accurate results in classifying agricultural areas and extracting urban areas.
LARS Tech Report Number
101873
Date of this Version
January 1973
Recommended Citation
Robertson, T. V., "Extraction and Classification of Objects in Multispectral Images" (1973). LARS Technical Reports. Paper 118.
https://docs.lib.purdue.edu/larstech/118